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int64 0
731k
| package
stringlengths 2
98
⌀ | name
stringlengths 1
76
| docstring
stringlengths 0
281k
⌀ | code
stringlengths 4
8.19k
| signature
stringlengths 2
42.8k
⌀ | embed_func_code
sequencelengths 768
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|---|---|---|---|---|---|---|
727,786 | fysom | _enter_state |
Executes the callback for onenter_state_ or on_state_.
| def _enter_state(self, e):
'''
Executes the callback for onenter_state_ or on_state_.
'''
for fnname in ['onenter' + e.dst, 'on' + e.dst,
'on_enter_' + e.dst, 'on_' + e.dst]:
if hasattr(self, fnname):
return getattr(self, fnname)(e)
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727,787 | fysom | _is_base_string |
Returns if the object is an instance of basestring.
| def _is_base_string(self, object): # pragma: no cover
'''
Returns if the object is an instance of basestring.
'''
try:
return isinstance(object, basestring)
except NameError:
return isinstance(object, str)
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] |
727,788 | fysom | _leave_state |
Checks to see if the machine can leave the current state and perform the transition.
This is helpful if the asynchronous job needs to be completed before the machine can
leave the current state.
| def _leave_state(self, e):
'''
Checks to see if the machine can leave the current state and perform the transition.
This is helpful if the asynchronous job needs to be completed before the machine can
leave the current state.
'''
for fnname in ['onleave' + e.src, 'on_leave_' + e.src]:
if hasattr(self, fnname):
return getattr(self, fnname)(e)
| (self, e) | [
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727,789 | fysom | _reenter_state |
Executes the callback for onreenter_state_.
This allows callbacks following reflexive transitions (i.e. where src == dst)
| def _reenter_state(self, e):
'''
Executes the callback for onreenter_state_.
This allows callbacks following reflexive transitions (i.e. where src == dst)
'''
for fnname in ['onreenter' + e.dst, 'on_reenter_' + e.dst]:
if hasattr(self, fnname):
return getattr(self, fnname)(e)
| (self, e) | [
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] |
727,790 | fysom | can |
Returns if the given event be fired in the current machine state.
| def can(self, event):
'''
Returns if the given event be fired in the current machine state.
'''
return (
event in self._map and
((self.current in self._map[event]) or WILDCARD in self._map[event]) and not
hasattr(self, 'transition'))
| (self, event) | [
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] |
727,791 | fysom | cannot |
Returns if the given event cannot be fired in the current state.
| def cannot(self, event):
'''
Returns if the given event cannot be fired in the current state.
'''
return not self.can(event)
| (self, event) | [
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] |
727,792 | fysom | is_finished |
Returns if the state machine is in its final state.
| def is_finished(self):
'''
Returns if the state machine is in its final state.
'''
return self._final and (self.current == self._final)
| (self) | [
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] |
727,793 | fysom | isstate |
Returns if the given state is the current state.
| def isstate(self, state):
'''
Returns if the given state is the current state.
'''
return self.current == state
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] |
727,795 | fysom | trigger |
Triggers the given event.
The event can be triggered by calling the event handler directly, for ex: fsm.eat()
but this method will come in handy if the event is determined dynamically and you have
the event name to trigger as a string.
| def trigger(self, event, *args, **kwargs):
'''
Triggers the given event.
The event can be triggered by calling the event handler directly, for ex: fsm.eat()
but this method will come in handy if the event is determined dynamically and you have
the event name to trigger as a string.
'''
if not hasattr(self, event):
raise FysomError(
"There isn't any event registered as %s" % event)
return getattr(self, event)(*args, **kwargs)
| (self, event, *args, **kwargs) | [
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] |
727,796 | fysom | FysomError |
Raised whenever an unexpected event gets triggered.
Optionally the event object can be attached to the exception
in case of sharing event data.
| class FysomError(Exception):
'''
Raised whenever an unexpected event gets triggered.
Optionally the event object can be attached to the exception
in case of sharing event data.
'''
def __init__(self, msg, event=None):
super(FysomError, self).__init__(msg)
self.event = event
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727,798 | fysom | FysomGlobal |
Target to be used as global machine.
| class FysomGlobal(object):
'''
Target to be used as global machine.
'''
def __init__(self, cfg={}, initial=None, events=None, callbacks=None,
final=None, state_field=None, **kwargs):
'''
Construct a Global Finite State Machine.
Takes same arguments as Fysom and an additional state_field
to specify which field holds the state to be processed.
Difference with Fysom:
1. Initial state will only be automatically triggered for class
derived with FysomGlobalMixin.
2. Conditions and conditional transition are implemented.
3. When an event/transition is canceled, the event object will
be attached to the raised Canceled exception. By doing this,
additional information can be passed through the exception.
Example:
class Model(FysomGlobalMixin, object):
GSM = FysomGlobal(
events=[('warn', 'green', 'yellow'),
{
'name': 'panic',
'src': ['green', 'yellow'],
'dst': 'red',
'cond': [ # can be function object or method name
'is_angry', # by default target is "True"
{True: 'is_very_angry', 'else': 'yellow'}
]
},
('calm', 'red', 'yellow'),
('clear', 'yellow', 'green')],
initial='green',
final='red',
state_field='state'
)
def __init__(self):
self.state = None
super(Model, self).__init__()
def is_angry(self, event):
return True
def is_very_angry(self, event):
return False
>>> obj = Model()
>>> obj.current
'green'
>>> obj.warn()
>>> obj.is_state('yellow')
True
>>> obj.panic()
>>> obj.current
'yellow'
>>> obj.is_finished()
False
'''
if sys.version_info[0] >= 3:
super().__init__(**kwargs)
cfg = dict(cfg)
# state_field is required for global machine
if not state_field:
raise FysomError('state_field required for global machine')
self.state_field = state_field
if "events" not in cfg:
cfg["events"] = []
if "callbacks" not in cfg:
cfg["callbacks"] = {}
if initial:
cfg['initial'] = initial
if events:
cfg["events"].extend(list(events))
if callbacks:
cfg["callbacks"].update(dict(callbacks))
if final:
cfg["final"] = final
# convert 3-tuples in the event specification to dicts
events_dicts = []
for e in cfg["events"]:
if isinstance(e, Mapping):
events_dicts.append(e)
elif hasattr(e, "__iter__"):
name, src, dst = list(e)[:3]
events_dicts.append({"name": name, "src": src, "dst": dst})
cfg["events"] = events_dicts
self._map = {} # different with Fysom's _map attribute
self._callbacks = {}
self._initial = None
self._final = None
self._apply(cfg)
def _apply(self, cfg):
def add(e):
if 'src' in e:
src = [e['src']] if self._is_base_string(
e['src']) else e['src']
else:
src = [WILDCARD]
_e = {'src': set(src), 'dst': e['dst']}
conditions = e.get('cond')
if conditions:
_e['cond'] = _c = []
if self._is_base_string(conditions) or callable(conditions):
_c.append({True: conditions})
else:
for cond in conditions:
if self._is_base_string(cond):
_c.append({True: cond})
else:
_c.append(cond)
self._map[e['name']] = _e
initial = cfg['initial'] if 'initial' in cfg else None
if self._is_base_string(initial):
initial = {'state': initial}
if initial:
if 'event' not in initial:
initial['event'] = 'startup'
self._initial = initial
add({'name': initial['event'],
'src': 'none', 'dst': initial['state']})
if 'final' in cfg:
self._final = cfg['final']
for e in cfg['events']:
add(e)
for event in self._map:
setattr(self, event, self._build_event(event))
for name, callback in cfg['callbacks'].items():
self._callbacks[name] = _weak_callback(callback)
def _build_event(self, event):
def fn(obj, *args, **kwargs):
if not self.can(obj, event):
raise FysomError(
'event %s inappropriate in current state %s'
% (event, self.current(obj)))
# Prepare the event object with all the meta data to pas through.
# On event occurrence, source will always be the current state.
e = self._e_obj()
e.fsm, e.obj, e.event, e.src, e.dst = (
self, obj, event, self.current(obj), self._map[event]['dst'])
setattr(e, 'args', args)
setattr(e, 'kwargs', kwargs)
for k, v in kwargs.items():
setattr(e, k, v)
# check conditions first, event dst may change during
# checking conditions
for c in self._map[event].get('cond', ()):
target = True in c
cond = c[target]
_c_r = self._check_condition(obj, cond, target, e)
if not _c_r:
if 'else' in c:
e.dst = c['else']
break
else:
raise Canceled(
'Cannot trigger event {0} because the {1} '
'condition not returns {2}'.format(
event, cond, target), e
)
# try to trigger the before event, unless it gets cancelled.
if self._before_event(obj, e) is False:
raise Canceled(
'Cannot trigger event {0} because the onbefore{0} '
'handler returns False'.format(event), e)
# wraps the activities that must constitute a single transaction
if self.current(obj) != e.dst:
def _trans():
delattr(obj, 'transition')
setattr(obj, self.state_field, e.dst)
self._enter_state(obj, e)
self._change_state(obj, e)
self._after_event(obj, e)
obj.transition = _trans
# Hook to perform asynchronous transition
if self._leave_state(obj, e) is not False:
obj.transition()
else:
self._reenter_state(obj, e)
self._after_event(obj, e)
fn.__name__ = str(event)
fn.__doc__ = (
"Event handler for an {event} event. This event can be "
"fired if the machine is in {states} states.".format(
event=event, states=self._map[event]['src']))
return fn
class _e_obj(object):
pass
@staticmethod
def _is_base_string(object): # pragma: no cover
try:
return isinstance(object, basestring) # noqa
except NameError:
return isinstance(object, str) # noqa
def _do_callbacks(self, obj, callbacks, *args, **kwargs):
for cb in callbacks:
if cb in self._callbacks:
return self._callbacks[cb](*args, **kwargs)
if hasattr(obj, cb):
return getattr(obj, cb)(*args, **kwargs) | (cfg={}, initial=None, events=None, callbacks=None, final=None, state_field=None, **kwargs) | [
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727,799 | fysom | __init__ |
Construct a Global Finite State Machine.
Takes same arguments as Fysom and an additional state_field
to specify which field holds the state to be processed.
Difference with Fysom:
1. Initial state will only be automatically triggered for class
derived with FysomGlobalMixin.
2. Conditions and conditional transition are implemented.
3. When an event/transition is canceled, the event object will
be attached to the raised Canceled exception. By doing this,
additional information can be passed through the exception.
Example:
class Model(FysomGlobalMixin, object):
GSM = FysomGlobal(
events=[('warn', 'green', 'yellow'),
{
'name': 'panic',
'src': ['green', 'yellow'],
'dst': 'red',
'cond': [ # can be function object or method name
'is_angry', # by default target is "True"
{True: 'is_very_angry', 'else': 'yellow'}
]
},
('calm', 'red', 'yellow'),
('clear', 'yellow', 'green')],
initial='green',
final='red',
state_field='state'
)
def __init__(self):
self.state = None
super(Model, self).__init__()
def is_angry(self, event):
return True
def is_very_angry(self, event):
return False
>>> obj = Model()
>>> obj.current
'green'
>>> obj.warn()
>>> obj.is_state('yellow')
True
>>> obj.panic()
>>> obj.current
'yellow'
>>> obj.is_finished()
False
| def __init__(self, cfg={}, initial=None, events=None, callbacks=None,
final=None, state_field=None, **kwargs):
'''
Construct a Global Finite State Machine.
Takes same arguments as Fysom and an additional state_field
to specify which field holds the state to be processed.
Difference with Fysom:
1. Initial state will only be automatically triggered for class
derived with FysomGlobalMixin.
2. Conditions and conditional transition are implemented.
3. When an event/transition is canceled, the event object will
be attached to the raised Canceled exception. By doing this,
additional information can be passed through the exception.
Example:
class Model(FysomGlobalMixin, object):
GSM = FysomGlobal(
events=[('warn', 'green', 'yellow'),
{
'name': 'panic',
'src': ['green', 'yellow'],
'dst': 'red',
'cond': [ # can be function object or method name
'is_angry', # by default target is "True"
{True: 'is_very_angry', 'else': 'yellow'}
]
},
('calm', 'red', 'yellow'),
('clear', 'yellow', 'green')],
initial='green',
final='red',
state_field='state'
)
def __init__(self):
self.state = None
super(Model, self).__init__()
def is_angry(self, event):
return True
def is_very_angry(self, event):
return False
>>> obj = Model()
>>> obj.current
'green'
>>> obj.warn()
>>> obj.is_state('yellow')
True
>>> obj.panic()
>>> obj.current
'yellow'
>>> obj.is_finished()
False
'''
if sys.version_info[0] >= 3:
super().__init__(**kwargs)
cfg = dict(cfg)
# state_field is required for global machine
if not state_field:
raise FysomError('state_field required for global machine')
self.state_field = state_field
if "events" not in cfg:
cfg["events"] = []
if "callbacks" not in cfg:
cfg["callbacks"] = {}
if initial:
cfg['initial'] = initial
if events:
cfg["events"].extend(list(events))
if callbacks:
cfg["callbacks"].update(dict(callbacks))
if final:
cfg["final"] = final
# convert 3-tuples in the event specification to dicts
events_dicts = []
for e in cfg["events"]:
if isinstance(e, Mapping):
events_dicts.append(e)
elif hasattr(e, "__iter__"):
name, src, dst = list(e)[:3]
events_dicts.append({"name": name, "src": src, "dst": dst})
cfg["events"] = events_dicts
self._map = {} # different with Fysom's _map attribute
self._callbacks = {}
self._initial = None
self._final = None
self._apply(cfg)
| (self, cfg={}, initial=None, events=None, callbacks=None, final=None, state_field=None, **kwargs) | [
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727,800 | fysom | _after_event | null | def _after_event(self, obj, e):
callbacks = ['onafter' + e.event, 'on' + e.event,
'on_after_' + e.event, 'on_' + e.event]
return self._do_callbacks(obj, callbacks, e)
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727,801 | fysom | _apply | null | def _apply(self, cfg):
def add(e):
if 'src' in e:
src = [e['src']] if self._is_base_string(
e['src']) else e['src']
else:
src = [WILDCARD]
_e = {'src': set(src), 'dst': e['dst']}
conditions = e.get('cond')
if conditions:
_e['cond'] = _c = []
if self._is_base_string(conditions) or callable(conditions):
_c.append({True: conditions})
else:
for cond in conditions:
if self._is_base_string(cond):
_c.append({True: cond})
else:
_c.append(cond)
self._map[e['name']] = _e
initial = cfg['initial'] if 'initial' in cfg else None
if self._is_base_string(initial):
initial = {'state': initial}
if initial:
if 'event' not in initial:
initial['event'] = 'startup'
self._initial = initial
add({'name': initial['event'],
'src': 'none', 'dst': initial['state']})
if 'final' in cfg:
self._final = cfg['final']
for e in cfg['events']:
add(e)
for event in self._map:
setattr(self, event, self._build_event(event))
for name, callback in cfg['callbacks'].items():
self._callbacks[name] = _weak_callback(callback)
| (self, cfg) | [
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727,802 | fysom | _before_event | null | def _before_event(self, obj, e):
callbacks = ['onbefore' + e.event, 'on_before_' + e.event]
return self._do_callbacks(obj, callbacks, e)
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727,803 | fysom | _build_event | null | def _build_event(self, event):
def fn(obj, *args, **kwargs):
if not self.can(obj, event):
raise FysomError(
'event %s inappropriate in current state %s'
% (event, self.current(obj)))
# Prepare the event object with all the meta data to pas through.
# On event occurrence, source will always be the current state.
e = self._e_obj()
e.fsm, e.obj, e.event, e.src, e.dst = (
self, obj, event, self.current(obj), self._map[event]['dst'])
setattr(e, 'args', args)
setattr(e, 'kwargs', kwargs)
for k, v in kwargs.items():
setattr(e, k, v)
# check conditions first, event dst may change during
# checking conditions
for c in self._map[event].get('cond', ()):
target = True in c
cond = c[target]
_c_r = self._check_condition(obj, cond, target, e)
if not _c_r:
if 'else' in c:
e.dst = c['else']
break
else:
raise Canceled(
'Cannot trigger event {0} because the {1} '
'condition not returns {2}'.format(
event, cond, target), e
)
# try to trigger the before event, unless it gets cancelled.
if self._before_event(obj, e) is False:
raise Canceled(
'Cannot trigger event {0} because the onbefore{0} '
'handler returns False'.format(event), e)
# wraps the activities that must constitute a single transaction
if self.current(obj) != e.dst:
def _trans():
delattr(obj, 'transition')
setattr(obj, self.state_field, e.dst)
self._enter_state(obj, e)
self._change_state(obj, e)
self._after_event(obj, e)
obj.transition = _trans
# Hook to perform asynchronous transition
if self._leave_state(obj, e) is not False:
obj.transition()
else:
self._reenter_state(obj, e)
self._after_event(obj, e)
fn.__name__ = str(event)
fn.__doc__ = (
"Event handler for an {event} event. This event can be "
"fired if the machine is in {states} states.".format(
event=event, states=self._map[event]['src']))
return fn
| (self, event) | [
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727,804 | fysom | _change_state | null | def _change_state(self, obj, e):
callbacks = ['onchangestate', 'on_change_state']
return self._do_callbacks(obj, callbacks, e)
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727,805 | fysom | _check_condition | null | def _check_condition(self, obj, func, target, e):
if callable(func):
return func(e) is target
return self._do_callbacks(obj, [func], e) is target
| (self, obj, func, target, e) | [
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727,806 | fysom | _do_callbacks | null | def _do_callbacks(self, obj, callbacks, *args, **kwargs):
for cb in callbacks:
if cb in self._callbacks:
return self._callbacks[cb](*args, **kwargs)
if hasattr(obj, cb):
return getattr(obj, cb)(*args, **kwargs)
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727,807 | fysom | _enter_state | null | def _enter_state(self, obj, e):
callbacks = ['onenter' + e.dst, 'on' + e.dst,
'on_enter_' + e.dst, 'on_' + e.dst]
return self._do_callbacks(obj, callbacks, e)
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] |
727,808 | fysom | _is_base_string | null | @staticmethod
def _is_base_string(object): # pragma: no cover
try:
return isinstance(object, basestring) # noqa
except NameError:
return isinstance(object, str) # noqa
| (object) | [
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727,809 | fysom | _leave_state | null | def _leave_state(self, obj, e):
callbacks = ['onleave' + e.src, 'on_leave_' + e.src]
return self._do_callbacks(obj, callbacks, e)
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727,810 | fysom | _reenter_state | null | def _reenter_state(self, obj, e):
callbacks = ['onreenter' + e.dst, 'on_reenter_' + e.dst]
return self._do_callbacks(obj, callbacks, e)
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727,811 | fysom | can | null | def can(self, obj, event):
if event not in self._map or hasattr(obj, 'transition'):
return False
src = self._map[event]['src']
return self.current(obj) in src or WILDCARD in src
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727,812 | fysom | cannot | null | def cannot(self, obj, event):
return not self.can(obj, event)
| (self, obj, event) | [
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727,813 | fysom | current | null | def current(self, obj):
return getattr(obj, self.state_field) or 'none'
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727,814 | fysom | is_finished | null | def is_finished(self, obj):
return self._final and (self.current(obj) == self._final)
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727,815 | fysom | isstate | null | def isstate(self, obj, state):
return self.current(obj) == state
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727,817 | fysom | trigger | null | def trigger(self, obj, event, *args, **kwargs):
if not hasattr(self, event):
raise FysomError(
"There isn't any event registered as %s" % event)
return getattr(self, event)(obj, *args, **kwargs)
| (self, obj, event, *args, **kwargs) | [
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727,818 | fysom | FysomGlobalMixin | null | class FysomGlobalMixin(object):
GSM = None # global state machine instance, override this
def __init__(self, *args, **kwargs):
super(FysomGlobalMixin, self).__init__(*args, **kwargs)
if self.is_state('none'):
_initial = self.GSM._initial
if _initial and not _initial.get('defer'):
self.trigger(_initial['event'])
def __getattribute__(self, attr):
'''
Proxy public event methods to global machine if available.
'''
try:
return super(FysomGlobalMixin, self).__getattribute__(attr)
except AttributeError as err:
if not attr.startswith('_'):
gsm_attr = getattr(self.GSM, attr)
if callable(gsm_attr):
return functools.partial(gsm_attr, self)
raise # pragma: no cover
@property
def current(self):
'''
Simulate the behavior of Fysom's "current" attribute.
'''
return self.GSM.current(self)
@current.setter
def current(self, state):
setattr(self, self.GSM.state_field, state)
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] |
727,819 | fysom | __getattribute__ |
Proxy public event methods to global machine if available.
| def __getattribute__(self, attr):
'''
Proxy public event methods to global machine if available.
'''
try:
return super(FysomGlobalMixin, self).__getattribute__(attr)
except AttributeError as err:
if not attr.startswith('_'):
gsm_attr = getattr(self.GSM, attr)
if callable(gsm_attr):
return functools.partial(gsm_attr, self)
raise # pragma: no cover
| (self, attr) | [
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727,820 | fysom | __init__ | null | def __init__(self, *args, **kwargs):
super(FysomGlobalMixin, self).__init__(*args, **kwargs)
if self.is_state('none'):
_initial = self.GSM._initial
if _initial and not _initial.get('defer'):
self.trigger(_initial['event'])
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] |
727,831 | fysom | _weak_callback |
Store a weak reference to a callback or method.
| def _weak_callback(func):
'''
Store a weak reference to a callback or method.
'''
if isinstance(func, types.MethodType):
# Don't hold a reference to the object, otherwise we might create
# a cycle.
# Reference: http://stackoverflow.com/a/6975682
# Tell coveralls to not cover this if block, as the Python 2.x case
# doesn't test the 3.x code and vice versa.
if sys.version_info[0] < 3: # pragma: no cover
# Python 2.x case
obj_ref = weakref.ref(func.im_self)
func_ref = weakref.ref(func.im_func)
else: # pragma: no cover
# Python 3.x case
obj_ref = weakref.ref(func.__self__)
func_ref = weakref.ref(func.__func__)
func = None
def _callback(*args, **kwargs):
obj = obj_ref()
func = func_ref()
if (obj is None) or (func is None):
return
return func(obj, *args, **kwargs)
return _callback
else:
# We should be safe enough holding callback functions ourselves.
return func
| (func) | [
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0.00023323719506151974,
0.004091152921319008,
0.04537125676870346
] |
727,836 | nibe_mqtt.config | Config | null | class Config:
def __init__(self):
self._data = None
def load(self, config_file: Path) -> dict:
assert config_file.is_file(), f"{config_file} should be a file"
with config_file.open("r", encoding="utf-8") as fh:
self._data = schema(yaml.safe_load(fh))
return self._data
def get(self):
assert self._data is not None, "Not yet loaded"
return self._data
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727,837 | nibe_mqtt.config | __init__ | null | def __init__(self):
self._data = None
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] |
727,838 | nibe_mqtt.config | get | null | def get(self):
assert self._data is not None, "Not yet loaded"
return self._data
| (self) | [
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727,839 | nibe_mqtt.config | load | null | def load(self, config_file: Path) -> dict:
assert config_file.is_file(), f"{config_file} should be a file"
with config_file.open("r", encoding="utf-8") as fh:
self._data = schema(yaml.safe_load(fh))
return self._data
| (self, config_file: pathlib.Path) -> dict | [
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727,841 | captionizer.captionizer | caption_from_path | null | def caption_from_path(file_path, base_path, class_token=None, token=None):
# Prefer OrderedDict - key order in regular dict is only guaranteed
# from Python 3.7 onward.
tokens = OrderedDict([('S', token), ('C', class_token)])
return generic_captions_from_path(file_path, base_path, tokens)
| (file_path, base_path, class_token=None, token=None) | [
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727,843 | captionizer.finder | find_images | null | def find_images(root_folder, glob_pattern="**/*.*"):
return list(glob.glob(f'{root_folder}{os.path.sep}{glob_pattern}', recursive=True))
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727,845 | captionizer.captionizer | generic_captions_from_path | null | def generic_captions_from_path(file_path, base_path, tokens):
rel_path = os.path.relpath(file_path, base_path)
parent_path = os.path.dirname(rel_path)
caption = 'broken caption'
if parent_path == '':
caption = token_caption(tokens, rel_path)
else:
caption = path_caption(rel_path, tokens)
return caption
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727,846 | typeapi.typehint | AnnotatedTypeHint | Represents the `Annotated` type hint. | class AnnotatedTypeHint(TypeHint):
"""Represents the `Annotated` type hint."""
@property
def args(self) -> Tuple[Any, ...]:
return (self._args[0],)
def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
assert len(args) == 1
new_hint = Annotated[args + (self._args[1:])] # type: ignore
return AnnotatedTypeHint(new_hint)
def __len__(self) -> int:
return 1
@property
def type(self) -> Any:
"""
Returns the wrapped type of the annotation. It's common to wrap the result in a `TypeHint` to recursively
introspect the wrapped type.
>>> TypeHint(Annotated[int, "foobar"]).type
<class 'int'>
"""
return self._args[0]
@property
def metadata(self) -> Tuple[Any, ...]:
"""
Returns the metadata, i.e. all the parameters after the wrapped type.
>>> TypeHint(Annotated[int, "foobar"]).metadata
('foobar',)
"""
return self._args[1:]
| (hint: object, source: 'Any | None' = None) -> 'TypeHint' | [
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727,847 | typeapi.typehint | __eq__ | null | def __eq__(self, other: object) -> bool:
if type(self) != type(other):
return False
assert isinstance(other, TypeHint)
return (self.hint, self.origin, self.args, self.parameters) == (
other.hint,
other.origin,
other.args,
other.parameters,
)
| (self, other: object) -> bool | [
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727,848 | typeapi.typehint | __getitem__ | null | def __getitem__(self, index: "int | slice") -> "TypeHint | List[TypeHint]":
if isinstance(index, int):
try:
return TypeHint(self.args[index])
except IndexError:
raise IndexError(f"TypeHint index {index} out of range [0..{len(self.args)}[")
else:
return [TypeHint(x) for x in self.args[index]]
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727,849 | typeapi.typehint | __init__ | null | def __init__(self, hint: object, source: "Any | None" = None) -> None:
self._hint = hint
self._origin = get_type_hint_origin_or_none(hint)
self._args = get_type_hint_args(hint)
self._parameters = get_type_hint_parameters(hint)
self._source = source
| (self, hint: object, source: Optional[Any] = None) -> NoneType | [
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727,850 | typeapi.typehint | __iter__ | null | def __iter__(self) -> Iterator["TypeHint"]:
for i in range(len(self.args)):
yield self[i]
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727,852 | typeapi.typehint | __repr__ | null | def __repr__(self) -> str:
return f"TypeHint({type_repr(self._hint)})"
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] |
727,853 | typeapi.typehint | _copy_with_args | null | def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
assert len(args) == 1
new_hint = Annotated[args + (self._args[1:])] # type: ignore
return AnnotatedTypeHint(new_hint)
| (self, args: Tuple[Any, ...]) -> typeapi.typehint.TypeHint | [
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] |
727,854 | typeapi.typehint | evaluate |
Evaluate forward references in the type hint using the given *context*.
This method supports evaluating forward references that use PEP585 and PEP604 syntax even in older
versions of Python that do not support the PEPs.
:param context: An object that supports `__getitem__()` to retrieve a value by name. If this is
not specified, the globals of the `__module__` of the type hint's source :attr:`source` is
used instead. If no source exists, a :class:`RuntimeError` is raised.
| def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> "TypeHint":
"""
Evaluate forward references in the type hint using the given *context*.
This method supports evaluating forward references that use PEP585 and PEP604 syntax even in older
versions of Python that do not support the PEPs.
:param context: An object that supports `__getitem__()` to retrieve a value by name. If this is
not specified, the globals of the `__module__` of the type hint's source :attr:`source` is
used instead. If no source exists, a :class:`RuntimeError` is raised.
"""
if context is None:
context = self.get_context()
if self.origin is not None and self.args:
args = tuple(TypeHint(x).evaluate(context).hint for x in self.args)
return self._copy_with_args(args)
else:
return self
| (self, context: Optional[typeapi.utils.HasGetitem[str, Any]] = None) -> typeapi.typehint.TypeHint | [
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727,855 | typeapi.typehint | get_context | Return the context for this type hint in which forward references must be evaluated.
The context is derived from the `source` attribute, which can be either a `ModuleType`, `Mapping` or
`type`. In case of a `type`, the context is composed of the class scope (to resolve class-level members)
and the scope of the module that contains the type (looked up in `sys.modules`).
Raises RuntimeError: If `source` is `None` or has not one of the three supported types.
| def get_context(self) -> HasGetitem[str, Any]:
"""Return the context for this type hint in which forward references must be evaluated.
The context is derived from the `source` attribute, which can be either a `ModuleType`, `Mapping` or
`type`. In case of a `type`, the context is composed of the class scope (to resolve class-level members)
and the scope of the module that contains the type (looked up in `sys.modules`).
Raises RuntimeError: If `source` is `None` or has not one of the three supported types.
"""
if self.source is None:
raise RuntimeError(
f"Missing context for {self}.evaluate(), the type hint has no `.source` "
"to which we could fall back to. Specify the `context` argument or make sure that the type "
"hint's `.source` is set."
)
if isinstance(self.source, ModuleType):
return vars(self.source)
if isinstance(self.source, Mapping):
return self.source
if isinstance(self.source, type):
return ChainMap(
cast(MutableMapping[str, Any], vars(self.source)),
cast(MutableMapping[str, Any], vars(sys.modules[self.source.__module__])),
)
raise RuntimeError(f"Unable to determine TypeHint.source context from source={self.source!r}")
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] |
727,856 | typeapi.typehint | parameterize |
Replace references to the type variables in the keys of *parameter_map*
with the type hints of the associated values.
:param parameter_map: A dictionary that maps :class:`TypeVar` to other
type hints.
| def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
"""
Replace references to the type variables in the keys of *parameter_map*
with the type hints of the associated values.
:param parameter_map: A dictionary that maps :class:`TypeVar` to other
type hints.
"""
if self.origin is not None and self.args:
args = tuple(TypeHint(x).parameterize(parameter_map).hint for x in self.args)
return self._copy_with_args(args)
else:
return self
| (self, parameter_map: Mapping[object, Any]) -> typeapi.typehint.TypeHint | [
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] |
727,857 | typeapi.typehint | ClassTypeHint | Represents a real, possibly parameterized, type. For example `int`, `list`, `list[int]` or `list[T]`. | class ClassTypeHint(TypeHint):
"""Represents a real, possibly parameterized, type. For example `int`, `list`, `list[int]` or `list[T]`."""
def __init__(self, hint: object, source: "Any | None" = None) -> None:
super().__init__(hint, source)
assert isinstance(self.hint, type) or isinstance(self.origin, type), (
"ClassTypeHint must be initialized from a real type or a generic that points to a real type. "
f'Got "{self.hint!r}" with origin "{self.origin}"'
)
def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
if self.type is Generic: # type: ignore[comparison-overlap]
return self
return super().parameterize(parameter_map)
@property
def type(self) -> type:
"""Returns the concrepte type."""
if isinstance(self.origin, type):
return self.origin
if isinstance(self.hint, type):
return self.hint
assert False, "ClassTypeHint not initialized from a real type or a generic that points to a real type."
@property
def bases(self) -> "Tuple[Any, ...]":
"""
Return the bases of the classes' types. If the type is a generic, the bases of the generic's origin are
returned in their parameterized form (e.g. `Generic[T]` instead of `Generic` is returned).
"""
return get_type_hint_original_bases(self.type) or self.type.__bases__
def get_parameter_map(self) -> Dict[Any, Any]:
"""
Returns a dictionary that maps generic parameters to their values.
>>> TypeHint(List[int]).type
<class 'list'>
>>> TypeHint(List[int]).args
(<class 'int'>,)
# NOTE(@niklas): This is a bug for built-in types, but it's not that big of a deal because we don't
# usually need to recursively expand forward references in these types.
>>> TypeHint(List[int]).parameters
()
>>> TypeHint(List[int]).get_parameter_map()
{}
>>> T = TypeVar("T")
>>> class A(Generic[T]): pass
>>> TypeHint(A[int]).get_parameter_map()
{~T: <class 'int'>}
"""
if not self.args:
return {}
# We need to look at the parameters of the original, un-parameterized type. That's why we can't
# use self.parameters.
return dict(zip(TypeHint(self.type).parameters, self.args))
def recurse_bases(
self, order: Literal["dfs", "bfs"] = "bfs"
) -> Generator["ClassTypeHint", Union[Literal["skip"], None], None]:
"""
Iterate over all base classes of this type hint, and continues recursively. The iteration order is
determined by the *order* parameter, which can be either depth-first or breadh-first. If the generator
receives the string `"skip"` from the caller, it will skip the bases of the last yielded type.
"""
# Find the item type in the base classes of the collection type.
bases = deque([self])
while bases:
current = bases.popleft()
if not isinstance(current, ClassTypeHint):
raise RuntimeError(
f"Expected to find a ClassTypeHint in the base classes of {self!r}, found {current!r} instead."
)
response = yield current
if response == "skip":
continue
current_bases = cast(
List[ClassTypeHint],
[TypeHint(x, current.type).evaluate().parameterize(current.get_parameter_map()) for x in current.bases],
)
if order == "bfs":
bases.extend(current_bases)
elif order == "dfs":
bases.extendleft(reversed(current_bases))
else:
raise ValueError(f"Invalid order {order!r}")
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727,860 | typeapi.typehint | __init__ | null | def __init__(self, hint: object, source: "Any | None" = None) -> None:
super().__init__(hint, source)
assert isinstance(self.hint, type) or isinstance(self.origin, type), (
"ClassTypeHint must be initialized from a real type or a generic that points to a real type. "
f'Got "{self.hint!r}" with origin "{self.origin}"'
)
| (self, hint: object, source: Optional[Any] = None) -> NoneType | [
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727,862 | typeapi.typehint | __len__ | null | def __len__(self) -> int:
return len(self.args)
| (self) -> int | [
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727,864 | typeapi.typehint | _copy_with_args |
Internal. Create a copy of this type hint with updated type arguments.
| def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
"""
Internal. Create a copy of this type hint with updated type arguments.
"""
generic = get_subscriptable_type_hint_from_origin(self.origin)
try:
new_hint = generic[args]
except TypeError as exc:
raise TypeError(f"{type_repr(generic)}: {exc}")
return TypeHint(new_hint)
| (self, args: Tuple[Any, ...]) -> typeapi.typehint.TypeHint | [
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] |
727,867 | typeapi.typehint | get_parameter_map |
Returns a dictionary that maps generic parameters to their values.
>>> TypeHint(List[int]).type
<class 'list'>
>>> TypeHint(List[int]).args
(<class 'int'>,)
# NOTE(@niklas): This is a bug for built-in types, but it's not that big of a deal because we don't
# usually need to recursively expand forward references in these types.
>>> TypeHint(List[int]).parameters
()
>>> TypeHint(List[int]).get_parameter_map()
{}
>>> T = TypeVar("T")
>>> class A(Generic[T]): pass
>>> TypeHint(A[int]).get_parameter_map()
{~T: <class 'int'>}
| def get_parameter_map(self) -> Dict[Any, Any]:
"""
Returns a dictionary that maps generic parameters to their values.
>>> TypeHint(List[int]).type
<class 'list'>
>>> TypeHint(List[int]).args
(<class 'int'>,)
# NOTE(@niklas): This is a bug for built-in types, but it's not that big of a deal because we don't
# usually need to recursively expand forward references in these types.
>>> TypeHint(List[int]).parameters
()
>>> TypeHint(List[int]).get_parameter_map()
{}
>>> T = TypeVar("T")
>>> class A(Generic[T]): pass
>>> TypeHint(A[int]).get_parameter_map()
{~T: <class 'int'>}
"""
if not self.args:
return {}
# We need to look at the parameters of the original, un-parameterized type. That's why we can't
# use self.parameters.
return dict(zip(TypeHint(self.type).parameters, self.args))
| (self) -> Dict[Any, Any] | [
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727,868 | typeapi.typehint | parameterize | null | def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
if self.type is Generic: # type: ignore[comparison-overlap]
return self
return super().parameterize(parameter_map)
| (self, parameter_map: Mapping[object, Any]) -> typeapi.typehint.TypeHint | [
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] |
727,869 | typeapi.typehint | recurse_bases |
Iterate over all base classes of this type hint, and continues recursively. The iteration order is
determined by the *order* parameter, which can be either depth-first or breadh-first. If the generator
receives the string `"skip"` from the caller, it will skip the bases of the last yielded type.
| def recurse_bases(
self, order: Literal["dfs", "bfs"] = "bfs"
) -> Generator["ClassTypeHint", Union[Literal["skip"], None], None]:
"""
Iterate over all base classes of this type hint, and continues recursively. The iteration order is
determined by the *order* parameter, which can be either depth-first or breadh-first. If the generator
receives the string `"skip"` from the caller, it will skip the bases of the last yielded type.
"""
# Find the item type in the base classes of the collection type.
bases = deque([self])
while bases:
current = bases.popleft()
if not isinstance(current, ClassTypeHint):
raise RuntimeError(
f"Expected to find a ClassTypeHint in the base classes of {self!r}, found {current!r} instead."
)
response = yield current
if response == "skip":
continue
current_bases = cast(
List[ClassTypeHint],
[TypeHint(x, current.type).evaluate().parameterize(current.get_parameter_map()) for x in current.bases],
)
if order == "bfs":
bases.extend(current_bases)
elif order == "dfs":
bases.extendleft(reversed(current_bases))
else:
raise ValueError(f"Invalid order {order!r}")
| (self, order: Literal['dfs', 'bfs'] = 'bfs') -> Generator[typeapi.typehint.ClassTypeHint, Optional[Literal['skip']], NoneType] | [
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727,870 | typeapi.typehint | ForwardRefTypeHint | Represents a forward reference, i.e. a string in the type annotation or an explicit `ForwardRef`. | class ForwardRefTypeHint(TypeHint):
"""Represents a forward reference, i.e. a string in the type annotation or an explicit `ForwardRef`."""
def __init__(self, hint: object, source: "Any | None") -> None:
super().__init__(hint, source)
if isinstance(self._hint, str):
self._forward_ref = ForwardRef(self._hint)
elif isinstance(self._hint, ForwardRef):
self._forward_ref = self._hint
else:
raise TypeError(
f"ForwardRefTypeHint must be initialized from a typing.ForwardRef or str. Got: {type(self._hint)!r}"
)
def parameterize(self, parameter_map: Mapping[object, Any]) -> TypeHint:
raise RuntimeError(
"ForwardRef cannot be parameterized. Ensure that your type hint is fully "
"evaluated before parameterization."
)
def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> TypeHint:
from .future.fake import FakeProvider
if context is None:
context = self.get_context()
hint = FakeProvider(context).execute(self.expr).evaluate()
return TypeHint(hint).evaluate(context)
@property
def hint(self) -> "ForwardRef | str":
"""Returns the original type hint."""
return self._hint # type: ignore
@property
def ref(self) -> ForwardRef:
"""Same as `hint`, but returns it as a `ForwardRef` always."""
return self._forward_ref
@property
def expr(self) -> str:
"""
Returns the expression of the forward reference.
>>> TypeHint(ForwardRef("Foobar")).expr
'Foobar'
>>> TypeHint(TypeHint(List["Foobar"]).args[0]).expr
'Foobar'
"""
return self._forward_ref.__forward_arg__
| (hint: object, source: 'Any | None' = None) -> 'TypeHint' | [
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727,873 | typeapi.typehint | __init__ | null | def __init__(self, hint: object, source: "Any | None") -> None:
super().__init__(hint, source)
if isinstance(self._hint, str):
self._forward_ref = ForwardRef(self._hint)
elif isinstance(self._hint, ForwardRef):
self._forward_ref = self._hint
else:
raise TypeError(
f"ForwardRefTypeHint must be initialized from a typing.ForwardRef or str. Got: {type(self._hint)!r}"
)
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727,878 | typeapi.typehint | evaluate | null | def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> TypeHint:
from .future.fake import FakeProvider
if context is None:
context = self.get_context()
hint = FakeProvider(context).execute(self.expr).evaluate()
return TypeHint(hint).evaluate(context)
| (self, context: Optional[typeapi.utils.HasGetitem[str, Any]] = None) -> typeapi.typehint.TypeHint | [
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727,880 | typeapi.typehint | parameterize | null | def parameterize(self, parameter_map: Mapping[object, Any]) -> TypeHint:
raise RuntimeError(
"ForwardRef cannot be parameterized. Ensure that your type hint is fully "
"evaluated before parameterization."
)
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727,881 | typeapi.typehint | LiteralTypeHint | Represents a literal type hint, e.g. `Literal["a", 42]`. | class LiteralTypeHint(TypeHint):
"""Represents a literal type hint, e.g. `Literal["a", 42]`."""
@property
def args(self) -> Tuple[Any, ...]:
return ()
def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
return self
def __len__(self) -> int:
return 0
@property
def values(self) -> Tuple[Any, ...]:
"""
Returns the values of the literal.
>>> TypeHint(Literal["a", 42]).values
('a', 42)
"""
return self._args
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727,891 | typeapi.typehint | parameterize | null | def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
return self
| (self, parameter_map: Mapping[object, Any]) -> typeapi.typehint.TypeHint | [
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727,892 | typeapi.typehint | TupleTypeHint |
A special class to represent a type hint for a parameterized tuple. This class does not represent a plain tuple
type without parameterization.
| class TupleTypeHint(ClassTypeHint):
"""
A special class to represent a type hint for a parameterized tuple. This class does not represent a plain tuple
type without parameterization.
"""
def __init__(self, hint: object, source: "Any | None") -> None:
super().__init__(hint, source)
if self._args == ((),):
self._args = ()
elif self._args == () and self._hint == tuple:
raise ValueError("TupleTypeHint can only represent a parameterized tuple.")
if ... in self._args:
assert self._args[-1] == ..., "Tuple Ellipsis not as last arg"
assert len(self._args) == 2, "Tuple with Ellipsis has more than two args"
self._repeated = True
self._args = self._args[:-1]
else:
self._repeated = False
def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
if self._repeated:
args = args + (...,)
return super()._copy_with_args(args)
@property
def type(self) -> type:
return tuple
@property
def repeated(self) -> bool:
"""
Returns `True` if the Tuple is of arbitrary length, but only of one type.
"""
return self._repeated
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727,895 | typeapi.typehint | __init__ | null | def __init__(self, hint: object, source: "Any | None") -> None:
super().__init__(hint, source)
if self._args == ((),):
self._args = ()
elif self._args == () and self._hint == tuple:
raise ValueError("TupleTypeHint can only represent a parameterized tuple.")
if ... in self._args:
assert self._args[-1] == ..., "Tuple Ellipsis not as last arg"
assert len(self._args) == 2, "Tuple with Ellipsis has more than two args"
self._repeated = True
self._args = self._args[:-1]
else:
self._repeated = False
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727,899 | typeapi.typehint | _copy_with_args | null | def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
if self._repeated:
args = args + (...,)
return super()._copy_with_args(args)
| (self, args: Tuple[Any, ...]) -> typeapi.typehint.TypeHint | [
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727,905 | typeapi.typehint | TypeHint |
Base class that provides an object-oriented interface to a Python type hint.
| class TypeHint(object, metaclass=_TypeHintMeta):
"""
Base class that provides an object-oriented interface to a Python type hint.
"""
def __init__(self, hint: object, source: "Any | None" = None) -> None:
self._hint = hint
self._origin = get_type_hint_origin_or_none(hint)
self._args = get_type_hint_args(hint)
self._parameters = get_type_hint_parameters(hint)
self._source = source
def __repr__(self) -> str:
return f"TypeHint({type_repr(self._hint)})"
@property
def hint(self) -> object:
"""
The original type hint.
"""
return self._hint
@property
def origin(self) -> "object | None":
"""
The original type behind a type hint (e.g. the `Generic.__origin__`). For example, for :class:`typing.List`,
it is `list`. For :class:`typing.Sequence`, it is :class:`collections.abc.Sequence`.
"""
return self._origin
@property
def args(self) -> Tuple[Any, ...]:
"""
Type hint arguments are the values passed into type hint subscripts, e.g. in `Union[int, str]`, the
arguments are `(int, str)`. We only return arguments that are expected to be types or other type hints.
For example, `Literal["foo", 0]` has an empty tuple for its `args`, and instead the values can be
retrievd using :attr:`LiteralTypeHint.valuse`.
"""
return self._args
@property
def parameters(self) -> Tuple[Any, ...]:
"""
The parameters of a type hint is basically :attr:`args` but filtered for #typing.TypeVar objects.
"""
return self._parameters
@property
def source(self) -> "Any | None":
"""
The object from which on which the type hint was found, for example a class or a function.
"""
return self._source
def __eq__(self, other: object) -> bool:
if type(self) != type(other):
return False
assert isinstance(other, TypeHint)
return (self.hint, self.origin, self.args, self.parameters) == (
other.hint,
other.origin,
other.args,
other.parameters,
)
def __iter__(self) -> Iterator["TypeHint"]:
for i in range(len(self.args)):
yield self[i]
def __len__(self) -> int:
return len(self.args)
@overload
def __getitem__(self, __index: int) -> "TypeHint": ...
@overload
def __getitem__(self, __slice: slice) -> List["TypeHint"]: ...
def __getitem__(self, index: "int | slice") -> "TypeHint | List[TypeHint]":
if isinstance(index, int):
try:
return TypeHint(self.args[index])
except IndexError:
raise IndexError(f"TypeHint index {index} out of range [0..{len(self.args)}[")
else:
return [TypeHint(x) for x in self.args[index]]
def _copy_with_args(self, args: "Tuple[Any, ...]") -> "TypeHint":
"""
Internal. Create a copy of this type hint with updated type arguments.
"""
generic = get_subscriptable_type_hint_from_origin(self.origin)
try:
new_hint = generic[args]
except TypeError as exc:
raise TypeError(f"{type_repr(generic)}: {exc}")
return TypeHint(new_hint)
def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
"""
Replace references to the type variables in the keys of *parameter_map*
with the type hints of the associated values.
:param parameter_map: A dictionary that maps :class:`TypeVar` to other
type hints.
"""
if self.origin is not None and self.args:
args = tuple(TypeHint(x).parameterize(parameter_map).hint for x in self.args)
return self._copy_with_args(args)
else:
return self
def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> "TypeHint":
"""
Evaluate forward references in the type hint using the given *context*.
This method supports evaluating forward references that use PEP585 and PEP604 syntax even in older
versions of Python that do not support the PEPs.
:param context: An object that supports `__getitem__()` to retrieve a value by name. If this is
not specified, the globals of the `__module__` of the type hint's source :attr:`source` is
used instead. If no source exists, a :class:`RuntimeError` is raised.
"""
if context is None:
context = self.get_context()
if self.origin is not None and self.args:
args = tuple(TypeHint(x).evaluate(context).hint for x in self.args)
return self._copy_with_args(args)
else:
return self
def get_context(self) -> HasGetitem[str, Any]:
"""Return the context for this type hint in which forward references must be evaluated.
The context is derived from the `source` attribute, which can be either a `ModuleType`, `Mapping` or
`type`. In case of a `type`, the context is composed of the class scope (to resolve class-level members)
and the scope of the module that contains the type (looked up in `sys.modules`).
Raises RuntimeError: If `source` is `None` or has not one of the three supported types.
"""
if self.source is None:
raise RuntimeError(
f"Missing context for {self}.evaluate(), the type hint has no `.source` "
"to which we could fall back to. Specify the `context` argument or make sure that the type "
"hint's `.source` is set."
)
if isinstance(self.source, ModuleType):
return vars(self.source)
if isinstance(self.source, Mapping):
return self.source
if isinstance(self.source, type):
return ChainMap(
cast(MutableMapping[str, Any], vars(self.source)),
cast(MutableMapping[str, Any], vars(sys.modules[self.source.__module__])),
)
raise RuntimeError(f"Unable to determine TypeHint.source context from source={self.source!r}")
| (hint: object, source: 'Any | None' = None) -> 'TypeHint' | [
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727,916 | typeapi.typehint | TypeVarTypeHint | Represents a `TypeVar` type hint. | class TypeVarTypeHint(TypeHint):
"""Represents a `TypeVar` type hint."""
@property
def hint(self) -> TypeVar:
assert isinstance(self._hint, TypeVar)
return self._hint
def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
return TypeHint(parameter_map.get(self.hint, self.hint))
def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> TypeHint:
return self
@property
def name(self) -> str:
"""
Returns the name of the type variable.
>>> TypeHint(TypeVar("T")).name
'T'
"""
return self.hint.__name__
@property
def covariant(self) -> bool:
"""
Returns whether the TypeVar is covariant.
>>> TypeHint(TypeVar("T")).covariant
False
>>> TypeHint(TypeVar("T", covariant=True)).covariant
True
"""
return self.hint.__covariant__
@property
def contravariant(self) -> bool:
"""
Returns whether the TypeVar is contravariant.
>>> TypeHint(TypeVar("T")).contravariant
False
>>> TypeHint(TypeVar("T", contravariant=True)).contravariant
True
"""
return self.hint.__contravariant__
@property
def constraints(self) -> "Tuple[Any, ...]":
"""
Returns the constraints of the TypeVar.
>>> TypeHint(TypeVar("T", int, str)).constraints
(<class 'int'>, <class 'str'>)
"""
return self.hint.__constraints__
@property
def bound(self) -> Any:
"""
Returns what the TypeVar is bound to.
>>> TypeHint(TypeVar("T", bound=str)).bound
<class 'str'>
"""
return self.hint.__bound__
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727,924 | typeapi.typehint | evaluate | null | def evaluate(self, context: "HasGetitem[str, Any] | None" = None) -> TypeHint:
return self
| (self, context: Optional[typeapi.utils.HasGetitem[str, Any]] = None) -> typeapi.typehint.TypeHint | [
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727,926 | typeapi.typehint | parameterize | null | def parameterize(self, parameter_map: Mapping[object, Any]) -> "TypeHint":
return TypeHint(parameter_map.get(self.hint, self.hint))
| (self, parameter_map: Mapping[object, Any]) -> typeapi.typehint.TypeHint | [
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727,927 | typeapi.utils | TypedDictProtocol | A protocol that describes #typing.TypedDict values (which are actually instances of the #typing._TypedDictMeta
metaclass). Use #is_typed_dict() to check if a hint is matches this protocol. | class TypedDictProtocol(Protocol):
"""A protocol that describes #typing.TypedDict values (which are actually instances of the #typing._TypedDictMeta
metaclass). Use #is_typed_dict() to check if a hint is matches this protocol."""
__annotations__: Dict[str, Any]
__required_keys__: Set[str]
__optional_keys__: Set[str]
__total__: bool
| (*args, **kwargs) | [
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727,929 | typeapi.typehint | UnionTypeHint | Represents a union of types, e.g. `typing.Union[A, B]` or `A | B`. | class UnionTypeHint(TypeHint):
"""Represents a union of types, e.g. `typing.Union[A, B]` or `A | B`."""
def has_none_type(self) -> bool:
return NoneType in self._args
def without_none_type(self) -> TypeHint:
args = tuple(x for x in self._args if x is not NoneType)
if len(args) == 1:
return TypeHint(args[0])
else:
return self._copy_with_args(args)
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727,939 | typeapi.typehint | has_none_type | null | def has_none_type(self) -> bool:
return NoneType in self._args
| (self) -> bool | [
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727,941 | typeapi.typehint | without_none_type | null | def without_none_type(self) -> TypeHint:
args = tuple(x for x in self._args if x is not NoneType)
if len(args) == 1:
return TypeHint(args[0])
else:
return self._copy_with_args(args)
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727,943 | typeapi.utils | get_annotations | Like #typing.get_type_hints(), but always includes extras. This is important when we want to inspect
#typing.Annotated hints (without extras the annotations are removed). In Python 3.10 and onwards, this is
an alias for #inspect.get_annotations() with `eval_str=True`.
If *include_bases* is set to `True`, annotations from base classes are taken into account as well.
This function will take into account the locals and globals accessible through the frame associated with
a function or type by the #scoped() decorator. | def get_annotations(
obj: Union[Callable[..., Any], ModuleType, type],
include_bases: bool = False,
globalns: Optional[Dict[str, Any]] = None,
localns: Optional[Dict[str, Any]] = None,
eval_str: bool = True,
) -> Dict[str, Any]:
"""Like #typing.get_type_hints(), but always includes extras. This is important when we want to inspect
#typing.Annotated hints (without extras the annotations are removed). In Python 3.10 and onwards, this is
an alias for #inspect.get_annotations() with `eval_str=True`.
If *include_bases* is set to `True`, annotations from base classes are taken into account as well.
This function will take into account the locals and globals accessible through the frame associated with
a function or type by the #scoped() decorator."""
if hasattr(obj, "__typeapi_frame__"):
frame: FrameType = obj.__typeapi_frame__ # type: ignore[union-attr]
globalns = frame.f_globals
localns = frame.f_locals
del frame
elif hasattr(obj, "__module__"):
module = sys.modules.get(obj.__module__)
if module is None:
warnings.warn(
f"sys.modules[{obj.__module__!r}] does not exist, type hint resolution context for object of type "
f"{type(obj).__name__!r} will not be available.",
UserWarning,
)
else:
assert hasattr(module, "__dict__"), module
globalns = vars(module)
from collections import ChainMap
from .typehint import TypeHint
def eval_callback(hint_expr: str, globals: Any, locals: Any) -> Any:
chainmap = ChainMap(locals or {}, globals or {})
if isinstance(obj, type):
chainmap = chainmap.new_child(cast(MutableMapping[str, Any], vars(obj)))
hint = TypeHint(hint_expr, chainmap)
return hint.evaluate().hint
annotations = _inspect_get_annotations(obj, globals=globalns, locals=localns, eval_str=eval_str, eval=eval_callback)
if isinstance(obj, type) and include_bases:
annotations = {}
for base in obj.__mro__:
base_annotations = _inspect_get_annotations(
base, globals=globalns, locals=localns, eval_str=eval_str, eval=eval_callback
)
annotations.update({k: v for k, v in base_annotations.items() if k not in annotations})
return annotations
| (obj: Union[Callable[..., Any], module, type], include_bases: bool = False, globalns: Optional[Dict[str, Any]] = None, localns: Optional[Dict[str, Any]] = None, eval_str: bool = True) -> Dict[str, Any] | [
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727,944 | typeapi.utils | is_typed_dict |
Returns:
`True` if *hint* is a #typing.TypedDict.
!!! note
Typed dictionaries are actually just type objects. This means #typeapi.of() will represent them as
#typeapi.models.Type.
| def is_typed_dict(hint: Any) -> TypeGuard[TypedDictProtocol]:
"""
Returns:
`True` if *hint* is a #typing.TypedDict.
!!! note
Typed dictionaries are actually just type objects. This means #typeapi.of() will represent them as
#typeapi.models.Type.
"""
import typing
import typing_extensions
for m in (typing, typing_extensions):
if hasattr(m, "_TypedDictMeta") and isinstance(hint, m._TypedDictMeta): # type: ignore[attr-defined]
return True
return False
| (hint: Any) -> TypeGuard[typeapi.utils.TypedDictProtocol] | [
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] |
727,945 | typeapi.utils | type_repr | #typing._type_repr() stolen from Python 3.8. | def type_repr(obj: Any) -> str:
"""#typing._type_repr() stolen from Python 3.8."""
if (getattr(obj, "__module__", None) or getattr(type(obj), "__module__", None)) in TYPING_MODULE_NAMES or hasattr(
obj, "__args__"
):
# NOTE(NiklasRosenstein): In Python 3.6, List[int] is actually a "type" subclass so we can't
# rely on the fall through on the below.
return repr(obj)
if isinstance(obj, type):
if obj.__module__ == "builtins":
return obj.__qualname__
return f"{obj.__module__}.{obj.__qualname__}"
if obj is ...:
return "..."
if isinstance(obj, FunctionType):
return obj.__name__
return repr(obj)
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] |
727,948 | builtins | dict | dict() -> new empty dictionary
dict(mapping) -> new dictionary initialized from a mapping object's
(key, value) pairs
dict(iterable) -> new dictionary initialized as if via:
d = {}
for k, v in iterable:
d[k] = v
dict(**kwargs) -> new dictionary initialized with the name=value pairs
in the keyword argument list. For example: dict(one=1, two=2) | dict[str, str]
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727,949 | mod_wsgi_van.router | Router | Router(base_path: str = '/var/www', venv_name: str = '.venv', wsgi_dir: str = 'wsgi', module_name: str = 'app', object_name: str = 'app', update_interval: float = 1.0) | class Router:
base_path: str = "/var/www"
venv_name: str = ".venv"
wsgi_dir: str = "wsgi"
module_name: str = "app"
object_name: str = "app"
update_interval: float = 1.0
def __post_init__(self) -> None:
self.servers: dict[str, Server] = {}
self.stop_watcher = threading.Event()
self.watcher = threading.Thread(
target=self.poll_server_paths,
daemon=True,
)
self.watcher.start()
atexit.register(self.shutdown)
def shutdown(self):
self.stop_watcher.set()
self.watcher.join()
def get_version(self, path: pathlib.Path) -> typing.Any:
# Monitor the vhost's WSGI directory
wsgi_path = path / self.wsgi_dir
# Follow symlink changes
hard_path = wsgi_path.resolve(strict=True)
# Allow touching to reload like mod_wsgi
return os.stat(hard_path).st_mtime
def poll_server_paths(self):
# Update servers when their path changes
while not self.stop_watcher.wait(self.update_interval):
for server in list(self.servers.values()):
try:
# Reload modules after a deploy
server.update(self.get_version(server.path))
except Exception as e:
# Purge deleted servers
server.log(e)
server.log("Closing")
del self.servers[server.host_name]
def get_server_path(self, host_name: str) -> pathlib.Path:
return pathlib.Path(self.base_path, host_name)
def get_venv_paths(self, path: pathlib.Path) -> list[pathlib.Path]:
venv_path = path / self.venv_name
return list(venv_path.glob("lib/python*/site-packages"))
def get_server(self, environ: Environ) -> Server:
host_name = environ["HTTP_HOST"]
# Lazy load and cache WSGI servers on request
if host_name not in self.servers:
path = self.get_server_path(host_name)
server = Server(
host_name=host_name,
script_name=environ["mod_wsgi.script_name"],
path=path,
venv_paths=self.get_venv_paths(path),
wsgi_dir=self.wsgi_dir,
module_name=self.module_name,
object_name=self.object_name,
version=self.get_version(path),
)
server.load()
self.servers[host_name] = server
return self.servers[host_name]
def application(self, environ: Environ, start_response: StartResponse) -> Response:
start_time = time.perf_counter()
server = self.get_server(environ)
with server.time("serve", start_time):
# Drain the generator to time the response
yield from server.serve(environ, start_response)
| (base_path: str = '/var/www', venv_name: str = '.venv', wsgi_dir: str = 'wsgi', module_name: str = 'app', object_name: str = 'app', update_interval: float = 1.0) -> None | [
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727,950 | mod_wsgi_van.router | __eq__ | null | import atexit
import dataclasses
import os
import pathlib
import threading
import time
import typing
from .server import Server, Environ, StartResponse, Response
@dataclasses.dataclass
class Router:
base_path: str = "/var/www"
venv_name: str = ".venv"
wsgi_dir: str = "wsgi"
module_name: str = "app"
object_name: str = "app"
update_interval: float = 1.0
def __post_init__(self) -> None:
self.servers: dict[str, Server] = {}
self.stop_watcher = threading.Event()
self.watcher = threading.Thread(
target=self.poll_server_paths,
daemon=True,
)
self.watcher.start()
atexit.register(self.shutdown)
def shutdown(self):
self.stop_watcher.set()
self.watcher.join()
def get_version(self, path: pathlib.Path) -> typing.Any:
# Monitor the vhost's WSGI directory
wsgi_path = path / self.wsgi_dir
# Follow symlink changes
hard_path = wsgi_path.resolve(strict=True)
# Allow touching to reload like mod_wsgi
return os.stat(hard_path).st_mtime
def poll_server_paths(self):
# Update servers when their path changes
while not self.stop_watcher.wait(self.update_interval):
for server in list(self.servers.values()):
try:
# Reload modules after a deploy
server.update(self.get_version(server.path))
except Exception as e:
# Purge deleted servers
server.log(e)
server.log("Closing")
del self.servers[server.host_name]
def get_server_path(self, host_name: str) -> pathlib.Path:
return pathlib.Path(self.base_path, host_name)
def get_venv_paths(self, path: pathlib.Path) -> list[pathlib.Path]:
venv_path = path / self.venv_name
return list(venv_path.glob("lib/python*/site-packages"))
def get_server(self, environ: Environ) -> Server:
host_name = environ["HTTP_HOST"]
# Lazy load and cache WSGI servers on request
if host_name not in self.servers:
path = self.get_server_path(host_name)
server = Server(
host_name=host_name,
script_name=environ["mod_wsgi.script_name"],
path=path,
venv_paths=self.get_venv_paths(path),
wsgi_dir=self.wsgi_dir,
module_name=self.module_name,
object_name=self.object_name,
version=self.get_version(path),
)
server.load()
self.servers[host_name] = server
return self.servers[host_name]
def application(self, environ: Environ, start_response: StartResponse) -> Response:
start_time = time.perf_counter()
server = self.get_server(environ)
with server.time("serve", start_time):
# Drain the generator to time the response
yield from server.serve(environ, start_response)
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] |
727,952 | mod_wsgi_van.router | __post_init__ | null | def __post_init__(self) -> None:
self.servers: dict[str, Server] = {}
self.stop_watcher = threading.Event()
self.watcher = threading.Thread(
target=self.poll_server_paths,
daemon=True,
)
self.watcher.start()
atexit.register(self.shutdown)
| (self) -> NoneType | [
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-0.009489006362855434
] |
727,954 | mod_wsgi_van.router | application | null | def application(self, environ: Environ, start_response: StartResponse) -> Response:
start_time = time.perf_counter()
server = self.get_server(environ)
with server.time("serve", start_time):
# Drain the generator to time the response
yield from server.serve(environ, start_response)
| (self, environ: dict[str, str], start_response: Callable) -> Generator | [
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727,955 | mod_wsgi_van.router | get_server | null | def get_server(self, environ: Environ) -> Server:
host_name = environ["HTTP_HOST"]
# Lazy load and cache WSGI servers on request
if host_name not in self.servers:
path = self.get_server_path(host_name)
server = Server(
host_name=host_name,
script_name=environ["mod_wsgi.script_name"],
path=path,
venv_paths=self.get_venv_paths(path),
wsgi_dir=self.wsgi_dir,
module_name=self.module_name,
object_name=self.object_name,
version=self.get_version(path),
)
server.load()
self.servers[host_name] = server
return self.servers[host_name]
| (self, environ: dict[str, str]) -> mod_wsgi_van.server.Server | [
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727,956 | mod_wsgi_van.router | get_server_path | null | def get_server_path(self, host_name: str) -> pathlib.Path:
return pathlib.Path(self.base_path, host_name)
| (self, host_name: str) -> pathlib.Path | [
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727,957 | mod_wsgi_van.router | get_venv_paths | null | def get_venv_paths(self, path: pathlib.Path) -> list[pathlib.Path]:
venv_path = path / self.venv_name
return list(venv_path.glob("lib/python*/site-packages"))
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727,958 | mod_wsgi_van.router | get_version | null | def get_version(self, path: pathlib.Path) -> typing.Any:
# Monitor the vhost's WSGI directory
wsgi_path = path / self.wsgi_dir
# Follow symlink changes
hard_path = wsgi_path.resolve(strict=True)
# Allow touching to reload like mod_wsgi
return os.stat(hard_path).st_mtime
| (self, path: pathlib.Path) -> Any | [
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727,959 | mod_wsgi_van.router | poll_server_paths | null | def poll_server_paths(self):
# Update servers when their path changes
while not self.stop_watcher.wait(self.update_interval):
for server in list(self.servers.values()):
try:
# Reload modules after a deploy
server.update(self.get_version(server.path))
except Exception as e:
# Purge deleted servers
server.log(e)
server.log("Closing")
del self.servers[server.host_name]
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727,960 | mod_wsgi_van.router | shutdown | null | def shutdown(self):
self.stop_watcher.set()
self.watcher.join()
| (self) | [
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727,961 | mod_wsgi_van.server | Server | Server(host_name: str, script_name: str, path: pathlib.Path, venv_paths: list[pathlib.Path], wsgi_dir: str, module_name: str, object_name: str, version: Any, import_cache: dict[str, module] = <factory>) | class Server:
host_name: str
script_name: str
path: pathlib.Path
venv_paths: list[pathlib.Path]
wsgi_dir: str
module_name: str
object_name: str
version: typing.Any
import_cache: dict[str, types.ModuleType] = dataclasses.field(default_factory=dict)
def load(self) -> None:
# Load one module at a time since sys is global
self.log("Loading")
with self.time("load"), self.environment():
self.module = importlib.import_module(self.module_name)
self.handler: Handler = getattr(self.module, self.object_name)
def update(self, version: typing.Any) -> None:
if self.version != version:
# Clear import cache and reload
self.import_cache = {}
self.load()
self.version = version
def serve(self, environ: Environ, start_response: typing.Callable) -> Response:
with self.environment():
yield from self.handler(environ, start_response)
@contextlib.contextmanager
def environment(self):
# Load cached imports
global_modules = set(sys.modules.keys())
sys.modules.update(self.import_cache)
# Prefix the import path with the server and venv
for path in self.venv_paths:
sys.path.insert(0, str(path))
sys.path.insert(0, str(self.path / self.wsgi_dir))
try:
yield None
finally:
# Reset the path
sys.path.pop(0)
for _ in self.venv_paths:
sys.path.pop(0)
# Unload imports into a cache
self.import_cache = {
name: sys.modules.pop(name)
for name in set(sys.modules.keys()) - global_modules
}
def log(self, message) -> None:
print(f"(wsgi:{self.script_name}:{self.host_name}): {message}")
@contextlib.contextmanager
def time(self, event: str, start_time: float | None = None):
start_time = start_time or time.perf_counter()
try:
yield None
finally:
end_time = time.perf_counter()
timing = end_time - start_time
self.log(f"[{timing:.3g} s] {event}")
| (host_name: str, script_name: str, path: pathlib.Path, venv_paths: list[pathlib.Path], wsgi_dir: str, module_name: str, object_name: str, version: Any, import_cache: dict[str, module] = <factory>) -> None | [
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] |
727,962 | mod_wsgi_van.server | __eq__ | null | import contextlib
import dataclasses
import importlib
import pathlib
import sys
import time
import types
import typing
Environ = dict[str, str]
Response = typing.Generator
StartResponse = typing.Callable
Handler = typing.Callable[[Environ, StartResponse], Response]
@dataclasses.dataclass
class Server:
host_name: str
script_name: str
path: pathlib.Path
venv_paths: list[pathlib.Path]
wsgi_dir: str
module_name: str
object_name: str
version: typing.Any
import_cache: dict[str, types.ModuleType] = dataclasses.field(default_factory=dict)
def load(self) -> None:
# Load one module at a time since sys is global
self.log("Loading")
with self.time("load"), self.environment():
self.module = importlib.import_module(self.module_name)
self.handler: Handler = getattr(self.module, self.object_name)
def update(self, version: typing.Any) -> None:
if self.version != version:
# Clear import cache and reload
self.import_cache = {}
self.load()
self.version = version
def serve(self, environ: Environ, start_response: typing.Callable) -> Response:
with self.environment():
yield from self.handler(environ, start_response)
@contextlib.contextmanager
def environment(self):
# Load cached imports
global_modules = set(sys.modules.keys())
sys.modules.update(self.import_cache)
# Prefix the import path with the server and venv
for path in self.venv_paths:
sys.path.insert(0, str(path))
sys.path.insert(0, str(self.path / self.wsgi_dir))
try:
yield None
finally:
# Reset the path
sys.path.pop(0)
for _ in self.venv_paths:
sys.path.pop(0)
# Unload imports into a cache
self.import_cache = {
name: sys.modules.pop(name)
for name in set(sys.modules.keys()) - global_modules
}
def log(self, message) -> None:
print(f"(wsgi:{self.script_name}:{self.host_name}): {message}")
@contextlib.contextmanager
def time(self, event: str, start_time: float | None = None):
start_time = start_time or time.perf_counter()
try:
yield None
finally:
end_time = time.perf_counter()
timing = end_time - start_time
self.log(f"[{timing:.3g} s] {event}")
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727,966 | mod_wsgi_van.server | load | null | def load(self) -> None:
# Load one module at a time since sys is global
self.log("Loading")
with self.time("load"), self.environment():
self.module = importlib.import_module(self.module_name)
self.handler: Handler = getattr(self.module, self.object_name)
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] |
727,967 | mod_wsgi_van.server | log | null | def log(self, message) -> None:
print(f"(wsgi:{self.script_name}:{self.host_name}): {message}")
| (self, message) -> NoneType | [
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727,968 | mod_wsgi_van.server | serve | null | def serve(self, environ: Environ, start_response: typing.Callable) -> Response:
with self.environment():
yield from self.handler(environ, start_response)
| (self, environ: dict[str, str], start_response: Callable) -> Generator | [
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727,970 | mod_wsgi_van.server | update | null | def update(self, version: typing.Any) -> None:
if self.version != version:
# Clear import cache and reload
self.import_cache = {}
self.load()
self.version = version
| (self, version: Any) -> NoneType | [
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727,973 | tables.array | Array | This class represents homogeneous datasets in an HDF5 file.
This class provides methods to write or read data to or from array objects
in the file. This class does not allow you neither to enlarge nor compress
the datasets on disk; use the EArray class (see :ref:`EArrayClassDescr`) if
you want enlargeable dataset support or compression features, or CArray
(see :ref:`CArrayClassDescr`) if you just want compression.
An interesting property of the Array class is that it remembers the
*flavor* of the object that has been saved so that if you saved, for
example, a list, you will get a list during readings afterwards; if you
saved a NumPy array, you will get a NumPy object, and so forth.
Note that this class inherits all the public attributes and methods that
Leaf (see :ref:`LeafClassDescr`) already provides. However, as Array
instances have no internal I/O buffers, it is not necessary to use the
flush() method they inherit from Leaf in order to save their internal state
to disk. When a writing method call returns, all the data is already on
disk.
Parameters
----------
parentnode
The parent :class:`Group` object.
.. versionchanged:: 3.0
Renamed from *parentNode* to *parentnode*
name : str
The name of this node in its parent group.
obj
The array or scalar to be saved. Accepted types are NumPy
arrays and scalars as well as native Python sequences and
scalars, provided that values are regular (i.e. they are not
like ``[[1,2],2]``) and homogeneous (i.e. all the elements are
of the same type).
.. versionchanged:: 3.0
Renamed form *object* into *obj*.
title
A description for this node (it sets the ``TITLE`` HDF5 attribute on
disk).
byteorder
The byteorder of the data *on disk*, specified as 'little' or 'big'.
If this is not specified, the byteorder is that of the given `object`.
track_times
Whether time data associated with the leaf are recorded (object
access time, raw data modification time, metadata change time, object
birth time); default True. Semantics of these times depend on their
implementation in the HDF5 library: refer to documentation of the
H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata
change time) is implemented.
.. versionadded:: 3.4.3
| class Array(hdf5extension.Array, Leaf):
"""This class represents homogeneous datasets in an HDF5 file.
This class provides methods to write or read data to or from array objects
in the file. This class does not allow you neither to enlarge nor compress
the datasets on disk; use the EArray class (see :ref:`EArrayClassDescr`) if
you want enlargeable dataset support or compression features, or CArray
(see :ref:`CArrayClassDescr`) if you just want compression.
An interesting property of the Array class is that it remembers the
*flavor* of the object that has been saved so that if you saved, for
example, a list, you will get a list during readings afterwards; if you
saved a NumPy array, you will get a NumPy object, and so forth.
Note that this class inherits all the public attributes and methods that
Leaf (see :ref:`LeafClassDescr`) already provides. However, as Array
instances have no internal I/O buffers, it is not necessary to use the
flush() method they inherit from Leaf in order to save their internal state
to disk. When a writing method call returns, all the data is already on
disk.
Parameters
----------
parentnode
The parent :class:`Group` object.
.. versionchanged:: 3.0
Renamed from *parentNode* to *parentnode*
name : str
The name of this node in its parent group.
obj
The array or scalar to be saved. Accepted types are NumPy
arrays and scalars as well as native Python sequences and
scalars, provided that values are regular (i.e. they are not
like ``[[1,2],2]``) and homogeneous (i.e. all the elements are
of the same type).
.. versionchanged:: 3.0
Renamed form *object* into *obj*.
title
A description for this node (it sets the ``TITLE`` HDF5 attribute on
disk).
byteorder
The byteorder of the data *on disk*, specified as 'little' or 'big'.
If this is not specified, the byteorder is that of the given `object`.
track_times
Whether time data associated with the leaf are recorded (object
access time, raw data modification time, metadata change time, object
birth time); default True. Semantics of these times depend on their
implementation in the HDF5 library: refer to documentation of the
H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata
change time) is implemented.
.. versionadded:: 3.4.3
"""
# Class identifier.
_c_classid = 'ARRAY'
@lazyattr
def dtype(self):
"""The NumPy ``dtype`` that most closely matches this array."""
return self.atom.dtype
@property
def nrows(self):
"""The number of rows in the array."""
if self.shape == ():
return SizeType(1) # scalar case
else:
return self.shape[self.maindim]
@property
def rowsize(self):
"""The size of the rows in bytes in dimensions orthogonal to
*maindim*."""
maindim = self.maindim
rowsize = self.atom.size
for i, dim in enumerate(self.shape):
if i != maindim:
rowsize *= dim
return rowsize
@property
def size_in_memory(self):
"""The size of this array's data in bytes when it is fully loaded into
memory."""
return self.nrows * self.rowsize
def __init__(self, parentnode, name,
obj=None, title="",
byteorder=None, _log=True, _atom=None,
track_times=True):
self._v_version = None
"""The object version of this array."""
self._v_new = new = obj is not None
"""Is this the first time the node has been created?"""
self._v_new_title = title
"""New title for this node."""
self._obj = obj
"""The object to be stored in the array. It can be any of numpy,
list, tuple, string, integer of floating point types, provided
that they are regular (i.e. they are not like ``[[1, 2], 2]``).
.. versionchanged:: 3.0
Renamed form *_object* into *_obj*.
"""
self._v_convert = True
"""Whether the ``Array`` object must be converted or not."""
# Miscellaneous iteration rubbish.
self._start = None
"""Starting row for the current iteration."""
self._stop = None
"""Stopping row for the current iteration."""
self._step = None
"""Step size for the current iteration."""
self._nrowsread = None
"""Number of rows read up to the current state of iteration."""
self._startb = None
"""Starting row for current buffer."""
self._stopb = None
"""Stopping row for current buffer. """
self._row = None
"""Current row in iterators (sentinel)."""
self._init = False
"""Whether we are in the middle of an iteration or not (sentinel)."""
self.listarr = None
"""Current buffer in iterators."""
# Documented (*public*) attributes.
self.atom = _atom
"""An Atom (see :ref:`AtomClassDescr`) instance representing the *type*
and *shape* of the atomic objects to be saved.
"""
self.shape = None
"""The shape of the stored array."""
self.nrow = None
"""On iterators, this is the index of the current row."""
self.extdim = -1 # ordinary arrays are not enlargeable
"""The index of the enlargeable dimension."""
# Ordinary arrays have no filters: leaf is created with default ones.
super().__init__(parentnode, name, new, Filters(), byteorder, _log,
track_times)
def _g_create(self):
"""Save a new array in file."""
self._v_version = obversion
try:
# `Leaf._g_post_init_hook()` should be setting the flavor on disk.
self._flavor = flavor = flavor_of(self._obj)
nparr = array_as_internal(self._obj, flavor)
except Exception: # XXX
# Problems converting data. Close the node and re-raise exception.
self.close(flush=0)
raise
# Raise an error in case of unsupported object
if nparr.dtype.kind in ['V', 'U', 'O']: # in void, unicode, object
raise TypeError("Array objects cannot currently deal with void, "
"unicode or object arrays")
# Decrease the number of references to the object
self._obj = None
# Fix the byteorder of data
nparr = self._g_fix_byteorder_data(nparr, nparr.dtype.byteorder)
# Create the array on-disk
try:
# ``self._v_objectid`` needs to be set because would be
# needed for setting attributes in some descendants later
# on
(self._v_objectid, self.shape, self.atom) = self._create_array(
nparr, self._v_new_title, self.atom)
except Exception: # XXX
# Problems creating the Array on disk. Close node and re-raise.
self.close(flush=0)
raise
# Compute the optimal buffer size
self.nrowsinbuf = self._calc_nrowsinbuf()
# Arrays don't have chunkshapes (so, set it to None)
self._v_chunkshape = None
return self._v_objectid
def _g_open(self):
"""Get the metadata info for an array in file."""
(oid, self.atom, self.shape, self._v_chunkshape) = self._open_array()
self.nrowsinbuf = self._calc_nrowsinbuf()
return oid
def get_enum(self):
"""Get the enumerated type associated with this array.
If this array is of an enumerated type, the corresponding Enum instance
(see :ref:`EnumClassDescr`) is returned. If it is not of an enumerated
type, a TypeError is raised.
"""
if self.atom.kind != 'enum':
raise TypeError("array ``%s`` is not of an enumerated type"
% self._v_pathname)
return self.atom.enum
def iterrows(self, start=Non | (parentnode, name, obj=None, title='', byteorder=None, _log=True, _atom=None, track_times=True) | [
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727,974 | tables.node | __del__ | null | def __del__(self):
# Closed `Node` instances can not be killed and revived.
# Instead, accessing a closed and deleted (from memory, not
# disk) one yields a *new*, open `Node` instance. This is
# because of two reasons:
#
# 1. Predictability. After closing a `Node` and deleting it,
# only one thing can happen when accessing it again: a new,
# open `Node` instance is returned. If closed nodes could be
# revived, one could get either a closed or an open `Node`.
#
# 2. Ease of use. If the user wants to access a closed node
# again, the only condition would be that no references to
# the `Node` instance were left. If closed nodes could be
# revived, the user would also need to force the closed
# `Node` out of memory, which is not a trivial task.
#
if not self._v_isopen:
return # the node is already closed or not initialized
self._v__deleting = True
# If we get here, the `Node` is still open.
try:
node_manager = self._v_file._node_manager
node_manager.drop_node(self, check_unregistered=False)
finally:
# At this point the node can still be open if there is still some
# alive reference around (e.g. if the __del__ method is called
# explicitly by the user).
if self._v_isopen:
self._v__deleting = True
self._f_close()
| (self) | [
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] |
727,975 | tables.array | __getitem__ | Get a row, a range of rows or a slice from the array.
The set of tokens allowed for the key is the same as that for extended
slicing in Python (including the Ellipsis or ... token). The result is
an object of the current flavor; its shape depends on the kind of slice
used as key and the shape of the array itself.
Furthermore, NumPy-style fancy indexing, where a list of indices in a
certain axis is specified, is also supported. Note that only one list
per selection is supported right now. Finally, NumPy-style point and
boolean selections are supported as well.
Examples
--------
::
array1 = array[4] # simple selection
array2 = array[4:1000:2] # slice selection
array3 = array[1, ..., ::2, 1:4, 4:] # general slice selection
array4 = array[1, [1,5,10], ..., -1] # fancy selection
array5 = array[np.where(array[:] > 4)] # point selection
array6 = array[array[:] > 4] # boolean selection
| def __getitem__(self, key):
"""Get a row, a range of rows or a slice from the array.
The set of tokens allowed for the key is the same as that for extended
slicing in Python (including the Ellipsis or ... token). The result is
an object of the current flavor; its shape depends on the kind of slice
used as key and the shape of the array itself.
Furthermore, NumPy-style fancy indexing, where a list of indices in a
certain axis is specified, is also supported. Note that only one list
per selection is supported right now. Finally, NumPy-style point and
boolean selections are supported as well.
Examples
--------
::
array1 = array[4] # simple selection
array2 = array[4:1000:2] # slice selection
array3 = array[1, ..., ::2, 1:4, 4:] # general slice selection
array4 = array[1, [1,5,10], ..., -1] # fancy selection
array5 = array[np.where(array[:] > 4)] # point selection
array6 = array[array[:] > 4] # boolean selection
"""
self._g_check_open()
try:
# First, try with a regular selection
startl, stopl, stepl, shape = self._interpret_indexing(key)
arr = self._read_slice(startl, stopl, stepl, shape)
except TypeError:
# Then, try with a point-wise selection
try:
coords = self._point_selection(key)
arr = self._read_coords(coords)
except TypeError:
# Finally, try with a fancy selection
selection, reorder, shape = self._fancy_selection(key)
arr = self._read_selection(selection, reorder, shape)
if self.flavor == "numpy" or not self._v_convert:
return arr
return internal_to_flavor(arr, self.flavor)
| (self, key) | [
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727,976 | tables.array | __init__ | null | def __init__(self, parentnode, name,
obj=None, title="",
byteorder=None, _log=True, _atom=None,
track_times=True):
self._v_version = None
"""The object version of this array."""
self._v_new = new = obj is not None
"""Is this the first time the node has been created?"""
self._v_new_title = title
"""New title for this node."""
self._obj = obj
"""The object to be stored in the array. It can be any of numpy,
list, tuple, string, integer of floating point types, provided
that they are regular (i.e. they are not like ``[[1, 2], 2]``).
.. versionchanged:: 3.0
Renamed form *_object* into *_obj*.
"""
self._v_convert = True
"""Whether the ``Array`` object must be converted or not."""
# Miscellaneous iteration rubbish.
self._start = None
"""Starting row for the current iteration."""
self._stop = None
"""Stopping row for the current iteration."""
self._step = None
"""Step size for the current iteration."""
self._nrowsread = None
"""Number of rows read up to the current state of iteration."""
self._startb = None
"""Starting row for current buffer."""
self._stopb = None
"""Stopping row for current buffer. """
self._row = None
"""Current row in iterators (sentinel)."""
self._init = False
"""Whether we are in the middle of an iteration or not (sentinel)."""
self.listarr = None
"""Current buffer in iterators."""
# Documented (*public*) attributes.
self.atom = _atom
"""An Atom (see :ref:`AtomClassDescr`) instance representing the *type*
and *shape* of the atomic objects to be saved.
"""
self.shape = None
"""The shape of the stored array."""
self.nrow = None
"""On iterators, this is the index of the current row."""
self.extdim = -1 # ordinary arrays are not enlargeable
"""The index of the enlargeable dimension."""
# Ordinary arrays have no filters: leaf is created with default ones.
super().__init__(parentnode, name, new, Filters(), byteorder, _log,
track_times)
| (self, parentnode, name, obj=None, title='', byteorder=None, _log=True, _atom=None, track_times=True) | [
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] |
727,977 | tables.array | __iter__ | Iterate over the rows of the array.
This is equivalent to calling :meth:`Array.iterrows` with default
arguments, i.e. it iterates over *all the rows* in the array.
Examples
--------
::
result = [row[2] for row in array]
Which is equivalent to::
result = [row[2] for row in array.iterrows()]
| def __iter__(self):
"""Iterate over the rows of the array.
This is equivalent to calling :meth:`Array.iterrows` with default
arguments, i.e. it iterates over *all the rows* in the array.
Examples
--------
::
result = [row[2] for row in array]
Which is equivalent to::
result = [row[2] for row in array.iterrows()]
"""
if not self._init:
# If the iterator is called directly, assign default variables
self._start = 0
self._stop = self.nrows
self._step = 1
# and initialize the loop
self._init_loop()
return self
| (self) | [
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727,978 | tables.leaf | __len__ | Return the length of the main dimension of the leaf data.
Please note that this may raise an OverflowError on 32-bit platforms
for datasets having more than 2**31-1 rows. This is a limitation of
Python that you can work around by using the nrows or shape attributes.
| def __len__(self):
"""Return the length of the main dimension of the leaf data.
Please note that this may raise an OverflowError on 32-bit platforms
for datasets having more than 2**31-1 rows. This is a limitation of
Python that you can work around by using the nrows or shape attributes.
"""
return self.nrows
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