Datasets:

espejelomar

/

code_search_net_python_10000_examples

like 10

honeybadger-io/honeybadger-python

honeybadger/contrib/flask.py

FlaskHoneybadger.init_app

def init_app(self, app, report_exceptions=False, reset_context_after_request=False): """ Initialize honeybadger and listen for errors. :param Flask app: the Flask application object. :param bool report_exceptions: whether to automatically report exceptions raised by Flask on requests (i.e. by calling abort) or not. :param bool reset_context_after_request: whether to reset honeybadger context after each request. """ from flask import request_tearing_down, got_request_exception self.app = app self.app.logger.info('Initializing Honeybadger') self.report_exceptions = report_exceptions self.reset_context_after_request = reset_context_after_request self._initialize_honeybadger(app.config) # Add hooks if self.report_exceptions: self._register_signal_handler('auto-reporting exceptions', got_request_exception, self._handle_exception) if self.reset_context_after_request: self._register_signal_handler('auto clear context on request end', request_tearing_down, self._reset_context) logger.info('Honeybadger helper installed')

python

def init_app(self, app, report_exceptions=False, reset_context_after_request=False): """ Initialize honeybadger and listen for errors. :param Flask app: the Flask application object. :param bool report_exceptions: whether to automatically report exceptions raised by Flask on requests (i.e. by calling abort) or not. :param bool reset_context_after_request: whether to reset honeybadger context after each request. """ from flask import request_tearing_down, got_request_exception self.app = app self.app.logger.info('Initializing Honeybadger') self.report_exceptions = report_exceptions self.reset_context_after_request = reset_context_after_request self._initialize_honeybadger(app.config) # Add hooks if self.report_exceptions: self._register_signal_handler('auto-reporting exceptions', got_request_exception, self._handle_exception) if self.reset_context_after_request: self._register_signal_handler('auto clear context on request end', request_tearing_down, self._reset_context) logger.info('Honeybadger helper installed')

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Initialize honeybadger and listen for errors. :param Flask app: the Flask application object. :param bool report_exceptions: whether to automatically report exceptions raised by Flask on requests (i.e. by calling abort) or not. :param bool reset_context_after_request: whether to reset honeybadger context after each request.

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train

https://github.com/honeybadger-io/honeybadger-python/blob/81519b40d3e446b62035f64e34900e08ff91938c/honeybadger/contrib/flask.py#L98-L127

bwohlberg/sporco

sporco/prox/_lp.py

norm_2l2

def norm_2l2(x, axis=None): r"""Compute the squared :math:`\ell_2` norm .. math:: \| \mathbf{x} \|_2^2 = \sum_i x_i^2 where :math:`x_i` is element :math:`i` of vector :math:`\mathbf{x}`. Parameters ---------- x : array_like Input array :math:`\mathbf{x}` axis : `None` or int or tuple of ints, optional (default None) Axes of `x` over which to compute the :math:`\ell_2` norm. If `None`, an entire multi-dimensional array is treated as a vector. If axes are specified, then distinct values are computed over the indices of the remaining axes of input array `x`. Returns ------- nl2 : float or ndarray Norm of `x`, or array of norms treating specified axes of `x` as a vector. """ nl2 = np.sum(x**2, axis=axis, keepdims=True) # If the result has a single element, convert it to a scalar if nl2.size == 1: nl2 = nl2.ravel()[0] return nl2

python

def norm_2l2(x, axis=None): r"""Compute the squared :math:`\ell_2` norm .. math:: \| \mathbf{x} \|_2^2 = \sum_i x_i^2 where :math:`x_i` is element :math:`i` of vector :math:`\mathbf{x}`. Parameters ---------- x : array_like Input array :math:`\mathbf{x}` axis : `None` or int or tuple of ints, optional (default None) Axes of `x` over which to compute the :math:`\ell_2` norm. If `None`, an entire multi-dimensional array is treated as a vector. If axes are specified, then distinct values are computed over the indices of the remaining axes of input array `x`. Returns ------- nl2 : float or ndarray Norm of `x`, or array of norms treating specified axes of `x` as a vector. """ nl2 = np.sum(x**2, axis=axis, keepdims=True) # If the result has a single element, convert it to a scalar if nl2.size == 1: nl2 = nl2.ravel()[0] return nl2

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r"""Compute the squared :math:`\ell_2` norm .. math:: \| \mathbf{x} \|_2^2 = \sum_i x_i^2 where :math:`x_i` is element :math:`i` of vector :math:`\mathbf{x}`. Parameters ---------- x : array_like Input array :math:`\mathbf{x}` axis : `None` or int or tuple of ints, optional (default None) Axes of `x` over which to compute the :math:`\ell_2` norm. If `None`, an entire multi-dimensional array is treated as a vector. If axes are specified, then distinct values are computed over the indices of the remaining axes of input array `x`. Returns ------- nl2 : float or ndarray Norm of `x`, or array of norms treating specified axes of `x` as a vector.

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train

https://github.com/bwohlberg/sporco/blob/8946a04331106f4e39904fbdf2dc7351900baa04/sporco/prox/_lp.py#L183-L212

caffeinehit/django-oauth2-provider

provider/oauth2/forms.py

ScopeChoiceField.validate

def validate(self, value): """ Validates that the input is a list or tuple. """ if self.required and not value: raise OAuthValidationError({'error': 'invalid_request'}) # Validate that each value in the value list is in self.choices. for val in value: if not self.valid_value(val): raise OAuthValidationError({ 'error': 'invalid_request', 'error_description': _("'%s' is not a valid scope.") % \ val})

python

def validate(self, value): """ Validates that the input is a list or tuple. """ if self.required and not value: raise OAuthValidationError({'error': 'invalid_request'}) # Validate that each value in the value list is in self.choices. for val in value: if not self.valid_value(val): raise OAuthValidationError({ 'error': 'invalid_request', 'error_description': _("'%s' is not a valid scope.") % \ val})

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Validates that the input is a list or tuple.

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train

https://github.com/caffeinehit/django-oauth2-provider/blob/6b5bc0d3ad706d2aaa47fa476f38406cddd01236/provider/oauth2/forms.py#L70-L83

sarenji/pyrc

example.py

GangstaBot.bling

def bling(self, target, sender): "will print yo" if target.startswith("#"): self.message(target, "%s: yo" % sender) else: self.message(sender, "yo")

python

def bling(self, target, sender): "will print yo" if target.startswith("#"): self.message(target, "%s: yo" % sender) else: self.message(sender, "yo")

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will print yo

['will', 'print', 'yo']

train

https://github.com/sarenji/pyrc/blob/5e8377ddcda6e0ef4ba7d66cf400e243b1fb8f68/example.py#L11-L16

collectiveacuity/jsonModel

jsonmodel/validators.py

jsonModel._validate_number

def _validate_number(self, input_number, path_to_root, object_title=''): ''' a helper method for validating properties of a number :return: input_number ''' rules_path_to_root = re.sub('\[\d+\]', '[0]', path_to_root) input_criteria = self.keyMap[rules_path_to_root] error_dict = { 'object_title': object_title, 'model_schema': self.schema, 'input_criteria': input_criteria, 'failed_test': 'value_datatype', 'input_path': path_to_root, 'error_value': input_number, 'error_code': 4001 } if 'integer_data' in input_criteria.keys(): if input_criteria['integer_data'] and not isinstance(input_number, int): error_dict['failed_test'] = 'integer_data' error_dict['error_code'] = 4021 raise InputValidationError(error_dict) if 'min_value' in input_criteria.keys(): if input_number < input_criteria['min_value']: error_dict['failed_test'] = 'min_value' error_dict['error_code'] = 4022 raise InputValidationError(error_dict) if 'max_value' in input_criteria.keys(): if input_number > input_criteria['max_value']: error_dict['failed_test'] = 'max_value' error_dict['error_code'] = 4023 raise InputValidationError(error_dict) if 'greater_than' in input_criteria.keys(): if input_number <= input_criteria['greater_than']: error_dict['failed_test'] = 'greater_than' error_dict['error_code'] = 4024 raise InputValidationError(error_dict) if 'less_than' in input_criteria.keys(): if input_number >= input_criteria['less_than']: error_dict['failed_test'] = 'less_than' error_dict['error_code'] = 4025 raise InputValidationError(error_dict) if 'equal_to' in input_criteria.keys(): if input_number != input_criteria['equal_to']: error_dict['failed_test'] = 'equal_to' error_dict['error_code'] = 4026 raise InputValidationError(error_dict) if 'discrete_values' in input_criteria.keys(): if input_number not in input_criteria['discrete_values']: error_dict['failed_test'] = 'discrete_values' error_dict['error_code'] = 4041 raise InputValidationError(error_dict) if 'excluded_values' in input_criteria.keys(): if input_number in input_criteria['excluded_values']: error_dict['failed_test'] = 'excluded_values' error_dict['error_code'] = 4042 raise InputValidationError(error_dict) # TODO: validate number against identical to reference # TODO: run lambda function and call validation url return input_number

python

def _validate_number(self, input_number, path_to_root, object_title=''): ''' a helper method for validating properties of a number :return: input_number ''' rules_path_to_root = re.sub('\[\d+\]', '[0]', path_to_root) input_criteria = self.keyMap[rules_path_to_root] error_dict = { 'object_title': object_title, 'model_schema': self.schema, 'input_criteria': input_criteria, 'failed_test': 'value_datatype', 'input_path': path_to_root, 'error_value': input_number, 'error_code': 4001 } if 'integer_data' in input_criteria.keys(): if input_criteria['integer_data'] and not isinstance(input_number, int): error_dict['failed_test'] = 'integer_data' error_dict['error_code'] = 4021 raise InputValidationError(error_dict) if 'min_value' in input_criteria.keys(): if input_number < input_criteria['min_value']: error_dict['failed_test'] = 'min_value' error_dict['error_code'] = 4022 raise InputValidationError(error_dict) if 'max_value' in input_criteria.keys(): if input_number > input_criteria['max_value']: error_dict['failed_test'] = 'max_value' error_dict['error_code'] = 4023 raise InputValidationError(error_dict) if 'greater_than' in input_criteria.keys(): if input_number <= input_criteria['greater_than']: error_dict['failed_test'] = 'greater_than' error_dict['error_code'] = 4024 raise InputValidationError(error_dict) if 'less_than' in input_criteria.keys(): if input_number >= input_criteria['less_than']: error_dict['failed_test'] = 'less_than' error_dict['error_code'] = 4025 raise InputValidationError(error_dict) if 'equal_to' in input_criteria.keys(): if input_number != input_criteria['equal_to']: error_dict['failed_test'] = 'equal_to' error_dict['error_code'] = 4026 raise InputValidationError(error_dict) if 'discrete_values' in input_criteria.keys(): if input_number not in input_criteria['discrete_values']: error_dict['failed_test'] = 'discrete_values' error_dict['error_code'] = 4041 raise InputValidationError(error_dict) if 'excluded_values' in input_criteria.keys(): if input_number in input_criteria['excluded_values']: error_dict['failed_test'] = 'excluded_values' error_dict['error_code'] = 4042 raise InputValidationError(error_dict) # TODO: validate number against identical to reference # TODO: run lambda function and call validation url return input_number

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a helper method for validating properties of a number :return: input_number

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train

https://github.com/collectiveacuity/jsonModel/blob/1ea64c36d78add3faa7b85ff82c5ec685458c940/jsonmodel/validators.py#L1000-L1064

IDSIA/sacred

sacred/ingredient.py

Ingredient.gather_named_configs

def gather_named_configs(self, ingredient): """Collect all named configs from this ingredient and its sub-ingredients. Yields ------ config_name: str The full (dotted) name of the named config. config: ConfigScope or ConfigDict or basestring The corresponding named config. """ for config_name, config in ingredient.named_configs.items(): yield join_paths(ingredient.path, config_name), config

python

def gather_named_configs(self, ingredient): """Collect all named configs from this ingredient and its sub-ingredients. Yields ------ config_name: str The full (dotted) name of the named config. config: ConfigScope or ConfigDict or basestring The corresponding named config. """ for config_name, config in ingredient.named_configs.items(): yield join_paths(ingredient.path, config_name), config

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Collect all named configs from this ingredient and its sub-ingredients. Yields ------ config_name: str The full (dotted) name of the named config. config: ConfigScope or ConfigDict or basestring The corresponding named config.

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train

https://github.com/IDSIA/sacred/blob/72633776bed9b5bddf93ae7d215188e61970973a/sacred/ingredient.py#L314-L326

apple/turicreate

src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/text_format.py

MessageToString

def MessageToString(message, as_utf8=False, as_one_line=False, pointy_brackets=False, use_index_order=False, float_format=None, use_field_number=False, descriptor_pool=None, indent=0): """Convert protobuf message to text format. Floating point values can be formatted compactly with 15 digits of precision (which is the most that IEEE 754 "double" can guarantee) using float_format='.15g'. To ensure that converting to text and back to a proto will result in an identical value, float_format='.17g' should be used. Args: message: The protocol buffers message. as_utf8: Produce text output in UTF8 format. as_one_line: Don't introduce newlines between fields. pointy_brackets: If True, use angle brackets instead of curly braces for nesting. use_index_order: If True, print fields of a proto message using the order defined in source code instead of the field number. By default, use the field number order. float_format: If set, use this to specify floating point number formatting (per the "Format Specification Mini-Language"); otherwise, str() is used. use_field_number: If True, print field numbers instead of names. descriptor_pool: A DescriptorPool used to resolve Any types. indent: The indent level, in terms of spaces, for pretty print. Returns: A string of the text formatted protocol buffer message. """ out = TextWriter(as_utf8) printer = _Printer(out, indent, as_utf8, as_one_line, pointy_brackets, use_index_order, float_format, use_field_number, descriptor_pool) printer.PrintMessage(message) result = out.getvalue() out.close() if as_one_line: return result.rstrip() return result

python

def MessageToString(message, as_utf8=False, as_one_line=False, pointy_brackets=False, use_index_order=False, float_format=None, use_field_number=False, descriptor_pool=None, indent=0): """Convert protobuf message to text format. Floating point values can be formatted compactly with 15 digits of precision (which is the most that IEEE 754 "double" can guarantee) using float_format='.15g'. To ensure that converting to text and back to a proto will result in an identical value, float_format='.17g' should be used. Args: message: The protocol buffers message. as_utf8: Produce text output in UTF8 format. as_one_line: Don't introduce newlines between fields. pointy_brackets: If True, use angle brackets instead of curly braces for nesting. use_index_order: If True, print fields of a proto message using the order defined in source code instead of the field number. By default, use the field number order. float_format: If set, use this to specify floating point number formatting (per the "Format Specification Mini-Language"); otherwise, str() is used. use_field_number: If True, print field numbers instead of names. descriptor_pool: A DescriptorPool used to resolve Any types. indent: The indent level, in terms of spaces, for pretty print. Returns: A string of the text formatted protocol buffer message. """ out = TextWriter(as_utf8) printer = _Printer(out, indent, as_utf8, as_one_line, pointy_brackets, use_index_order, float_format, use_field_number, descriptor_pool) printer.PrintMessage(message) result = out.getvalue() out.close() if as_one_line: return result.rstrip() return result

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['Convert', 'protobuf', 'message', 'to', 'text', 'format', '.']

train

https://github.com/apple/turicreate/blob/74514c3f99e25b46f22c6e02977fe3da69221c2e/src/external/coremltools_wrap/coremltools/deps/protobuf/python/google/protobuf/text_format.py#L121-L164

ratt-ru/PyMORESANE

pymoresane/iuwt.py

iuwt_recomposition

def iuwt_recomposition(in1, scale_adjust=0, mode='ser', core_count=1, store_on_gpu=False, smoothed_array=None): """ This function serves as a handler for the different implementations of the IUWT recomposition. It allows the different methods to be used almost interchangeably. INPUTS: in1 (no default): Array on which the decomposition is to be performed. scale_adjust (no default): Number of omitted scales. mode (default='ser') Implementation of the IUWT to be used - 'ser', 'mp' or 'gpu'. core_count (default=1) Additional option for multiprocessing - specifies core count. store_on_gpu (default=False): Boolean specifier for whether the decomposition is stored on the gpu or not. OUTPUTS: Returns the recomposition. """ if mode=='ser': return ser_iuwt_recomposition(in1, scale_adjust, smoothed_array) elif mode=='mp': return mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array) elif mode=='gpu': return gpu_iuwt_recomposition(in1, scale_adjust, store_on_gpu, smoothed_array)

python

def iuwt_recomposition(in1, scale_adjust=0, mode='ser', core_count=1, store_on_gpu=False, smoothed_array=None): """ This function serves as a handler for the different implementations of the IUWT recomposition. It allows the different methods to be used almost interchangeably. INPUTS: in1 (no default): Array on which the decomposition is to be performed. scale_adjust (no default): Number of omitted scales. mode (default='ser') Implementation of the IUWT to be used - 'ser', 'mp' or 'gpu'. core_count (default=1) Additional option for multiprocessing - specifies core count. store_on_gpu (default=False): Boolean specifier for whether the decomposition is stored on the gpu or not. OUTPUTS: Returns the recomposition. """ if mode=='ser': return ser_iuwt_recomposition(in1, scale_adjust, smoothed_array) elif mode=='mp': return mp_iuwt_recomposition(in1, scale_adjust, core_count, smoothed_array) elif mode=='gpu': return gpu_iuwt_recomposition(in1, scale_adjust, store_on_gpu, smoothed_array)

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This function serves as a handler for the different implementations of the IUWT recomposition. It allows the different methods to be used almost interchangeably. INPUTS: in1 (no default): Array on which the decomposition is to be performed. scale_adjust (no default): Number of omitted scales. mode (default='ser') Implementation of the IUWT to be used - 'ser', 'mp' or 'gpu'. core_count (default=1) Additional option for multiprocessing - specifies core count. store_on_gpu (default=False): Boolean specifier for whether the decomposition is stored on the gpu or not. OUTPUTS: Returns the recomposition.

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train

https://github.com/ratt-ru/PyMORESANE/blob/b024591ad0bbb69320d08841f28a2c27f62ae1af/pymoresane/iuwt.py#L43-L64

tanghaibao/jcvi

jcvi/utils/aws.py

start

def start(args): """ %prog start Launch ec2 instance through command line. """ p = OptionParser(start.__doc__) p.add_option("--ondemand", default=False, action="store_true", help="Do we want a more expensive on-demand instance") p.add_option("--profile", default="mvrad-datasci-role", help="Profile name") p.add_option("--price", default=4.0, type=float, help="Spot price") opts, args = p.parse_args(args) if len(args) != 0: sys.exit(not p.print_help()) role(["htang"]) session = boto3.Session(profile_name=opts.profile) client = session.client('ec2') s = InstanceSkeleton() # Make sure the instance id is empty instance_id = s.instance_id if instance_id != "": logging.error("Instance exists {}".format(instance_id)) sys.exit(1) launch_spec = s.launch_spec instance_id = "" if opts.ondemand: # Launch on-demand instance response = client.run_instances( BlockDeviceMappings=s.block_device_mappings, MaxCount=1, MinCount=1, ImageId=s.image_id, InstanceType=s.instance_type, KeyName=s.key_name, Placement={"AvailabilityZone": s.availability_zone}, SecurityGroupIds=s.security_group_ids, SubnetId=s.subnet_id, EbsOptimized=s.ebs_optimized, IamInstanceProfile=s.iam_instance_profile, ) instance_id = response["Instances"][0]["InstanceId"] else: # Launch spot instance response = client.request_spot_instances( SpotPrice=str(opts.price), InstanceCount=1, Type="one-time", AvailabilityZoneGroup=s.availability_zone, LaunchSpecification=launch_spec ) request_id = response["SpotInstanceRequests"][0]["SpotInstanceRequestId"] print("Request id {}".format(request_id), file=sys.stderr) while not instance_id: response = client.describe_spot_instance_requests( SpotInstanceRequestIds=[request_id] ) if "InstanceId" in response["SpotInstanceRequests"][0]: instance_id = response["SpotInstanceRequests"][0]["InstanceId"] else: logging.debug("Waiting to be fulfilled ...") time.sleep(10) # Check if the instance is running print("Instance id {}".format(instance_id), file=sys.stderr) status = "" while status != "running": logging.debug("Waiting instance to run ...") time.sleep(3) response = client.describe_instance_status(InstanceIds=[instance_id]) if len(response["InstanceStatuses"]) > 0: status = response["InstanceStatuses"][0]["InstanceState"]["Name"] # Tagging name = "htang-lx-ondemand" if opts.ondemand else "htang-lx-spot" response = client.create_tags( Resources=[instance_id], Tags=[{"Key": k, "Value": v} for k, v in { \ "Name": name, "owner": "htang", "project": "mv-bioinformatics" }.items()] ) # Attach working volumes volumes = s.volumes for volume in volumes: response = client.attach_volume( VolumeId=volume["VolumeId"], InstanceId=instance_id, Device=volume["Device"] ) # Save instance id and ip response = client.describe_instances(InstanceIds=[instance_id]) ip_address = response["Reservations"][0]["Instances"][0]["PrivateIpAddress"] print("IP address {}".format(ip_address), file=sys.stderr) s.save_instance_id(instance_id, ip_address)

python

def start(args): """ %prog start Launch ec2 instance through command line. """ p = OptionParser(start.__doc__) p.add_option("--ondemand", default=False, action="store_true", help="Do we want a more expensive on-demand instance") p.add_option("--profile", default="mvrad-datasci-role", help="Profile name") p.add_option("--price", default=4.0, type=float, help="Spot price") opts, args = p.parse_args(args) if len(args) != 0: sys.exit(not p.print_help()) role(["htang"]) session = boto3.Session(profile_name=opts.profile) client = session.client('ec2') s = InstanceSkeleton() # Make sure the instance id is empty instance_id = s.instance_id if instance_id != "": logging.error("Instance exists {}".format(instance_id)) sys.exit(1) launch_spec = s.launch_spec instance_id = "" if opts.ondemand: # Launch on-demand instance response = client.run_instances( BlockDeviceMappings=s.block_device_mappings, MaxCount=1, MinCount=1, ImageId=s.image_id, InstanceType=s.instance_type, KeyName=s.key_name, Placement={"AvailabilityZone": s.availability_zone}, SecurityGroupIds=s.security_group_ids, SubnetId=s.subnet_id, EbsOptimized=s.ebs_optimized, IamInstanceProfile=s.iam_instance_profile, ) instance_id = response["Instances"][0]["InstanceId"] else: # Launch spot instance response = client.request_spot_instances( SpotPrice=str(opts.price), InstanceCount=1, Type="one-time", AvailabilityZoneGroup=s.availability_zone, LaunchSpecification=launch_spec ) request_id = response["SpotInstanceRequests"][0]["SpotInstanceRequestId"] print("Request id {}".format(request_id), file=sys.stderr) while not instance_id: response = client.describe_spot_instance_requests( SpotInstanceRequestIds=[request_id] ) if "InstanceId" in response["SpotInstanceRequests"][0]: instance_id = response["SpotInstanceRequests"][0]["InstanceId"] else: logging.debug("Waiting to be fulfilled ...") time.sleep(10) # Check if the instance is running print("Instance id {}".format(instance_id), file=sys.stderr) status = "" while status != "running": logging.debug("Waiting instance to run ...") time.sleep(3) response = client.describe_instance_status(InstanceIds=[instance_id]) if len(response["InstanceStatuses"]) > 0: status = response["InstanceStatuses"][0]["InstanceState"]["Name"] # Tagging name = "htang-lx-ondemand" if opts.ondemand else "htang-lx-spot" response = client.create_tags( Resources=[instance_id], Tags=[{"Key": k, "Value": v} for k, v in { \ "Name": name, "owner": "htang", "project": "mv-bioinformatics" }.items()] ) # Attach working volumes volumes = s.volumes for volume in volumes: response = client.attach_volume( VolumeId=volume["VolumeId"], InstanceId=instance_id, Device=volume["Device"] ) # Save instance id and ip response = client.describe_instances(InstanceIds=[instance_id]) ip_address = response["Reservations"][0]["Instances"][0]["PrivateIpAddress"] print("IP address {}".format(ip_address), file=sys.stderr) s.save_instance_id(instance_id, ip_address)

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train

https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/utils/aws.py#L135-L239

FNNDSC/chrisapp

chrisapp/base.py

ChrisApp.add_argument

def add_argument(self, *args, **kwargs): """ Add a parameter to this app. """ if not (('action' in kwargs) and (kwargs['action'] == 'help')): # make sure required parameter options were defined try: name = kwargs['dest'] param_type = kwargs['type'] optional = kwargs['optional'] except KeyError as e: detail = "%s option required. " % e raise KeyError(detail) if optional and ('default' not in kwargs): detail = "A default value is required for optional parameters %s." % name raise KeyError(detail) # grab the default and help values default = None if 'default' in kwargs: default = kwargs['default'] param_help = "" if 'help' in kwargs: param_help = kwargs['help'] # set the ArgumentParser's action if param_type not in (str, int, float, bool, ChrisApp.path): detail = "unsupported type: '%s'" % param_type raise ValueError(detail) action = 'store' if param_type == bool: action = 'store_false' if default else 'store_true' del kwargs['default'] # 'default' and 'type' not allowed for boolean actions del kwargs['type'] kwargs['action'] = action # store the parameters internally (param_type.__name__ to enable json serialization) param = {'name': name, 'type': param_type.__name__, 'optional': optional, 'flag': args[0], 'action': action, 'help': param_help, 'default': default} self._parameters.append(param) # add the parameter to the parser del kwargs['optional'] ArgumentParser.add_argument(self, *args, **kwargs)

python

def add_argument(self, *args, **kwargs): """ Add a parameter to this app. """ if not (('action' in kwargs) and (kwargs['action'] == 'help')): # make sure required parameter options were defined try: name = kwargs['dest'] param_type = kwargs['type'] optional = kwargs['optional'] except KeyError as e: detail = "%s option required. " % e raise KeyError(detail) if optional and ('default' not in kwargs): detail = "A default value is required for optional parameters %s." % name raise KeyError(detail) # grab the default and help values default = None if 'default' in kwargs: default = kwargs['default'] param_help = "" if 'help' in kwargs: param_help = kwargs['help'] # set the ArgumentParser's action if param_type not in (str, int, float, bool, ChrisApp.path): detail = "unsupported type: '%s'" % param_type raise ValueError(detail) action = 'store' if param_type == bool: action = 'store_false' if default else 'store_true' del kwargs['default'] # 'default' and 'type' not allowed for boolean actions del kwargs['type'] kwargs['action'] = action # store the parameters internally (param_type.__name__ to enable json serialization) param = {'name': name, 'type': param_type.__name__, 'optional': optional, 'flag': args[0], 'action': action, 'help': param_help, 'default': default} self._parameters.append(param) # add the parameter to the parser del kwargs['optional'] ArgumentParser.add_argument(self, *args, **kwargs)

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mardiros/pyshop

pyshop/models.py

User.by_ldap_credentials

def by_ldap_credentials(cls, session, login, password, settings): """if possible try to contact the LDAP for authentification if success and login don't exist localy create one and return it :param session: SQLAlchemy session :type session: :class:`sqlalchemy.Session` :param login: username :type login: unicode :param password: user password :type password: unicode :param settings: settings from self.request.registry.settings in views :type settings: dict :return: associated user :rtype: :class:`pyshop.models.User` """ if not asbool(settings.get('pyshop.ldap.use_for_auth', 'False')): return None if ldap is None: raise ImportError( "no module name ldap. Install python-ldap package") try: if hasattr(ldap, 'OPT_X_TLS_CACERTDIR'): ldap.set_option( ldap.OPT_X_TLS_CACERTDIR, '/etc/openldap/cacerts') ldap.set_option(ldap.OPT_REFERRALS, ldap.OPT_OFF) ldap.set_option(ldap.OPT_RESTART, ldap.OPT_ON) ldap.set_option(ldap.OPT_TIMEOUT, 20) ldap.set_option(ldap.OPT_NETWORK_TIMEOUT, 10) ldap.set_option(ldap.OPT_TIMELIMIT, 15) ldap_server_type = settings.get('pyshop.ldap.type', 'ldap') host = settings['pyshop.ldap.host'].strip() port = settings.get('pyshop.ldap.port', None).strip() if ldap_server_type in ["ldaps", "start_tls"]: port = port or 689 ldap_type = "ldaps" certreq = settings.get('pyshop.ldap.certreq', 'DEMAND').strip() if certreq not in ['DEMAND', 'ALLOW', 'HARD', 'TRY', 'NEVER']: certreq = 'DEMAND' tls_cert = getattr(ldap, 'OPT_X_TLS_%s' % certreq) ldap.set_option(ldap.OPT_X_TLS_REQUIRE_CERT, tls_cert) else: port = port or 389 ldap_type = 'ldap' server_url = "{ldap_type}://{host}:{port}".format( ldap_type=ldap_type, host=host, port=port) server = ldap.initialize(server_url) if ldap_server_type == "start_tls": server.start_tls_s() server.protocol = ldap.VERSION3 # bind the account if needed if settings['pyshop.ldap.account'] and \ settings['pyshop.ldap.password']: server.simple_bind_s(settings['pyshop.ldap.account'], settings['pyshop.ldap.password']) filter_ = settings['pyshop.ldap.search_filter'].format( username=login) results = server.search_ext_s( settings['pyshop.ldap.bind_dn'], getattr(ldap, 'SCOPE_%s' % settings['pyshop.ldap.search_scope']), filter_) if results is None: log.debug("LDAP rejected password for user %s", (login)) return None for (dn, _attrs) in results: if dn is None: continue log.debug('Trying simple bind with %s', dn) server.simple_bind_s(dn, password) attrs = server.search_ext_s( dn, ldap.SCOPE_BASE, '(objectClass=*)')[0][1] break else: log.debug("No matching LDAP objects for authentication of " "'%s'", login) return None log.debug('LDAP authentication OK') # we may create a new user if it don't exist user_ldap = User.by_login(session, login) if user_ldap is None: log.debug('create user %s', login) user_ldap = User() user_ldap.login = login # when creating a User, do not copy the ldap password user_ldap.password = '' user_ldap.local = True user_ldap.firstname = attrs[ settings['pyshop.ldap.first_name_attr']][0] user_ldap.lastname = attrs[ settings['pyshop.ldap.last_name_attr']][0] user_ldap.email = attrs[ settings['pyshop.ldap.email_attr']][0] for groupname in ["developer", "installer"]: user_ldap.groups.append(Group.by_name(session, groupname)) if user_ldap.validate(session): session.add(user_ldap) log.debug('User "%s" added', login) transaction.commit() # its OK return user_ldap except ldap.NO_SUCH_OBJECT: log.debug("LDAP says no such user '%s'", login) except ldap.SERVER_DOWN: log.error("LDAP can't access authentication server") except ldap.LDAPError: log.error('ERROR while using LDAP connection') except Exception as exc: log.error('Unmanaged exception %s', exc, exc_info=True) return None

python

def by_ldap_credentials(cls, session, login, password, settings): """if possible try to contact the LDAP for authentification if success and login don't exist localy create one and return it :param session: SQLAlchemy session :type session: :class:`sqlalchemy.Session` :param login: username :type login: unicode :param password: user password :type password: unicode :param settings: settings from self.request.registry.settings in views :type settings: dict :return: associated user :rtype: :class:`pyshop.models.User` """ if not asbool(settings.get('pyshop.ldap.use_for_auth', 'False')): return None if ldap is None: raise ImportError( "no module name ldap. Install python-ldap package") try: if hasattr(ldap, 'OPT_X_TLS_CACERTDIR'): ldap.set_option( ldap.OPT_X_TLS_CACERTDIR, '/etc/openldap/cacerts') ldap.set_option(ldap.OPT_REFERRALS, ldap.OPT_OFF) ldap.set_option(ldap.OPT_RESTART, ldap.OPT_ON) ldap.set_option(ldap.OPT_TIMEOUT, 20) ldap.set_option(ldap.OPT_NETWORK_TIMEOUT, 10) ldap.set_option(ldap.OPT_TIMELIMIT, 15) ldap_server_type = settings.get('pyshop.ldap.type', 'ldap') host = settings['pyshop.ldap.host'].strip() port = settings.get('pyshop.ldap.port', None).strip() if ldap_server_type in ["ldaps", "start_tls"]: port = port or 689 ldap_type = "ldaps" certreq = settings.get('pyshop.ldap.certreq', 'DEMAND').strip() if certreq not in ['DEMAND', 'ALLOW', 'HARD', 'TRY', 'NEVER']: certreq = 'DEMAND' tls_cert = getattr(ldap, 'OPT_X_TLS_%s' % certreq) ldap.set_option(ldap.OPT_X_TLS_REQUIRE_CERT, tls_cert) else: port = port or 389 ldap_type = 'ldap' server_url = "{ldap_type}://{host}:{port}".format( ldap_type=ldap_type, host=host, port=port) server = ldap.initialize(server_url) if ldap_server_type == "start_tls": server.start_tls_s() server.protocol = ldap.VERSION3 # bind the account if needed if settings['pyshop.ldap.account'] and \ settings['pyshop.ldap.password']: server.simple_bind_s(settings['pyshop.ldap.account'], settings['pyshop.ldap.password']) filter_ = settings['pyshop.ldap.search_filter'].format( username=login) results = server.search_ext_s( settings['pyshop.ldap.bind_dn'], getattr(ldap, 'SCOPE_%s' % settings['pyshop.ldap.search_scope']), filter_) if results is None: log.debug("LDAP rejected password for user %s", (login)) return None for (dn, _attrs) in results: if dn is None: continue log.debug('Trying simple bind with %s', dn) server.simple_bind_s(dn, password) attrs = server.search_ext_s( dn, ldap.SCOPE_BASE, '(objectClass=*)')[0][1] break else: log.debug("No matching LDAP objects for authentication of " "'%s'", login) return None log.debug('LDAP authentication OK') # we may create a new user if it don't exist user_ldap = User.by_login(session, login) if user_ldap is None: log.debug('create user %s', login) user_ldap = User() user_ldap.login = login # when creating a User, do not copy the ldap password user_ldap.password = '' user_ldap.local = True user_ldap.firstname = attrs[ settings['pyshop.ldap.first_name_attr']][0] user_ldap.lastname = attrs[ settings['pyshop.ldap.last_name_attr']][0] user_ldap.email = attrs[ settings['pyshop.ldap.email_attr']][0] for groupname in ["developer", "installer"]: user_ldap.groups.append(Group.by_name(session, groupname)) if user_ldap.validate(session): session.add(user_ldap) log.debug('User "%s" added', login) transaction.commit() # its OK return user_ldap except ldap.NO_SUCH_OBJECT: log.debug("LDAP says no such user '%s'", login) except ldap.SERVER_DOWN: log.error("LDAP can't access authentication server") except ldap.LDAPError: log.error('ERROR while using LDAP connection') except Exception as exc: log.error('Unmanaged exception %s', exc, exc_info=True) return None

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tk0miya/tk.phpautodoc

src/phply/phpparse.py

p_common_scalar_magic_method

def p_common_scalar_magic_method(p): 'common_scalar : METHOD_C' p[0] = ast.MagicConstant(p[1].upper(), None, lineno=p.lineno(1))

python

def p_common_scalar_magic_method(p): 'common_scalar : METHOD_C' p[0] = ast.MagicConstant(p[1].upper(), None, lineno=p.lineno(1))

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codelv/enaml-native

src/enamlnative/android/android_grid_layout.py

AndroidGridLayout.create_widget

def create_widget(self): """ Create the underlying widget. """ d = self.declaration self.widget = GridLayout(self.get_context(), None, d.style)

python

def create_widget(self): """ Create the underlying widget. """ d = self.declaration self.widget = GridLayout(self.get_context(), None, d.style)

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train

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tamasgal/km3pipe

km3pipe/stats.py

param_describe

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python

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omaraboumrad/mastool

mastool/practices.py

find_poor_default_arg

def find_poor_default_arg(node): """Finds poor default args""" poor_defaults = [ ast.Call, ast.Dict, ast.DictComp, ast.GeneratorExp, ast.List, ast.ListComp, ast.Set, ast.SetComp, ] # pylint: disable=unidiomatic-typecheck return ( isinstance(node, ast.FunctionDef) and any((n for n in node.args.defaults if type(n) in poor_defaults)) )

python

def find_poor_default_arg(node): """Finds poor default args""" poor_defaults = [ ast.Call, ast.Dict, ast.DictComp, ast.GeneratorExp, ast.List, ast.ListComp, ast.Set, ast.SetComp, ] # pylint: disable=unidiomatic-typecheck return ( isinstance(node, ast.FunctionDef) and any((n for n in node.args.defaults if type(n) in poor_defaults)) )

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train

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symphonyoss/python-symphony

symphony/Pod/connections.py

Connections.sessioninfo

def sessioninfo(self): ''' session info ''' response, status_code = self.__pod__.Session.get_v2_sessioninfo( sessionToken=self.__session__ ).result() self.logger.debug('%s: %s' % (status_code, response)) return status_code, response

python

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StackStorm/pybind

pybind/slxos/v17r_1_01a/routing_system/route_map/content/set_/__init__.py

set_._set_weight

def _set_weight(self, v, load=False): """ Setter method for weight, mapped from YANG variable /routing_system/route_map/content/set/weight (container) If this variable is read-only (config: false) in the source YANG file, then _set_weight is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_weight() directly. YANG Description: BGP weight for routing table """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=weight.weight, is_container='container', presence=False, yang_name="weight", rest_name="weight", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'BGP weight for routing table', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ip-policy', defining_module='brocade-ip-policy', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """weight must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=weight.weight, is_container='container', presence=False, yang_name="weight", rest_name="weight", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'BGP weight for routing table', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ip-policy', defining_module='brocade-ip-policy', yang_type='container', is_config=True)""", }) self.__weight = t if hasattr(self, '_set'): self._set()

python

def _set_weight(self, v, load=False): """ Setter method for weight, mapped from YANG variable /routing_system/route_map/content/set/weight (container) If this variable is read-only (config: false) in the source YANG file, then _set_weight is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_weight() directly. YANG Description: BGP weight for routing table """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=weight.weight, is_container='container', presence=False, yang_name="weight", rest_name="weight", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'BGP weight for routing table', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ip-policy', defining_module='brocade-ip-policy', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """weight must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=weight.weight, is_container='container', presence=False, yang_name="weight", rest_name="weight", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'BGP weight for routing table', u'cli-full-no': None}}, namespace='urn:brocade.com:mgmt:brocade-ip-policy', defining_module='brocade-ip-policy', yang_type='container', is_config=True)""", }) self.__weight = t if hasattr(self, '_set'): self._set()

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train

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Azure/azure-cosmos-python

azure/cosmos/cosmos_client.py

CosmosClient.DeleteConflict

def DeleteConflict(self, conflict_link, options=None): """Deletes a conflict. :param str conflict_link: The link to the conflict. :param dict options: The request options for the request. :return: The deleted Conflict. :rtype: dict """ if options is None: options = {} path = base.GetPathFromLink(conflict_link) conflict_id = base.GetResourceIdOrFullNameFromLink(conflict_link) return self.DeleteResource(path, 'conflicts', conflict_id, None, options)

python

def DeleteConflict(self, conflict_link, options=None): """Deletes a conflict. :param str conflict_link: The link to the conflict. :param dict options: The request options for the request. :return: The deleted Conflict. :rtype: dict """ if options is None: options = {} path = base.GetPathFromLink(conflict_link) conflict_id = base.GetResourceIdOrFullNameFromLink(conflict_link) return self.DeleteResource(path, 'conflicts', conflict_id, None, options)

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train

https://github.com/Azure/azure-cosmos-python/blob/dd01b3c5d308c6da83cfcaa0ab7083351a476353/azure/cosmos/cosmos_client.py#L2259-L2282

Samreay/ChainConsumer

chainconsumer/diagnostic.py

Diagnostic.gelman_rubin

def gelman_rubin(self, chain=None, threshold=0.05): r""" Runs the Gelman Rubin diagnostic on the supplied chains. Parameters ---------- chain : int|str, optional Which chain to run the diagnostic on. By default, this is `None`, which will run the diagnostic on all chains. You can also supply and integer (the chain index) or a string, for the chain name (if you set one). threshold : float, optional The maximum deviation permitted from 1 for the final value :math:`\hat{R}` Returns ------- float whether or not the chains pass the test Notes ----- I follow PyMC in calculating the Gelman-Rubin statistic, where, having :math:`m` chains of length :math:`n`, we compute .. math:: B = \frac{n}{m-1} \sum_{j=1}^{m} \left(\bar{\theta}_{.j} - \bar{\theta}_{..}\right)^2 W = \frac{1}{m} \sum_{j=1}^{m} \left[ \frac{1}{n-1} \sum_{i=1}^{n} \left( \theta_{ij} - \bar{\theta_{.j}}\right)^2 \right] where :math:`\theta` represents each model parameter. We then compute :math:`\hat{V} = \frac{n_1}{n}W + \frac{1}{n}B`, and have our convergence ratio :math:`\hat{R} = \sqrt{\frac{\hat{V}}{W}}`. We check that for all parameters, this ratio deviates from unity by less than the supplied threshold. """ if chain is None: return np.all([self.gelman_rubin(k, threshold=threshold) for k in range(len(self.parent.chains))]) index = self.parent._get_chain(chain) assert len(index) == 1, "Please specify only one chain, have %d chains" % len(index) chain = self.parent.chains[index[0]] num_walkers = chain.walkers parameters = chain.parameters name = chain.name data = chain.chain chains = np.split(data, num_walkers) assert num_walkers > 1, "Cannot run Gelman-Rubin statistic with only one walker" m = 1.0 * len(chains) n = 1.0 * chains[0].shape[0] all_mean = np.mean(data, axis=0) chain_means = np.array([np.mean(c, axis=0) for c in chains]) chain_var = np.array([np.var(c, axis=0, ddof=1) for c in chains]) b = n / (m - 1) * ((chain_means - all_mean)**2).sum(axis=0) w = (1 / m) * chain_var.sum(axis=0) var = (n - 1) * w / n + b / n v = var + b / (n * m) R = np.sqrt(v / w) passed = np.abs(R - 1) < threshold print("Gelman-Rubin Statistic values for chain %s" % name) for p, v, pas in zip(parameters, R, passed): param = "Param %d" % p if isinstance(p, int) else p print("%s: %7.5f (%s)" % (param, v, "Passed" if pas else "Failed")) return np.all(passed)

python

def gelman_rubin(self, chain=None, threshold=0.05): r""" Runs the Gelman Rubin diagnostic on the supplied chains. Parameters ---------- chain : int|str, optional Which chain to run the diagnostic on. By default, this is `None`, which will run the diagnostic on all chains. You can also supply and integer (the chain index) or a string, for the chain name (if you set one). threshold : float, optional The maximum deviation permitted from 1 for the final value :math:`\hat{R}` Returns ------- float whether or not the chains pass the test Notes ----- I follow PyMC in calculating the Gelman-Rubin statistic, where, having :math:`m` chains of length :math:`n`, we compute .. math:: B = \frac{n}{m-1} \sum_{j=1}^{m} \left(\bar{\theta}_{.j} - \bar{\theta}_{..}\right)^2 W = \frac{1}{m} \sum_{j=1}^{m} \left[ \frac{1}{n-1} \sum_{i=1}^{n} \left( \theta_{ij} - \bar{\theta_{.j}}\right)^2 \right] where :math:`\theta` represents each model parameter. We then compute :math:`\hat{V} = \frac{n_1}{n}W + \frac{1}{n}B`, and have our convergence ratio :math:`\hat{R} = \sqrt{\frac{\hat{V}}{W}}`. We check that for all parameters, this ratio deviates from unity by less than the supplied threshold. """ if chain is None: return np.all([self.gelman_rubin(k, threshold=threshold) for k in range(len(self.parent.chains))]) index = self.parent._get_chain(chain) assert len(index) == 1, "Please specify only one chain, have %d chains" % len(index) chain = self.parent.chains[index[0]] num_walkers = chain.walkers parameters = chain.parameters name = chain.name data = chain.chain chains = np.split(data, num_walkers) assert num_walkers > 1, "Cannot run Gelman-Rubin statistic with only one walker" m = 1.0 * len(chains) n = 1.0 * chains[0].shape[0] all_mean = np.mean(data, axis=0) chain_means = np.array([np.mean(c, axis=0) for c in chains]) chain_var = np.array([np.var(c, axis=0, ddof=1) for c in chains]) b = n / (m - 1) * ((chain_means - all_mean)**2).sum(axis=0) w = (1 / m) * chain_var.sum(axis=0) var = (n - 1) * w / n + b / n v = var + b / (n * m) R = np.sqrt(v / w) passed = np.abs(R - 1) < threshold print("Gelman-Rubin Statistic values for chain %s" % name) for p, v, pas in zip(parameters, R, passed): param = "Param %d" % p if isinstance(p, int) else p print("%s: %7.5f (%s)" % (param, v, "Passed" if pas else "Failed")) return np.all(passed)

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r""" Runs the Gelman Rubin diagnostic on the supplied chains. Parameters ---------- chain : int|str, optional Which chain to run the diagnostic on. By default, this is `None`, which will run the diagnostic on all chains. You can also supply and integer (the chain index) or a string, for the chain name (if you set one). threshold : float, optional The maximum deviation permitted from 1 for the final value :math:`\hat{R}` Returns ------- float whether or not the chains pass the test Notes ----- I follow PyMC in calculating the Gelman-Rubin statistic, where, having :math:`m` chains of length :math:`n`, we compute .. math:: B = \frac{n}{m-1} \sum_{j=1}^{m} \left(\bar{\theta}_{.j} - \bar{\theta}_{..}\right)^2 W = \frac{1}{m} \sum_{j=1}^{m} \left[ \frac{1}{n-1} \sum_{i=1}^{n} \left( \theta_{ij} - \bar{\theta_{.j}}\right)^2 \right] where :math:`\theta` represents each model parameter. We then compute :math:`\hat{V} = \frac{n_1}{n}W + \frac{1}{n}B`, and have our convergence ratio :math:`\hat{R} = \sqrt{\frac{\hat{V}}{W}}`. We check that for all parameters, this ratio deviates from unity by less than the supplied threshold.

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train

https://github.com/Samreay/ChainConsumer/blob/902288e4d85c2677a9051a2172e03128a6169ad7/chainconsumer/diagnostic.py#L11-L76

KelSolaar/Umbra

umbra/ui/widgets/codeEditor_QPlainTextEdit.py

LinesNumbers_QWidget.separator_width

def separator_width(self, value): """ Setter for **self.__separator_width** attribute. :param value: Attribute value. :type value: int """ if value is not None: assert type(value) is int, "'{0}' attribute: '{1}' type is not 'int'!".format("separator_width", value) assert value > 0, "'{0}' attribute: '{1}' need to be exactly positive!".format("separator_width", value) self.__separator_width = value

python

def separator_width(self, value): """ Setter for **self.__separator_width** attribute. :param value: Attribute value. :type value: int """ if value is not None: assert type(value) is int, "'{0}' attribute: '{1}' type is not 'int'!".format("separator_width", value) assert value > 0, "'{0}' attribute: '{1}' need to be exactly positive!".format("separator_width", value) self.__separator_width = value

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train

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SKA-ScienceDataProcessor/integration-prototype

sip/execution_control/configuration_db/sip_config_db/_events/pubsub.py

_get_event_id

def _get_event_id(object_type: str) -> str: """Return an event key for the event on the object type. This must be a unique event id for the object. Args: object_type (str): Type of object Returns: str, event id """ key = _keys.event_counter(object_type) DB.watch(key, pipeline=True) count = DB.get_value(key) DB.increment(key) DB.execute() if count is None: count = 0 return '{}_event_{:08d}'.format(object_type, int(count))

python

def _get_event_id(object_type: str) -> str: """Return an event key for the event on the object type. This must be a unique event id for the object. Args: object_type (str): Type of object Returns: str, event id """ key = _keys.event_counter(object_type) DB.watch(key, pipeline=True) count = DB.get_value(key) DB.increment(key) DB.execute() if count is None: count = 0 return '{}_event_{:08d}'.format(object_type, int(count))

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train

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dmlc/xgboost

python-package/xgboost/core.py

DMatrix.feature_names

def feature_names(self, feature_names): """Set feature names (column labels). Parameters ---------- feature_names : list or None Labels for features. None will reset existing feature names """ if feature_names is not None: # validate feature name try: if not isinstance(feature_names, str): feature_names = [n for n in iter(feature_names)] else: feature_names = [feature_names] except TypeError: feature_names = [feature_names] if len(feature_names) != len(set(feature_names)): raise ValueError('feature_names must be unique') if len(feature_names) != self.num_col(): msg = 'feature_names must have the same length as data' raise ValueError(msg) # prohibit to use symbols may affect to parse. e.g. []< if not all(isinstance(f, STRING_TYPES) and not any(x in f for x in set(('[', ']', '<'))) for f in feature_names): raise ValueError('feature_names may not contain [, ] or <') else: # reset feature_types also self.feature_types = None self._feature_names = feature_names

python

def feature_names(self, feature_names): """Set feature names (column labels). Parameters ---------- feature_names : list or None Labels for features. None will reset existing feature names """ if feature_names is not None: # validate feature name try: if not isinstance(feature_names, str): feature_names = [n for n in iter(feature_names)] else: feature_names = [feature_names] except TypeError: feature_names = [feature_names] if len(feature_names) != len(set(feature_names)): raise ValueError('feature_names must be unique') if len(feature_names) != self.num_col(): msg = 'feature_names must have the same length as data' raise ValueError(msg) # prohibit to use symbols may affect to parse. e.g. []< if not all(isinstance(f, STRING_TYPES) and not any(x in f for x in set(('[', ']', '<'))) for f in feature_names): raise ValueError('feature_names may not contain [, ] or <') else: # reset feature_types also self.feature_types = None self._feature_names = feature_names

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train

https://github.com/dmlc/xgboost/blob/253fdd8a42d5ec6b819788199584d27bf9ea6253/python-package/xgboost/core.py#L843-L874

nion-software/nionswift-io

nionswift_plugin/TIFF_IO/tifffile.py

validate_jhove

def validate_jhove(filename, jhove=None, ignore=None): """Validate TIFF file using jhove -m TIFF-hul. Raise ValueError if jhove outputs an error message unless the message contains one of the strings in 'ignore'. JHOVE does not support bigtiff or more than 50 IFDs. See `JHOVE TIFF-hul Module <http://jhove.sourceforge.net/tiff-hul.html>`_ """ import subprocess # noqa: delayed import if ignore is None: ignore = ['More than 50 IFDs'] if jhove is None: jhove = 'jhove' out = subprocess.check_output([jhove, filename, '-m', 'TIFF-hul']) if b'ErrorMessage: ' in out: for line in out.splitlines(): line = line.strip() if line.startswith(b'ErrorMessage: '): error = line[14:].decode('utf8') for i in ignore: if i in error: break else: raise ValueError(error) break

python

def validate_jhove(filename, jhove=None, ignore=None): """Validate TIFF file using jhove -m TIFF-hul. Raise ValueError if jhove outputs an error message unless the message contains one of the strings in 'ignore'. JHOVE does not support bigtiff or more than 50 IFDs. See `JHOVE TIFF-hul Module <http://jhove.sourceforge.net/tiff-hul.html>`_ """ import subprocess # noqa: delayed import if ignore is None: ignore = ['More than 50 IFDs'] if jhove is None: jhove = 'jhove' out = subprocess.check_output([jhove, filename, '-m', 'TIFF-hul']) if b'ErrorMessage: ' in out: for line in out.splitlines(): line = line.strip() if line.startswith(b'ErrorMessage: '): error = line[14:].decode('utf8') for i in ignore: if i in error: break else: raise ValueError(error) break

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train

https://github.com/nion-software/nionswift-io/blob/e9ae37f01faa9332c48b647f93afd5ef2166b155/nionswift_plugin/TIFF_IO/tifffile.py#L10684-L10711

jbarlow83/OCRmyPDF

src/ocrmypdf/leptonica.py

Pix.scale

def scale(self, scale_xy): "Returns the pix object rescaled according to the proportions given." with _LeptonicaErrorTrap(): return Pix(lept.pixScale(self._cdata, scale_xy[0], scale_xy[1]))

python

def scale(self, scale_xy): "Returns the pix object rescaled according to the proportions given." with _LeptonicaErrorTrap(): return Pix(lept.pixScale(self._cdata, scale_xy[0], scale_xy[1]))

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Returns the pix object rescaled according to the proportions given.

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train

https://github.com/jbarlow83/OCRmyPDF/blob/79c84eefa353632a3d7ccddbd398c6678c1c1777/src/ocrmypdf/leptonica.py#L367-L370

idlesign/uwsgiconf

uwsgiconf/options/applications.py

Applications.switch_into_lazy_mode

def switch_into_lazy_mode(self, affect_master=None): """Load apps in workers instead of master. This option may have memory usage implications as Copy-on-Write semantics can not be used. .. note:: Consider using ``touch_chain_reload`` option in ``workers`` basic params for lazy apps reloading. :param bool affect_master: If **True** only workers will be reloaded by uWSGI's reload signals; the master will remain alive. .. warning:: uWSGI configuration changes are not picked up on reload by the master. """ self._set('lazy' if affect_master else 'lazy-apps', True, cast=bool) return self._section

python

def switch_into_lazy_mode(self, affect_master=None): """Load apps in workers instead of master. This option may have memory usage implications as Copy-on-Write semantics can not be used. .. note:: Consider using ``touch_chain_reload`` option in ``workers`` basic params for lazy apps reloading. :param bool affect_master: If **True** only workers will be reloaded by uWSGI's reload signals; the master will remain alive. .. warning:: uWSGI configuration changes are not picked up on reload by the master. """ self._set('lazy' if affect_master else 'lazy-apps', True, cast=bool) return self._section

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train

https://github.com/idlesign/uwsgiconf/blob/475407acb44199edbf7e0a66261bfeb51de1afae/uwsgiconf/options/applications.py#L70-L88

sanger-pathogens/circlator

circlator/merge.py

Merger._write_act_files

def _write_act_files(self, ref_fasta, qry_fasta, coords_file, outprefix): '''Writes crunch file and shell script to start up ACT, showing comparison of ref and qry''' if self.verbose: print('Making ACT files from', ref_fasta, qry_fasta, coords_file) ref_fasta = os.path.relpath(ref_fasta) qry_fasta = os.path.relpath(qry_fasta) coords_file = os.path.relpath(coords_file) outprefix = os.path.relpath(outprefix) self._index_fasta(ref_fasta) self._index_fasta(qry_fasta) crunch_file = outprefix + '.crunch' pymummer.coords_file.convert_to_msp_crunch( coords_file, crunch_file, ref_fai=ref_fasta + '.fai', qry_fai=qry_fasta + '.fai' ) bash_script = outprefix + '.start_act.sh' with open(bash_script, 'w') as f: print('#!/usr/bin/env bash', file=f) print('act', ref_fasta, crunch_file, qry_fasta, file=f) pyfastaq.utils.syscall('chmod +x ' + bash_script)

python

def _write_act_files(self, ref_fasta, qry_fasta, coords_file, outprefix): '''Writes crunch file and shell script to start up ACT, showing comparison of ref and qry''' if self.verbose: print('Making ACT files from', ref_fasta, qry_fasta, coords_file) ref_fasta = os.path.relpath(ref_fasta) qry_fasta = os.path.relpath(qry_fasta) coords_file = os.path.relpath(coords_file) outprefix = os.path.relpath(outprefix) self._index_fasta(ref_fasta) self._index_fasta(qry_fasta) crunch_file = outprefix + '.crunch' pymummer.coords_file.convert_to_msp_crunch( coords_file, crunch_file, ref_fai=ref_fasta + '.fai', qry_fai=qry_fasta + '.fai' ) bash_script = outprefix + '.start_act.sh' with open(bash_script, 'w') as f: print('#!/usr/bin/env bash', file=f) print('act', ref_fasta, crunch_file, qry_fasta, file=f) pyfastaq.utils.syscall('chmod +x ' + bash_script)

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train

https://github.com/sanger-pathogens/circlator/blob/a4befb8c9dbbcd4b3ad1899a95aa3e689d58b638/circlator/merge.py#L636-L659

jreese/dotlink

dotlink/dotlink.py

Dotlink.scp

def scp(self, local_file, remote_path=''): """Copy a local file to the given remote path.""" if self.args.user: upload_spec = '{0}@{1}:{2}'.format(self.args.user, self.args.server, remote_path) else: upload_spec = '{0}:{1}'.format(self.args.server, remote_path) return self.sh('scp', local_file, upload_spec)

python

def scp(self, local_file, remote_path=''): """Copy a local file to the given remote path.""" if self.args.user: upload_spec = '{0}@{1}:{2}'.format(self.args.user, self.args.server, remote_path) else: upload_spec = '{0}:{1}'.format(self.args.server, remote_path) return self.sh('scp', local_file, upload_spec)

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Copy a local file to the given remote path.

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train

https://github.com/jreese/dotlink/blob/5e48c1493c20fc6df4ad0144e80563915ce339b6/dotlink/dotlink.py#L231-L240

SavinaRoja/PyUserInput

pykeyboard/windows.py

PyKeyboard.release_key

def release_key(self, character=''): """ Release a given character key. """ try: shifted = self.is_char_shifted(character) except AttributeError: win32api.keybd_event(character, 0, KEYEVENTF_KEYUP, 0) else: if shifted: win32api.keybd_event(self.shift_key, 0, KEYEVENTF_KEYUP, 0) char_vk = win32api.VkKeyScan(character) win32api.keybd_event(char_vk, 0, KEYEVENTF_KEYUP, 0)

python

def release_key(self, character=''): """ Release a given character key. """ try: shifted = self.is_char_shifted(character) except AttributeError: win32api.keybd_event(character, 0, KEYEVENTF_KEYUP, 0) else: if shifted: win32api.keybd_event(self.shift_key, 0, KEYEVENTF_KEYUP, 0) char_vk = win32api.VkKeyScan(character) win32api.keybd_event(char_vk, 0, KEYEVENTF_KEYUP, 0)

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train

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maartenbreddels/ipyvolume

ipyvolume/astro.py

_randomSO3

def _randomSO3(): """Return random rotatation matrix, algo by James Arvo.""" u1 = np.random.random() u2 = np.random.random() u3 = np.random.random() R = np.array( [ [np.cos(2 * np.pi * u1), np.sin(2 * np.pi * u1), 0], [-np.sin(2 * np.pi * u1), np.cos(2 * np.pi * u1), 0], [0, 0, 1], ] ) v = np.array([np.cos(2 * np.pi * u2) * np.sqrt(u3), np.sin(2 * np.pi * u2) * np.sqrt(u3), np.sqrt(1 - u3)]) H = np.identity(3) - 2 * v * np.transpose([v]) return -np.dot(H, R)

python

def _randomSO3(): """Return random rotatation matrix, algo by James Arvo.""" u1 = np.random.random() u2 = np.random.random() u3 = np.random.random() R = np.array( [ [np.cos(2 * np.pi * u1), np.sin(2 * np.pi * u1), 0], [-np.sin(2 * np.pi * u1), np.cos(2 * np.pi * u1), 0], [0, 0, 1], ] ) v = np.array([np.cos(2 * np.pi * u2) * np.sqrt(u3), np.sin(2 * np.pi * u2) * np.sqrt(u3), np.sqrt(1 - u3)]) H = np.identity(3) - 2 * v * np.transpose([v]) return -np.dot(H, R)

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Return random rotatation matrix, algo by James Arvo.

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train

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tgalal/yowsup

yowsup/config/transforms/config_dict.py

ConfigDictTransform.transform

def transform(self, config): """ :param config: :type config: dict :return: :rtype: yowsup.config.config.Config """ out = {} for prop in vars(config): out[prop] = getattr(config, prop) return out

python

def transform(self, config): """ :param config: :type config: dict :return: :rtype: yowsup.config.config.Config """ out = {} for prop in vars(config): out[prop] = getattr(config, prop) return out

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train

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Apitax/Apitax

apitax/api/controllers/scriptax_controller.py

delete_driver_script

def delete_driver_script(driver, script_delete=None): # noqa: E501 """Delete a script Delete a script # noqa: E501 :param driver: The driver to use for the request. ie. github :type driver: str :param script_delete: The data needed to delete this script :type script_delete: dict | bytes :rtype: Response """ if connexion.request.is_json: script_delete = ScriptDelete.from_dict(connexion.request.get_json()) # noqa: E501 response = errorIfUnauthorized(role='developer') if response: return response else: response = ApitaxResponse() driver: Driver = LoadedDrivers.getDriver(driver) driver.deleteDriverScript(script_delete.script.name) return Response(status=200, body=response.getResponseBody())

python

def delete_driver_script(driver, script_delete=None): # noqa: E501 """Delete a script Delete a script # noqa: E501 :param driver: The driver to use for the request. ie. github :type driver: str :param script_delete: The data needed to delete this script :type script_delete: dict | bytes :rtype: Response """ if connexion.request.is_json: script_delete = ScriptDelete.from_dict(connexion.request.get_json()) # noqa: E501 response = errorIfUnauthorized(role='developer') if response: return response else: response = ApitaxResponse() driver: Driver = LoadedDrivers.getDriver(driver) driver.deleteDriverScript(script_delete.script.name) return Response(status=200, body=response.getResponseBody())

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Delete a script Delete a script # noqa: E501 :param driver: The driver to use for the request. ie. github :type driver: str :param script_delete: The data needed to delete this script :type script_delete: dict | bytes :rtype: Response

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train

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PyCQA/astroid

astroid/manager.py

AstroidManager.ast_from_file

def ast_from_file(self, filepath, modname=None, fallback=True, source=False): """given a module name, return the astroid object""" try: filepath = modutils.get_source_file(filepath, include_no_ext=True) source = True except modutils.NoSourceFile: pass if modname is None: try: modname = ".".join(modutils.modpath_from_file(filepath)) except ImportError: modname = filepath if ( modname in self.astroid_cache and self.astroid_cache[modname].file == filepath ): return self.astroid_cache[modname] if source: from astroid.builder import AstroidBuilder return AstroidBuilder(self).file_build(filepath, modname) if fallback and modname: return self.ast_from_module_name(modname) raise exceptions.AstroidBuildingError( "Unable to build an AST for {path}.", path=filepath )

python

def ast_from_file(self, filepath, modname=None, fallback=True, source=False): """given a module name, return the astroid object""" try: filepath = modutils.get_source_file(filepath, include_no_ext=True) source = True except modutils.NoSourceFile: pass if modname is None: try: modname = ".".join(modutils.modpath_from_file(filepath)) except ImportError: modname = filepath if ( modname in self.astroid_cache and self.astroid_cache[modname].file == filepath ): return self.astroid_cache[modname] if source: from astroid.builder import AstroidBuilder return AstroidBuilder(self).file_build(filepath, modname) if fallback and modname: return self.ast_from_module_name(modname) raise exceptions.AstroidBuildingError( "Unable to build an AST for {path}.", path=filepath )

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train

https://github.com/PyCQA/astroid/blob/e0a298df55b15abcb77c2a93253f5ab7be52d0fb/astroid/manager.py#L71-L96

tanghaibao/jcvi

jcvi/assembly/postprocess.py

overlap

def overlap(args): """ %prog overlap ctgfasta poolfasta Fish out the sequences in `poolfasta` that overlap with `ctgfasta`. Mix and combine using `minimus2`. """ p = OptionParser(overlap.__doc__) opts, args = p.parse_args(args) if len(args) != 2: sys.exit(not p.print_help()) ctgfasta, poolfasta = args prefix = ctgfasta.split(".")[0] rid = list(Fasta(ctgfasta).iterkeys()) assert len(rid) == 1, "Use overlapbatch() to improve multi-FASTA file" rid = rid[0] splitctgfasta = ctgfasta.rsplit(".", 1)[0] + ".split.fasta" ctgfasta = run_gapsplit(infile=ctgfasta, outfile=splitctgfasta) # Run BLAST blastfile = ctgfasta + ".blast" run_megablast(infile=ctgfasta, outfile=blastfile, db=poolfasta) # Extract contigs and merge using minimus2 closuredir = prefix + ".closure" closure = False if need_update(blastfile, closuredir): mkdir(closuredir, overwrite=True) closure = True if closure: idsfile = op.join(closuredir, prefix + ".ids") cmd = "cut -f2 {0} | sort -u".format(blastfile) sh(cmd, outfile=idsfile) idsfastafile = op.join(closuredir, prefix + ".ids.fasta") cmd = "faSomeRecords {0} {1} {2}".format(poolfasta, idsfile, idsfastafile) sh(cmd) # This step is a hack to weight the bases from original sequences more # than the pulled sequences, by literally adding another copy to be used # in consensus calls. redundantfastafile = op.join(closuredir, prefix + ".redundant.fasta") format([ctgfasta, redundantfastafile, "--prefix=RED."]) mergedfastafile = op.join(closuredir, prefix + ".merged.fasta") cmd = "cat {0} {1} {2}".format(ctgfasta, redundantfastafile, idsfastafile) sh(cmd, outfile=mergedfastafile) afgfile = op.join(closuredir, prefix + ".afg") cmd = "toAmos -s {0} -o {1}".format(mergedfastafile, afgfile) sh(cmd) cwd = os.getcwd() os.chdir(closuredir) cmd = "minimus2 {0} -D REFCOUNT=0".format(prefix) cmd += " -D OVERLAP=100 -D MINID=98" sh(cmd) os.chdir(cwd) # Analyze output, make sure that: # + Get the singletons of the original set back # + Drop any contig that is comprised entirely of pulled set originalIDs = set(Fasta(ctgfasta).iterkeys()) minimuscontig = op.join(closuredir, prefix + ".contig") c = ContigFile(minimuscontig) excludecontigs = set() for rec in c.iter_records(): reads = set(x.id for x in rec.reads) if reads.isdisjoint(originalIDs): excludecontigs.add(rec.id) logging.debug("Exclude contigs: {0}".\ format(", ".join(sorted(excludecontigs)))) finalfasta = prefix + ".improved.fasta_" fw = open(finalfasta, "w") minimusfasta = op.join(closuredir, prefix + ".fasta") f = Fasta(minimusfasta) for id, rec in f.iteritems_ordered(): if id in excludecontigs: continue SeqIO.write([rec], fw, "fasta") singletonfile = op.join(closuredir, prefix + ".singletons") singletons = set(x.strip() for x in open(singletonfile)) leftovers = singletons & originalIDs logging.debug("Pull leftover singletons: {0}".\ format(", ".join(sorted(leftovers)))) f = Fasta(ctgfasta) for id, rec in f.iteritems_ordered(): if id not in leftovers: continue SeqIO.write([rec], fw, "fasta") fw.close() fastafile = finalfasta finalfasta = fastafile.rstrip("_") format([fastafile, finalfasta, "--sequential", "--pad0=3", "--prefix={0}_".format(rid)]) logging.debug("Improved FASTA written to `{0}`.".format(finalfasta)) n50([ctgfasta]) n50([finalfasta]) errlog = "error.log" for f in (fastafile, blastfile, errlog): if op.exists(f): os.remove(f)

python

def overlap(args): """ %prog overlap ctgfasta poolfasta Fish out the sequences in `poolfasta` that overlap with `ctgfasta`. Mix and combine using `minimus2`. """ p = OptionParser(overlap.__doc__) opts, args = p.parse_args(args) if len(args) != 2: sys.exit(not p.print_help()) ctgfasta, poolfasta = args prefix = ctgfasta.split(".")[0] rid = list(Fasta(ctgfasta).iterkeys()) assert len(rid) == 1, "Use overlapbatch() to improve multi-FASTA file" rid = rid[0] splitctgfasta = ctgfasta.rsplit(".", 1)[0] + ".split.fasta" ctgfasta = run_gapsplit(infile=ctgfasta, outfile=splitctgfasta) # Run BLAST blastfile = ctgfasta + ".blast" run_megablast(infile=ctgfasta, outfile=blastfile, db=poolfasta) # Extract contigs and merge using minimus2 closuredir = prefix + ".closure" closure = False if need_update(blastfile, closuredir): mkdir(closuredir, overwrite=True) closure = True if closure: idsfile = op.join(closuredir, prefix + ".ids") cmd = "cut -f2 {0} | sort -u".format(blastfile) sh(cmd, outfile=idsfile) idsfastafile = op.join(closuredir, prefix + ".ids.fasta") cmd = "faSomeRecords {0} {1} {2}".format(poolfasta, idsfile, idsfastafile) sh(cmd) # This step is a hack to weight the bases from original sequences more # than the pulled sequences, by literally adding another copy to be used # in consensus calls. redundantfastafile = op.join(closuredir, prefix + ".redundant.fasta") format([ctgfasta, redundantfastafile, "--prefix=RED."]) mergedfastafile = op.join(closuredir, prefix + ".merged.fasta") cmd = "cat {0} {1} {2}".format(ctgfasta, redundantfastafile, idsfastafile) sh(cmd, outfile=mergedfastafile) afgfile = op.join(closuredir, prefix + ".afg") cmd = "toAmos -s {0} -o {1}".format(mergedfastafile, afgfile) sh(cmd) cwd = os.getcwd() os.chdir(closuredir) cmd = "minimus2 {0} -D REFCOUNT=0".format(prefix) cmd += " -D OVERLAP=100 -D MINID=98" sh(cmd) os.chdir(cwd) # Analyze output, make sure that: # + Get the singletons of the original set back # + Drop any contig that is comprised entirely of pulled set originalIDs = set(Fasta(ctgfasta).iterkeys()) minimuscontig = op.join(closuredir, prefix + ".contig") c = ContigFile(minimuscontig) excludecontigs = set() for rec in c.iter_records(): reads = set(x.id for x in rec.reads) if reads.isdisjoint(originalIDs): excludecontigs.add(rec.id) logging.debug("Exclude contigs: {0}".\ format(", ".join(sorted(excludecontigs)))) finalfasta = prefix + ".improved.fasta_" fw = open(finalfasta, "w") minimusfasta = op.join(closuredir, prefix + ".fasta") f = Fasta(minimusfasta) for id, rec in f.iteritems_ordered(): if id in excludecontigs: continue SeqIO.write([rec], fw, "fasta") singletonfile = op.join(closuredir, prefix + ".singletons") singletons = set(x.strip() for x in open(singletonfile)) leftovers = singletons & originalIDs logging.debug("Pull leftover singletons: {0}".\ format(", ".join(sorted(leftovers)))) f = Fasta(ctgfasta) for id, rec in f.iteritems_ordered(): if id not in leftovers: continue SeqIO.write([rec], fw, "fasta") fw.close() fastafile = finalfasta finalfasta = fastafile.rstrip("_") format([fastafile, finalfasta, "--sequential", "--pad0=3", "--prefix={0}_".format(rid)]) logging.debug("Improved FASTA written to `{0}`.".format(finalfasta)) n50([ctgfasta]) n50([finalfasta]) errlog = "error.log" for f in (fastafile, blastfile, errlog): if op.exists(f): os.remove(f)

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%prog overlap ctgfasta poolfasta Fish out the sequences in `poolfasta` that overlap with `ctgfasta`. Mix and combine using `minimus2`.

['%prog', 'overlap', 'ctgfasta', 'poolfasta']

train

https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/assembly/postprocess.py#L388-L503

StackStorm/pybind

pybind/nos/v6_0_2f/rbridge_id/qos/__init__.py

qos._set_rcv_queue

def _set_rcv_queue(self, v, load=False): """ Setter method for rcv_queue, mapped from YANG variable /rbridge_id/qos/rcv_queue (container) If this variable is read-only (config: false) in the source YANG file, then _set_rcv_queue is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_rcv_queue() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=rcv_queue.rcv_queue, is_container='container', presence=False, yang_name="rcv-queue", rest_name="rcv-queue", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure qos ingress queueing', u'callpoint': u'qos_ingress_queue', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-qos', defining_module='brocade-qos', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """rcv_queue must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=rcv_queue.rcv_queue, is_container='container', presence=False, yang_name="rcv-queue", rest_name="rcv-queue", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure qos ingress queueing', u'callpoint': u'qos_ingress_queue', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-qos', defining_module='brocade-qos', yang_type='container', is_config=True)""", }) self.__rcv_queue = t if hasattr(self, '_set'): self._set()

python

def _set_rcv_queue(self, v, load=False): """ Setter method for rcv_queue, mapped from YANG variable /rbridge_id/qos/rcv_queue (container) If this variable is read-only (config: false) in the source YANG file, then _set_rcv_queue is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_rcv_queue() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=rcv_queue.rcv_queue, is_container='container', presence=False, yang_name="rcv-queue", rest_name="rcv-queue", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure qos ingress queueing', u'callpoint': u'qos_ingress_queue', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-qos', defining_module='brocade-qos', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """rcv_queue must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=rcv_queue.rcv_queue, is_container='container', presence=False, yang_name="rcv-queue", rest_name="rcv-queue", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure qos ingress queueing', u'callpoint': u'qos_ingress_queue', u'cli-incomplete-no': None}}, namespace='urn:brocade.com:mgmt:brocade-qos', defining_module='brocade-qos', yang_type='container', is_config=True)""", }) self.__rcv_queue = t if hasattr(self, '_set'): self._set()

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train

https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/nos/v6_0_2f/rbridge_id/qos/__init__.py#L127-L148

BernardFW/bernard

src/bernard/middleware/_builtins.py

AutoSleep.clean_stacks

def clean_stacks(self, stacks: List[List[BaseLayer]]) \ -> List[List[BaseLayer]]: """ Two cases: if a stack finishes by a sleep then let's keep it (it means that there was nothing after the text). However if the stack finishes with something else (like a quick reply) then we don't risk an is preserved. """ ns: List[List[BaseLayer]] = [] for stack in stacks: if isinstance(stack[-1], lyr.Sleep): ns.extend([x] for x in stack) else: ns.append([x for x in stack if not isinstance(x, lyr.Sleep)]) if not ns: return ns last = ns[-1] if len(last) == 1 and isinstance(last[0], lyr.Sleep): return ns[:-1] else: return ns

python

def clean_stacks(self, stacks: List[List[BaseLayer]]) \ -> List[List[BaseLayer]]: """ Two cases: if a stack finishes by a sleep then let's keep it (it means that there was nothing after the text). However if the stack finishes with something else (like a quick reply) then we don't risk an is preserved. """ ns: List[List[BaseLayer]] = [] for stack in stacks: if isinstance(stack[-1], lyr.Sleep): ns.extend([x] for x in stack) else: ns.append([x for x in stack if not isinstance(x, lyr.Sleep)]) if not ns: return ns last = ns[-1] if len(last) == 1 and isinstance(last[0], lyr.Sleep): return ns[:-1] else: return ns

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https://github.com/BernardFW/bernard/blob/9c55703e5ffe5717c9fa39793df59dbfa5b4c5ab/src/bernard/middleware/_builtins.py#L95-L119

JdeRobot/base

src/drivers/MAVLinkServer/MAVProxy/pymavlink/rotmat.py

Matrix3.from_euler

def from_euler(self, roll, pitch, yaw): '''fill the matrix from Euler angles in radians''' cp = cos(pitch) sp = sin(pitch) sr = sin(roll) cr = cos(roll) sy = sin(yaw) cy = cos(yaw) self.a.x = cp * cy self.a.y = (sr * sp * cy) - (cr * sy) self.a.z = (cr * sp * cy) + (sr * sy) self.b.x = cp * sy self.b.y = (sr * sp * sy) + (cr * cy) self.b.z = (cr * sp * sy) - (sr * cy) self.c.x = -sp self.c.y = sr * cp self.c.z = cr * cp

python

def from_euler(self, roll, pitch, yaw): '''fill the matrix from Euler angles in radians''' cp = cos(pitch) sp = sin(pitch) sr = sin(roll) cr = cos(roll) sy = sin(yaw) cy = cos(yaw) self.a.x = cp * cy self.a.y = (sr * sp * cy) - (cr * sy) self.a.z = (cr * sp * cy) + (sr * sy) self.b.x = cp * sy self.b.y = (sr * sp * sy) + (cr * cy) self.b.z = (cr * sp * sy) - (sr * cy) self.c.x = -sp self.c.y = sr * cp self.c.z = cr * cp

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eventbrite/eventbrite-sdk-python

eventbrite/access_methods.py

AccessMethodsMixin.get_user_events

def get_user_events(self, id, **data): """ GET /users/:id/events/ Returns a :ref:`paginated <pagination>` response of :format:`events <event>`, under the key ``events``, of all events the user has access to """ return self.get("/users/{0}/events/".format(id), data=data)

python

def get_user_events(self, id, **data): """ GET /users/:id/events/ Returns a :ref:`paginated <pagination>` response of :format:`events <event>`, under the key ``events``, of all events the user has access to """ return self.get("/users/{0}/events/".format(id), data=data)

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dw/mitogen

mitogen/core.py

Latch.close

def close(self): """ Mark the latch as closed, and cause every sleeping thread to be woken, with :class:`mitogen.core.LatchError` raised in each thread. """ self._lock.acquire() try: self.closed = True while self._waking < len(self._sleeping): wsock, cookie = self._sleeping[self._waking] self._wake(wsock, cookie) self._waking += 1 finally: self._lock.release()

python

def close(self): """ Mark the latch as closed, and cause every sleeping thread to be woken, with :class:`mitogen.core.LatchError` raised in each thread. """ self._lock.acquire() try: self.closed = True while self._waking < len(self._sleeping): wsock, cookie = self._sleeping[self._waking] self._wake(wsock, cookie) self._waking += 1 finally: self._lock.release()

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bodylabs/lace

lace/topology.py

MeshMixin.remove_redundant_verts

def remove_redundant_verts(self, eps=1e-10): """Given verts and faces, this remove colocated vertices""" import numpy as np from scipy.spatial import cKDTree # FIXME pylint: disable=no-name-in-module fshape = self.f.shape tree = cKDTree(self.v) close_pairs = list(tree.query_pairs(eps)) if close_pairs: close_pairs = np.sort(close_pairs, axis=1) # update faces to not refer to redundant vertices equivalent_verts = np.arange(self.v.shape[0]) for v1, v2 in close_pairs: if equivalent_verts[v2] > v1: equivalent_verts[v2] = v1 self.f = equivalent_verts[self.f.flatten()].reshape((-1, 3)) # get rid of unused verts, and update faces accordingly vertidxs_left = np.unique(self.f) repl = np.arange(np.max(self.f)+1) repl[vertidxs_left] = np.arange(len(vertidxs_left)) self.v = self.v[vertidxs_left] self.f = repl[self.f].reshape((-1, fshape[1]))

python

def remove_redundant_verts(self, eps=1e-10): """Given verts and faces, this remove colocated vertices""" import numpy as np from scipy.spatial import cKDTree # FIXME pylint: disable=no-name-in-module fshape = self.f.shape tree = cKDTree(self.v) close_pairs = list(tree.query_pairs(eps)) if close_pairs: close_pairs = np.sort(close_pairs, axis=1) # update faces to not refer to redundant vertices equivalent_verts = np.arange(self.v.shape[0]) for v1, v2 in close_pairs: if equivalent_verts[v2] > v1: equivalent_verts[v2] = v1 self.f = equivalent_verts[self.f.flatten()].reshape((-1, 3)) # get rid of unused verts, and update faces accordingly vertidxs_left = np.unique(self.f) repl = np.arange(np.max(self.f)+1) repl[vertidxs_left] = np.arange(len(vertidxs_left)) self.v = self.v[vertidxs_left] self.f = repl[self.f].reshape((-1, fshape[1]))

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fastai/fastai

fastai/vision/data.py

_db_pre_transform

def _db_pre_transform(self, train_tfm:List[Callable], valid_tfm:List[Callable]): "Call `train_tfm` and `valid_tfm` after opening image, before converting from `PIL.Image`" self.train_ds.x.after_open = compose(train_tfm) self.valid_ds.x.after_open = compose(valid_tfm) return self

python

def _db_pre_transform(self, train_tfm:List[Callable], valid_tfm:List[Callable]): "Call `train_tfm` and `valid_tfm` after opening image, before converting from `PIL.Image`" self.train_ds.x.after_open = compose(train_tfm) self.valid_ds.x.after_open = compose(valid_tfm) return self

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modin-project/modin

modin/backends/pandas/query_compiler.py

PandasQueryCompiler.numeric_function_clean_dataframe

def numeric_function_clean_dataframe(self, axis): """Preprocesses numeric functions to clean dataframe and pick numeric indices. Args: axis: '0' if columns and '1' if rows. Returns: Tuple with return value(if any), indices to apply func to & cleaned Manager. """ result = None query_compiler = self # If no numeric columns and over columns, then return empty Series if not axis and len(self.index) == 0: result = pandas.Series(dtype=np.int64) nonnumeric = [ col for col, dtype in zip(self.columns, self.dtypes) if not is_numeric_dtype(dtype) ] if len(nonnumeric) == len(self.columns): # If over rows and no numeric columns, return this if axis: result = pandas.Series([np.nan for _ in self.index]) else: result = pandas.Series([0 for _ in self.index]) else: query_compiler = self.drop(columns=nonnumeric) return result, query_compiler

python

def numeric_function_clean_dataframe(self, axis): """Preprocesses numeric functions to clean dataframe and pick numeric indices. Args: axis: '0' if columns and '1' if rows. Returns: Tuple with return value(if any), indices to apply func to & cleaned Manager. """ result = None query_compiler = self # If no numeric columns and over columns, then return empty Series if not axis and len(self.index) == 0: result = pandas.Series(dtype=np.int64) nonnumeric = [ col for col, dtype in zip(self.columns, self.dtypes) if not is_numeric_dtype(dtype) ] if len(nonnumeric) == len(self.columns): # If over rows and no numeric columns, return this if axis: result = pandas.Series([np.nan for _ in self.index]) else: result = pandas.Series([0 for _ in self.index]) else: query_compiler = self.drop(columns=nonnumeric) return result, query_compiler

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pmacosta/pmisc

pmisc/member.py

isreal

def isreal(obj): """ Test if the argument is a real number (float or integer). :param obj: Object :type obj: any :rtype: boolean """ return ( (obj is not None) and (not isinstance(obj, bool)) and isinstance(obj, (int, float)) )

python

def isreal(obj): """ Test if the argument is a real number (float or integer). :param obj: Object :type obj: any :rtype: boolean """ return ( (obj is not None) and (not isinstance(obj, bool)) and isinstance(obj, (int, float)) )

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train

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twilio/twilio-python

twilio/rest/api/v2010/account/__init__.py

AccountContext.new_keys

def new_keys(self): """ Access the new_keys :returns: twilio.rest.api.v2010.account.new_key.NewKeyList :rtype: twilio.rest.api.v2010.account.new_key.NewKeyList """ if self._new_keys is None: self._new_keys = NewKeyList(self._version, account_sid=self._solution['sid'], ) return self._new_keys

python

def new_keys(self): """ Access the new_keys :returns: twilio.rest.api.v2010.account.new_key.NewKeyList :rtype: twilio.rest.api.v2010.account.new_key.NewKeyList """ if self._new_keys is None: self._new_keys = NewKeyList(self._version, account_sid=self._solution['sid'], ) return self._new_keys

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ewels/MultiQC

multiqc/modules/bbmap/bbmap.py

MultiqcModule.make_basic_table

def make_basic_table(self, file_type): """ Create table of key-value items in 'file_type'. """ table_data = {sample: items['kv'] for sample, items in self.mod_data[file_type].items() } table_headers = {} for column_header, (description, header_options) in file_types[file_type]['kv_descriptions'].items(): table_headers[column_header] = { 'rid': '{}_{}_bbmstheader'.format(file_type, column_header), 'title': column_header, 'description': description, } table_headers[column_header].update(header_options) tconfig = { 'id': file_type + '_bbm_table', 'namespace': 'BBTools' } for sample in table_data: for key, value in table_data[sample].items(): try: table_data[sample][key] = float(value) except ValueError: pass return table.plot(table_data, table_headers, tconfig)

python

def make_basic_table(self, file_type): """ Create table of key-value items in 'file_type'. """ table_data = {sample: items['kv'] for sample, items in self.mod_data[file_type].items() } table_headers = {} for column_header, (description, header_options) in file_types[file_type]['kv_descriptions'].items(): table_headers[column_header] = { 'rid': '{}_{}_bbmstheader'.format(file_type, column_header), 'title': column_header, 'description': description, } table_headers[column_header].update(header_options) tconfig = { 'id': file_type + '_bbm_table', 'namespace': 'BBTools' } for sample in table_data: for key, value in table_data[sample].items(): try: table_data[sample][key] = float(value) except ValueError: pass return table.plot(table_data, table_headers, tconfig)

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saltstack/salt

salt/modules/systemd_service.py

_check_unmask

def _check_unmask(name, unmask, unmask_runtime, root=None): ''' Common code for conditionally removing masks before making changes to a service's state. ''' if unmask: unmask_(name, runtime=False, root=root) if unmask_runtime: unmask_(name, runtime=True, root=root)

python

def _check_unmask(name, unmask, unmask_runtime, root=None): ''' Common code for conditionally removing masks before making changes to a service's state. ''' if unmask: unmask_(name, runtime=False, root=root) if unmask_runtime: unmask_(name, runtime=True, root=root)

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train

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ArtoLabs/SimpleSteem

simplesteem/util.py

Util.minutes_back

def minutes_back(self, date): ''' Gives a number (integer) of days since a given date ''' elapsed = (datetime.utcnow() - datetime.strptime(date,'%Y-%m-%dT%H:%M:%S')) if elapsed.days > 0: secondsback = (elapsed.days * 24 * 60 * 60) + elapsed.seconds else: secondsback = elapsed.seconds minutesback = secondsback / 60 return int(minutesback)

python

def minutes_back(self, date): ''' Gives a number (integer) of days since a given date ''' elapsed = (datetime.utcnow() - datetime.strptime(date,'%Y-%m-%dT%H:%M:%S')) if elapsed.days > 0: secondsback = (elapsed.days * 24 * 60 * 60) + elapsed.seconds else: secondsback = elapsed.seconds minutesback = secondsback / 60 return int(minutesback)

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fulfilio/fulfil-python-api

fulfil_client/client.py

AsyncResult.refresh_if_needed

def refresh_if_needed(self): """ Refresh the status of the task from server if required. """ if self.state in (self.PENDING, self.STARTED): try: response, = self._fetch_result()['tasks'] except (KeyError, ValueError): raise Exception( "Unable to find results for task." ) if 'error' in response: self.state == self.FAILURE raise ServerError(response['error']) if 'state' in response: self.state = response['state'] self.result = response['result']

python

def refresh_if_needed(self): """ Refresh the status of the task from server if required. """ if self.state in (self.PENDING, self.STARTED): try: response, = self._fetch_result()['tasks'] except (KeyError, ValueError): raise Exception( "Unable to find results for task." ) if 'error' in response: self.state == self.FAILURE raise ServerError(response['error']) if 'state' in response: self.state = response['state'] self.result = response['result']

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elapouya/python-textops

textops/base.py

eformat

def eformat(format_str,lst,dct,defvalue='-'): """ Formats a list and a dictionary, manages unkown keys It works like :meth:`string.Formatter.vformat` except that it accepts a defvalue for not matching keys. Defvalue can be a callable that will receive the requested key as argument and return a string Args: format_string (str): Same format string as for :meth:`str.format` lst (dict) : the list to format dct (dict) : the dict to format defvalue (str or callable): the default value to display when the data is not in the dict Examples: >>> d = {'count': '32591', 'soft': 'textops'} >>> l = ['Eric','Guido'] >>> eformat('{0} => {soft} : {count} dowloads',l,d) 'Eric => textops : 32591 dowloads' >>> eformat('{2} => {software} : {count} dowloads',l,d,'N/A') 'N/A => N/A : 32591 dowloads' >>> eformat('{2} => {software} : {count} dowloads',l,d,lambda k:'unknown_tag_%s' % k) 'unknown_tag_2 => unknown_tag_software : 32591 dowloads' """ return vformat(format_str,DefaultList(defvalue,lst),DefaultDict(defvalue,dct))

python

def eformat(format_str,lst,dct,defvalue='-'): """ Formats a list and a dictionary, manages unkown keys It works like :meth:`string.Formatter.vformat` except that it accepts a defvalue for not matching keys. Defvalue can be a callable that will receive the requested key as argument and return a string Args: format_string (str): Same format string as for :meth:`str.format` lst (dict) : the list to format dct (dict) : the dict to format defvalue (str or callable): the default value to display when the data is not in the dict Examples: >>> d = {'count': '32591', 'soft': 'textops'} >>> l = ['Eric','Guido'] >>> eformat('{0} => {soft} : {count} dowloads',l,d) 'Eric => textops : 32591 dowloads' >>> eformat('{2} => {software} : {count} dowloads',l,d,'N/A') 'N/A => N/A : 32591 dowloads' >>> eformat('{2} => {software} : {count} dowloads',l,d,lambda k:'unknown_tag_%s' % k) 'unknown_tag_2 => unknown_tag_software : 32591 dowloads' """ return vformat(format_str,DefaultList(defvalue,lst),DefaultDict(defvalue,dct))

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train

https://github.com/elapouya/python-textops/blob/5c63b9074a1acd8dd108725f1b370f6684c941ef/textops/base.py#L1035-L1058

saltstack/salt

salt/modules/mysql.py

verify_login

def verify_login(user, password=None, **connection_args): ''' Attempt to login using the provided credentials. If successful, return true. Otherwise, return False. CLI Example: .. code-block:: bash salt '*' mysql.verify_login root password ''' # Override the connection args for username and password connection_args['connection_user'] = user connection_args['connection_pass'] = password dbc = _connect(**connection_args) if dbc is None: # Clear the mysql.error if unable to connect # if the connection fails, we simply return False if 'mysql.error' in __context__: del __context__['mysql.error'] return False return True

python

def verify_login(user, password=None, **connection_args): ''' Attempt to login using the provided credentials. If successful, return true. Otherwise, return False. CLI Example: .. code-block:: bash salt '*' mysql.verify_login root password ''' # Override the connection args for username and password connection_args['connection_user'] = user connection_args['connection_pass'] = password dbc = _connect(**connection_args) if dbc is None: # Clear the mysql.error if unable to connect # if the connection fails, we simply return False if 'mysql.error' in __context__: del __context__['mysql.error'] return False return True

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train

https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/mysql.py#L2336-L2358

tgbugs/pyontutils

neurondm/neurondm/lang.py

config

def config(remote_base= 'https://raw.githubusercontent.com/SciCrunch/NIF-Ontology/', local_base= None, # devconfig.ontology_local_repo by default branch= devconfig.neurons_branch, core_graph_paths= ['ttl/phenotype-core.ttl', 'ttl/phenotypes.ttl'], core_graph= None, in_graph_paths= tuple(), out_graph_path= '/tmp/_Neurons.ttl', out_imports= ['ttl/phenotype-core.ttl'], out_graph= None, prefixes= tuple(), force_remote= False, checkout_ok= ont_checkout_ok, scigraph= None, # defaults to devconfig.scigraph_api iri= None, sources= tuple(), source_file= None, use_local_import_paths=True, ignore_existing= True): """ Wraps graphBase.configGraphIO to provide a set of sane defaults for input ontologies and output files. """ graphBase.configGraphIO(remote_base=remote_base, local_base=local_base, branch=branch, core_graph_paths=core_graph_paths, core_graph=core_graph, in_graph_paths=in_graph_paths, out_graph_path=out_graph_path, out_imports=out_imports, out_graph=out_graph, prefixes=prefixes, force_remote=force_remote, checkout_ok=checkout_ok, scigraph=scigraph, iri=iri, sources=sources, source_file=source_file, use_local_import_paths=use_local_import_paths, ignore_existing=ignore_existing) pred = graphBase._predicates return pred

python

def config(remote_base= 'https://raw.githubusercontent.com/SciCrunch/NIF-Ontology/', local_base= None, # devconfig.ontology_local_repo by default branch= devconfig.neurons_branch, core_graph_paths= ['ttl/phenotype-core.ttl', 'ttl/phenotypes.ttl'], core_graph= None, in_graph_paths= tuple(), out_graph_path= '/tmp/_Neurons.ttl', out_imports= ['ttl/phenotype-core.ttl'], out_graph= None, prefixes= tuple(), force_remote= False, checkout_ok= ont_checkout_ok, scigraph= None, # defaults to devconfig.scigraph_api iri= None, sources= tuple(), source_file= None, use_local_import_paths=True, ignore_existing= True): """ Wraps graphBase.configGraphIO to provide a set of sane defaults for input ontologies and output files. """ graphBase.configGraphIO(remote_base=remote_base, local_base=local_base, branch=branch, core_graph_paths=core_graph_paths, core_graph=core_graph, in_graph_paths=in_graph_paths, out_graph_path=out_graph_path, out_imports=out_imports, out_graph=out_graph, prefixes=prefixes, force_remote=force_remote, checkout_ok=checkout_ok, scigraph=scigraph, iri=iri, sources=sources, source_file=source_file, use_local_import_paths=use_local_import_paths, ignore_existing=ignore_existing) pred = graphBase._predicates return pred

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train

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gabstopper/smc-python

smc/base/collection.py

ElementCollection.filter

def filter(self, *filter, **kw): # @ReservedAssignment """ Filter results for specific element type. keyword arguments can be used to specify a match against the elements attribute directly. It's important to note that if the search filter contains a / or -, the SMC will only search the name and comment fields. Otherwise other key fields of an element are searched. In addition, SMC searches are a 'contains' search meaning you may return more results than wanted. Use a key word argument to specify the elements attribute and value expected. :: >>> list(Router.objects.filter('10.10.10.1')) [Router(name=Router-110.10.10.10), Router(name=Router-10.10.10.10), Router(name=Router-10.10.10.1)] >>> list(Router.objects.filter(address='10.10.10.1')) [Router(name=Router-10.10.10.1)] :param str filter: any parameter to attempt to match on. For example, if this is a service, you could match on service name 'http' or ports of interest, '80'. :param bool exact_match: Can be passed as a keyword arg. Specifies whether the match needs to be exact or not (default: False) :param bool case_sensitive: Can be passed as a keyword arg. Specifies whether the match is case sensitive or not. (default: True) :param kw: keyword args can specify an attribute=value to use as an exact match against the elements attribute. :return: :class:`.ElementCollection` """ iexact = None if filter: _filter = filter[0] exact_match = kw.pop('exact_match', False) case_sensitive = kw.pop('case_sensitive', True) if kw: _, value = next(iter(kw.items())) _filter = value iexact = kw # Only strip metachars from network and address range if not exact_match and self._params.get('filter_context', {})\ in ('network', 'address_range', 'network_elements'): _filter = _strip_metachars(_filter) return self._clone( filter=_filter, iexact=iexact, exact_match=exact_match, case_sensitive=case_sensitive)

python

def filter(self, *filter, **kw): # @ReservedAssignment """ Filter results for specific element type. keyword arguments can be used to specify a match against the elements attribute directly. It's important to note that if the search filter contains a / or -, the SMC will only search the name and comment fields. Otherwise other key fields of an element are searched. In addition, SMC searches are a 'contains' search meaning you may return more results than wanted. Use a key word argument to specify the elements attribute and value expected. :: >>> list(Router.objects.filter('10.10.10.1')) [Router(name=Router-110.10.10.10), Router(name=Router-10.10.10.10), Router(name=Router-10.10.10.1)] >>> list(Router.objects.filter(address='10.10.10.1')) [Router(name=Router-10.10.10.1)] :param str filter: any parameter to attempt to match on. For example, if this is a service, you could match on service name 'http' or ports of interest, '80'. :param bool exact_match: Can be passed as a keyword arg. Specifies whether the match needs to be exact or not (default: False) :param bool case_sensitive: Can be passed as a keyword arg. Specifies whether the match is case sensitive or not. (default: True) :param kw: keyword args can specify an attribute=value to use as an exact match against the elements attribute. :return: :class:`.ElementCollection` """ iexact = None if filter: _filter = filter[0] exact_match = kw.pop('exact_match', False) case_sensitive = kw.pop('case_sensitive', True) if kw: _, value = next(iter(kw.items())) _filter = value iexact = kw # Only strip metachars from network and address range if not exact_match and self._params.get('filter_context', {})\ in ('network', 'address_range', 'network_elements'): _filter = _strip_metachars(_filter) return self._clone( filter=_filter, iexact=iexact, exact_match=exact_match, case_sensitive=case_sensitive)

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train

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hardbyte/python-can

can/io/sqlite.py

SqliteWriter.stop

def stop(self): """Stops the reader an writes all remaining messages to the database. Thus, this might take a while and block. """ BufferedReader.stop(self) self._stop_running_event.set() self._writer_thread.join() BaseIOHandler.stop(self)

python

def stop(self): """Stops the reader an writes all remaining messages to the database. Thus, this might take a while and block. """ BufferedReader.stop(self) self._stop_running_event.set() self._writer_thread.join() BaseIOHandler.stop(self)

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django-fluent/django-fluent-comments

fluent_comments/__init__.py

get_form

def get_form(): """ Return the form to use for commenting. """ global form_class from fluent_comments import appsettings if form_class is None: if appsettings.FLUENT_COMMENTS_FORM_CLASS: from django.utils.module_loading import import_string form_class = import_string(appsettings.FLUENT_COMMENTS_FORM_CLASS) else: from fluent_comments.forms import FluentCommentForm form_class = FluentCommentForm return form_class

python

def get_form(): """ Return the form to use for commenting. """ global form_class from fluent_comments import appsettings if form_class is None: if appsettings.FLUENT_COMMENTS_FORM_CLASS: from django.utils.module_loading import import_string form_class = import_string(appsettings.FLUENT_COMMENTS_FORM_CLASS) else: from fluent_comments.forms import FluentCommentForm form_class = FluentCommentForm return form_class

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openclimatedata/pymagicc

pymagicc/definitions/__init__.py

get_magicc6_to_magicc7_variable_mapping

def get_magicc6_to_magicc7_variable_mapping(inverse=False): """Get the mappings from MAGICC6 to MAGICC7 variables. Note that this mapping is not one to one. For example, "HFC4310", "HFC43-10" and "HFC-43-10" in MAGICC6 both map to "HFC4310" in MAGICC7 but "HFC4310" in MAGICC7 maps back to "HFC4310". Note that HFC-245fa was mistakenly labelled as HFC-245ca in MAGICC6. In reality, they are not the same thing. However, the MAGICC6 labelling was merely a typo so the mapping between the two is one-to-one. Parameters ---------- inverse : bool If True, return the inverse mappings i.e. MAGICC7 to MAGICC6 mappings Returns ------- dict Dictionary of mappings """ # we generate the mapping dynamically, the first name in the list # is the one which will be used for inverse mappings magicc6_simple_mapping_vars = [ "KYOTO-CO2EQ", "CO2I", "CO2B", "CH4", "N2O", "BC", "OC", "SOx", "NOx", "NMVOC", "CO", "SF6", "NH3", "CF4", "C2F6", "HFC4310", "HFC43-10", "HFC-43-10", "HFC4310", "HFC134a", "HFC143a", "HFC227ea", "CCl4", "CH3CCl3", "HFC245fa", "Halon 1211", "Halon 1202", "Halon 1301", "Halon 2402", "Halon1211", "Halon1202", "Halon1301", "Halon2402", "CH3Br", "CH3Cl", "C6F14", ] magicc6_sometimes_hyphen_vars = [ "CFC-11", "CFC-12", "CFC-113", "CFC-114", "CFC-115", "HCFC-22", "HFC-23", "HFC-32", "HFC-125", "HFC-134a", "HFC-143a", "HCFC-141b", "HCFC-142b", "HFC-227ea", "HFC-245fa", ] magicc6_sometimes_hyphen_vars = [ v.replace("-", "") for v in magicc6_sometimes_hyphen_vars ] + magicc6_sometimes_hyphen_vars magicc6_sometimes_underscore_vars = [ "HFC43_10", "CFC_11", "CFC_12", "CFC_113", "CFC_114", "CFC_115", "HCFC_22", "HCFC_141b", "HCFC_142b", ] magicc6_sometimes_underscore_replacements = { v: v.replace("_", "") for v in magicc6_sometimes_underscore_vars } special_case_replacements = { "FossilCO2": "CO2I", "OtherCO2": "CO2B", "MCF": "CH3CCL3", "CARB_TET": "CCL4", "MHALOSUMCFC12EQ": "MHALOSUMCFC12EQ", # special case to avoid confusion with MCF } one_way_replacements = {"HFC-245ca": "HFC245FA", "HFC245ca": "HFC245FA"} all_possible_magicc6_vars = ( magicc6_simple_mapping_vars + magicc6_sometimes_hyphen_vars + magicc6_sometimes_underscore_vars + list(special_case_replacements.keys()) + list(one_way_replacements.keys()) ) replacements = {} for m6v in all_possible_magicc6_vars: if m6v in special_case_replacements: replacements[m6v] = special_case_replacements[m6v] elif ( m6v in magicc6_sometimes_underscore_vars and not inverse ): # underscores one way replacements[m6v] = magicc6_sometimes_underscore_replacements[m6v] elif (m6v in one_way_replacements) and not inverse: replacements[m6v] = one_way_replacements[m6v] else: m7v = m6v.replace("-", "").replace(" ", "").upper() # i.e. if we've already got a value for the inverse, we don't # want to overwrite it if (m7v in replacements.values()) and inverse: continue replacements[m6v] = m7v if inverse: return {v: k for k, v in replacements.items()} else: return replacements

python

def get_magicc6_to_magicc7_variable_mapping(inverse=False): """Get the mappings from MAGICC6 to MAGICC7 variables. Note that this mapping is not one to one. For example, "HFC4310", "HFC43-10" and "HFC-43-10" in MAGICC6 both map to "HFC4310" in MAGICC7 but "HFC4310" in MAGICC7 maps back to "HFC4310". Note that HFC-245fa was mistakenly labelled as HFC-245ca in MAGICC6. In reality, they are not the same thing. However, the MAGICC6 labelling was merely a typo so the mapping between the two is one-to-one. Parameters ---------- inverse : bool If True, return the inverse mappings i.e. MAGICC7 to MAGICC6 mappings Returns ------- dict Dictionary of mappings """ # we generate the mapping dynamically, the first name in the list # is the one which will be used for inverse mappings magicc6_simple_mapping_vars = [ "KYOTO-CO2EQ", "CO2I", "CO2B", "CH4", "N2O", "BC", "OC", "SOx", "NOx", "NMVOC", "CO", "SF6", "NH3", "CF4", "C2F6", "HFC4310", "HFC43-10", "HFC-43-10", "HFC4310", "HFC134a", "HFC143a", "HFC227ea", "CCl4", "CH3CCl3", "HFC245fa", "Halon 1211", "Halon 1202", "Halon 1301", "Halon 2402", "Halon1211", "Halon1202", "Halon1301", "Halon2402", "CH3Br", "CH3Cl", "C6F14", ] magicc6_sometimes_hyphen_vars = [ "CFC-11", "CFC-12", "CFC-113", "CFC-114", "CFC-115", "HCFC-22", "HFC-23", "HFC-32", "HFC-125", "HFC-134a", "HFC-143a", "HCFC-141b", "HCFC-142b", "HFC-227ea", "HFC-245fa", ] magicc6_sometimes_hyphen_vars = [ v.replace("-", "") for v in magicc6_sometimes_hyphen_vars ] + magicc6_sometimes_hyphen_vars magicc6_sometimes_underscore_vars = [ "HFC43_10", "CFC_11", "CFC_12", "CFC_113", "CFC_114", "CFC_115", "HCFC_22", "HCFC_141b", "HCFC_142b", ] magicc6_sometimes_underscore_replacements = { v: v.replace("_", "") for v in magicc6_sometimes_underscore_vars } special_case_replacements = { "FossilCO2": "CO2I", "OtherCO2": "CO2B", "MCF": "CH3CCL3", "CARB_TET": "CCL4", "MHALOSUMCFC12EQ": "MHALOSUMCFC12EQ", # special case to avoid confusion with MCF } one_way_replacements = {"HFC-245ca": "HFC245FA", "HFC245ca": "HFC245FA"} all_possible_magicc6_vars = ( magicc6_simple_mapping_vars + magicc6_sometimes_hyphen_vars + magicc6_sometimes_underscore_vars + list(special_case_replacements.keys()) + list(one_way_replacements.keys()) ) replacements = {} for m6v in all_possible_magicc6_vars: if m6v in special_case_replacements: replacements[m6v] = special_case_replacements[m6v] elif ( m6v in magicc6_sometimes_underscore_vars and not inverse ): # underscores one way replacements[m6v] = magicc6_sometimes_underscore_replacements[m6v] elif (m6v in one_way_replacements) and not inverse: replacements[m6v] = one_way_replacements[m6v] else: m7v = m6v.replace("-", "").replace(" ", "").upper() # i.e. if we've already got a value for the inverse, we don't # want to overwrite it if (m7v in replacements.values()) and inverse: continue replacements[m6v] = m7v if inverse: return {v: k for k, v in replacements.items()} else: return replacements

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Get the mappings from MAGICC6 to MAGICC7 variables. Note that this mapping is not one to one. For example, "HFC4310", "HFC43-10" and "HFC-43-10" in MAGICC6 both map to "HFC4310" in MAGICC7 but "HFC4310" in MAGICC7 maps back to "HFC4310". Note that HFC-245fa was mistakenly labelled as HFC-245ca in MAGICC6. In reality, they are not the same thing. However, the MAGICC6 labelling was merely a typo so the mapping between the two is one-to-one. Parameters ---------- inverse : bool If True, return the inverse mappings i.e. MAGICC7 to MAGICC6 mappings Returns ------- dict Dictionary of mappings

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brocade/pynos

pynos/versions/ver_7/ver_7_1_0/yang/brocade_fabric_service.py

brocade_fabric_service.show_fabric_trunk_info_output_show_trunk_list_trunk_list_groups_trunk_list_member_trunk_list_nbr_interface_type

def show_fabric_trunk_info_output_show_trunk_list_trunk_list_groups_trunk_list_member_trunk_list_nbr_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_fabric_trunk_info = ET.Element("show_fabric_trunk_info") config = show_fabric_trunk_info output = ET.SubElement(show_fabric_trunk_info, "output") show_trunk_list = ET.SubElement(output, "show-trunk-list") trunk_list_groups = ET.SubElement(show_trunk_list, "trunk-list-groups") trunk_list_member = ET.SubElement(trunk_list_groups, "trunk-list-member") trunk_list_nbr_interface_type = ET.SubElement(trunk_list_member, "trunk-list-nbr-interface-type") trunk_list_nbr_interface_type.text = kwargs.pop('trunk_list_nbr_interface_type') callback = kwargs.pop('callback', self._callback) return callback(config)

python

def show_fabric_trunk_info_output_show_trunk_list_trunk_list_groups_trunk_list_member_trunk_list_nbr_interface_type(self, **kwargs): """Auto Generated Code """ config = ET.Element("config") show_fabric_trunk_info = ET.Element("show_fabric_trunk_info") config = show_fabric_trunk_info output = ET.SubElement(show_fabric_trunk_info, "output") show_trunk_list = ET.SubElement(output, "show-trunk-list") trunk_list_groups = ET.SubElement(show_trunk_list, "trunk-list-groups") trunk_list_member = ET.SubElement(trunk_list_groups, "trunk-list-member") trunk_list_nbr_interface_type = ET.SubElement(trunk_list_member, "trunk-list-nbr-interface-type") trunk_list_nbr_interface_type.text = kwargs.pop('trunk_list_nbr_interface_type') callback = kwargs.pop('callback', self._callback) return callback(config)

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celery/django-celery

djcelery/compat.py

python_2_unicode_compatible

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python

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cloudboss/friend

friend/collections.py

select_dict

def select_dict(coll, key, value): """ Given an iterable of dictionaries, return the dictionaries where the values at a given key match the given value. If the value is an iterable of objects, the function will consider any to be a match. This is especially useful when calling REST APIs which return arrays of JSON objects. When such a response is converted to a Python list of dictionaries, it may be easily filtered using this function. :param iter coll: An iterable containing dictionaries :param obj key: A key to search in each dictionary :param value: A value or iterable of values to match :type value: obj or iter :returns: A list of dictionaries matching the query :rtype: list :Example: :: >>> dicts = [ ... {'hi': 'bye'}, ... {10: 2, 30: 4}, ... {'hi': 'hello', 'bye': 'goodbye'}, ... ] >>> select_dict(dicts, 'hi', 'bye') [{'hi': 'bye'}] >>> select_dict(dicts, 'hi', ('bye', 'hello')) [{'hi': 'bye'}, {'hi': 'hello', 'bye': 'goodbye'}] """ if getattr(value, '__iter__', None): iterable = value else: iterable = [value] return [v for v in coll if key in v and v[key] in iterable]

python

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project-ncl/pnc-cli

pnc_cli/common.py

get_entity

def get_entity(api, entity_id): """ Generic "getSpecific" call that calls get_specific with the given id :param api: api to call get_specific on :param id: id of the entity to retrieve :return: REST entity """ response = utils.checked_api_call(api, 'get_specific', id=entity_id) if response: return response.content return

python

def get_entity(api, entity_id): """ Generic "getSpecific" call that calls get_specific with the given id :param api: api to call get_specific on :param id: id of the entity to retrieve :return: REST entity """ response = utils.checked_api_call(api, 'get_specific', id=entity_id) if response: return response.content return

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jrmontag/STLDecompose

stldecompose/forecast_funcs.py

mean

def mean(data, n=3, **kwargs): """The mean forecast for the next point is the mean value of the previous ``n`` points in the series. Args: data (np.array): Observed data, presumed to be ordered in time. n (int): period over which to calculate the mean Returns: float: a single-valued forecast for the next value in the series. """ # don't start averaging until we've seen n points if len(data[-n:]) < n: forecast = np.nan else: # nb: we'll keep the forecast as a float forecast = np.mean(data[-n:]) return forecast

python

def mean(data, n=3, **kwargs): """The mean forecast for the next point is the mean value of the previous ``n`` points in the series. Args: data (np.array): Observed data, presumed to be ordered in time. n (int): period over which to calculate the mean Returns: float: a single-valued forecast for the next value in the series. """ # don't start averaging until we've seen n points if len(data[-n:]) < n: forecast = np.nan else: # nb: we'll keep the forecast as a float forecast = np.mean(data[-n:]) return forecast

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The mean forecast for the next point is the mean value of the previous ``n`` points in the series. Args: data (np.array): Observed data, presumed to be ordered in time. n (int): period over which to calculate the mean Returns: float: a single-valued forecast for the next value in the series.

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train

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pywbem/pywbem

pywbem/_statistics.py

OperationStatistic.stop_timer

def stop_timer(self, request_len, reply_len, server_time=None, exception=False): """ This is a low-level method is called by pywbem at the end of an operation. It completes the measurement for that operation by capturing the needed data, and updates the statistics data, if statistics is enabled for the connection. Parameters: request_len (:term:`integer`) Size of the HTTP body of the CIM-XML request message, in Bytes. reply_len (:term:`integer`) Size of the HTTP body of the CIM-XML response message, in Bytes. exception (:class:`py:bool`) Boolean that specifies whether an exception was raised while processing the operation. server_time (:class:`py:bool`) Time in seconds that the server optionally returns to the client in the HTTP response defining the time from when the server received the request to when it started sending the response. If `None`, there is no time from the server. Returns: float: The elapsed time for the operation that just ended, or `None` if the statistics container holding this object is not enabled. """ if not self.container.enabled: return None # stop the timer if self._start_time is None: raise RuntimeError('stop_timer() called without preceding ' 'start_timer()') dt = time.time() - self._start_time self._start_time = None self._count += 1 self._time_sum += dt self._request_len_sum += request_len self._reply_len_sum += reply_len if exception: self._exception_count += 1 if dt > self._time_max: self._time_max = dt if dt < self._time_min: self._time_min = dt if server_time: self._server_time_stored = True self._server_time_sum += server_time if dt > self._server_time_max: self._server_time_max = server_time if dt < self._server_time_min: self._server_time_min = server_time if request_len > self._request_len_max: self._request_len_max = request_len if request_len < self._request_len_min: self._request_len_min = request_len if reply_len > self._reply_len_max: self._reply_len_max = reply_len if reply_len < self._reply_len_min: self._reply_len_min = reply_len return dt

python

def stop_timer(self, request_len, reply_len, server_time=None, exception=False): """ This is a low-level method is called by pywbem at the end of an operation. It completes the measurement for that operation by capturing the needed data, and updates the statistics data, if statistics is enabled for the connection. Parameters: request_len (:term:`integer`) Size of the HTTP body of the CIM-XML request message, in Bytes. reply_len (:term:`integer`) Size of the HTTP body of the CIM-XML response message, in Bytes. exception (:class:`py:bool`) Boolean that specifies whether an exception was raised while processing the operation. server_time (:class:`py:bool`) Time in seconds that the server optionally returns to the client in the HTTP response defining the time from when the server received the request to when it started sending the response. If `None`, there is no time from the server. Returns: float: The elapsed time for the operation that just ended, or `None` if the statistics container holding this object is not enabled. """ if not self.container.enabled: return None # stop the timer if self._start_time is None: raise RuntimeError('stop_timer() called without preceding ' 'start_timer()') dt = time.time() - self._start_time self._start_time = None self._count += 1 self._time_sum += dt self._request_len_sum += request_len self._reply_len_sum += reply_len if exception: self._exception_count += 1 if dt > self._time_max: self._time_max = dt if dt < self._time_min: self._time_min = dt if server_time: self._server_time_stored = True self._server_time_sum += server_time if dt > self._server_time_max: self._server_time_max = server_time if dt < self._server_time_min: self._server_time_min = server_time if request_len > self._request_len_max: self._request_len_max = request_len if request_len < self._request_len_min: self._request_len_min = request_len if reply_len > self._reply_len_max: self._reply_len_max = reply_len if reply_len < self._reply_len_min: self._reply_len_min = reply_len return dt

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train

https://github.com/pywbem/pywbem/blob/e54ecb82c2211e289a268567443d60fdd489f1e4/pywbem/_statistics.py#L398-L470

tanghaibao/jcvi

jcvi/compara/quota.py

get_1D_overlap

def get_1D_overlap(eclusters, depth=1): """ Find blocks that are 1D overlapping, returns cliques of block ids that are in conflict """ overlap_set = set() active = set() ends = [] for i, (chr, left, right) in enumerate(eclusters): ends.append((chr, left, 0, i)) # 0/1 for left/right-ness ends.append((chr, right, 1, i)) ends.sort() chr_last = "" for chr, pos, left_right, i in ends: if chr != chr_last: active.clear() if left_right == 0: active.add(i) else: active.remove(i) if len(active) > depth: overlap_set.add(tuple(sorted(active))) chr_last = chr return overlap_set

python

def get_1D_overlap(eclusters, depth=1): """ Find blocks that are 1D overlapping, returns cliques of block ids that are in conflict """ overlap_set = set() active = set() ends = [] for i, (chr, left, right) in enumerate(eclusters): ends.append((chr, left, 0, i)) # 0/1 for left/right-ness ends.append((chr, right, 1, i)) ends.sort() chr_last = "" for chr, pos, left_right, i in ends: if chr != chr_last: active.clear() if left_right == 0: active.add(i) else: active.remove(i) if len(active) > depth: overlap_set.add(tuple(sorted(active))) chr_last = chr return overlap_set

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train

https://github.com/tanghaibao/jcvi/blob/d2e31a77b6ade7f41f3b321febc2b4744d1cdeca/jcvi/compara/quota.py#L33-L61

spyder-ide/spyder

spyder/plugins/plots/widgets/figurebrowser.py

FigureThumbnail.eventFilter

def eventFilter(self, widget, event): """ A filter that is used to send a signal when the figure canvas is clicked. """ if event.type() == QEvent.MouseButtonPress: if event.button() == Qt.LeftButton: self.sig_canvas_clicked.emit(self) return super(FigureThumbnail, self).eventFilter(widget, event)

python

def eventFilter(self, widget, event): """ A filter that is used to send a signal when the figure canvas is clicked. """ if event.type() == QEvent.MouseButtonPress: if event.button() == Qt.LeftButton: self.sig_canvas_clicked.emit(self) return super(FigureThumbnail, self).eventFilter(widget, event)

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train

https://github.com/spyder-ide/spyder/blob/f76836ce1b924bcc4efd3f74f2960d26a4e528e0/spyder/plugins/plots/widgets/figurebrowser.py#L809-L817

RudolfCardinal/pythonlib

cardinal_pythonlib/extract_text.py

convert_odt_to_text

def convert_odt_to_text(filename: str = None, blob: bytes = None, config: TextProcessingConfig = _DEFAULT_CONFIG) -> str: """ Converts an OpenOffice ODT file to text. Pass either a filename or a binary object. """ # We can't use exactly the same method as for DOCX files, using docx: # sometimes that works, but sometimes it falls over with: # KeyError: "There is no item named 'word/document.xml' in the archive" with get_filelikeobject(filename, blob) as fp: z = zipfile.ZipFile(fp) tree = ElementTree.fromstring(z.read('content.xml')) # ... may raise zipfile.BadZipfile textlist = [] # type: List[str] for element in tree.iter(): if element.text: textlist.append(element.text.strip()) return '\n\n'.join(textlist)

python

def convert_odt_to_text(filename: str = None, blob: bytes = None, config: TextProcessingConfig = _DEFAULT_CONFIG) -> str: """ Converts an OpenOffice ODT file to text. Pass either a filename or a binary object. """ # We can't use exactly the same method as for DOCX files, using docx: # sometimes that works, but sometimes it falls over with: # KeyError: "There is no item named 'word/document.xml' in the archive" with get_filelikeobject(filename, blob) as fp: z = zipfile.ZipFile(fp) tree = ElementTree.fromstring(z.read('content.xml')) # ... may raise zipfile.BadZipfile textlist = [] # type: List[str] for element in tree.iter(): if element.text: textlist.append(element.text.strip()) return '\n\n'.join(textlist)

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Converts an OpenOffice ODT file to text. Pass either a filename or a binary object.

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train

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hotdoc/hotdoc

hotdoc/extensions/c/clang/cindex.py

Type.element_count

def element_count(self): """Retrieve the number of elements in this type. Returns an int. If the Type is not an array or vector, this raises. """ result = conf.lib.clang_getNumElements(self) if result < 0: raise Exception('Type does not have elements.') return result

python

def element_count(self): """Retrieve the number of elements in this type. Returns an int. If the Type is not an array or vector, this raises. """ result = conf.lib.clang_getNumElements(self) if result < 0: raise Exception('Type does not have elements.') return result

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Retrieve the number of elements in this type. Returns an int. If the Type is not an array or vector, this raises.

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train

https://github.com/hotdoc/hotdoc/blob/1067cdc8482b585b364a38fb52ca5d904e486280/hotdoc/extensions/c/clang/cindex.py#L2026-L2037

ska-sa/katcp-python

katcp/server.py

MessageHandlerThread.stop

def stop(self, timeout=1.0): """Stop the handler thread (from another thread). Parameters ---------- timeout : float, optional Seconds to wait for server to have *started*. """ if timeout: self._running.wait(timeout) self._running.clear() # Make sure to wake the run thread. self._wake.set()

python

def stop(self, timeout=1.0): """Stop the handler thread (from another thread). Parameters ---------- timeout : float, optional Seconds to wait for server to have *started*. """ if timeout: self._running.wait(timeout) self._running.clear() # Make sure to wake the run thread. self._wake.set()

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Stop the handler thread (from another thread). Parameters ---------- timeout : float, optional Seconds to wait for server to have *started*.

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train

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pantsbuild/pants

src/python/pants/build_graph/target.py

Target.create_sources_field

def create_sources_field(self, sources, sources_rel_path, key_arg=None): """Factory method to create a SourcesField appropriate for the type of the sources object. Note that this method is called before the call to Target.__init__ so don't expect fields to be populated! :API: public :return: a payload field object representing the sources parameter :rtype: SourcesField """ if not sources: sources = FilesetWithSpec.empty(sources_rel_path) elif not isinstance(sources, FilesetWithSpec): key_arg_section = "'{}' to be ".format(key_arg) if key_arg else "" raise TargetDefinitionException(self, "Expected {}a glob, an address or a list, but was {}" .format(key_arg_section, type(sources))) return SourcesField(sources=sources)

python

def create_sources_field(self, sources, sources_rel_path, key_arg=None): """Factory method to create a SourcesField appropriate for the type of the sources object. Note that this method is called before the call to Target.__init__ so don't expect fields to be populated! :API: public :return: a payload field object representing the sources parameter :rtype: SourcesField """ if not sources: sources = FilesetWithSpec.empty(sources_rel_path) elif not isinstance(sources, FilesetWithSpec): key_arg_section = "'{}' to be ".format(key_arg) if key_arg else "" raise TargetDefinitionException(self, "Expected {}a glob, an address or a list, but was {}" .format(key_arg_section, type(sources))) return SourcesField(sources=sources)

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train

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AndrewAnnex/SpiceyPy

spiceypy/spiceypy.py

surfnm

def surfnm(a, b, c, point): """ This routine computes the outward-pointing, unit normal vector from a point on the surface of an ellipsoid. http://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/surfnm_c.html :param a: Length of the ellisoid semi-axis along the x-axis. :type a: float :param b: Length of the ellisoid semi-axis along the y-axis. :type b: float :param c: Length of the ellisoid semi-axis along the z-axis. :type c: float :param point: Body-fixed coordinates of a point on the ellipsoid' :type point: 3-Element Array of floats :return: Outward pointing unit normal to ellipsoid at point. :rtype: 3-Element Array of floats """ a = ctypes.c_double(a) b = ctypes.c_double(b) c = ctypes.c_double(c) point = stypes.toDoubleVector(point) normal = stypes.emptyDoubleVector(3) libspice.surfnm_c(a, b, c, point, normal) return stypes.cVectorToPython(normal)

python

def surfnm(a, b, c, point): """ This routine computes the outward-pointing, unit normal vector from a point on the surface of an ellipsoid. http://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/cspice/surfnm_c.html :param a: Length of the ellisoid semi-axis along the x-axis. :type a: float :param b: Length of the ellisoid semi-axis along the y-axis. :type b: float :param c: Length of the ellisoid semi-axis along the z-axis. :type c: float :param point: Body-fixed coordinates of a point on the ellipsoid' :type point: 3-Element Array of floats :return: Outward pointing unit normal to ellipsoid at point. :rtype: 3-Element Array of floats """ a = ctypes.c_double(a) b = ctypes.c_double(b) c = ctypes.c_double(c) point = stypes.toDoubleVector(point) normal = stypes.emptyDoubleVector(3) libspice.surfnm_c(a, b, c, point, normal) return stypes.cVectorToPython(normal)

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train

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tensorflow/tensor2tensor

tensor2tensor/layers/common_attention.py

masked_local_attention_2d

def masked_local_attention_2d(q, k, v, query_shape=(8, 16), memory_flange=(8, 16), name=None): """Strided block local self-attention. Each position in a query block can attend to all the generated queries in the query block, which are generated in raster scan, and positions that are generated to the left and top. The shapes are specified by query shape and memory flange. Note that if you're using this function, you do not need to right shift. Right shifting happens inside this function separately for each block. Args: q: a Tensor with shape [batch, heads, h, w, depth_k] k: a Tensor with shape [batch, heads, h, w, depth_k] v: a Tensor with shape [batch, heads, h, w, depth_v]. In the current implementation, depth_v must be equal to depth_k. query_shape: an tuple indicating the height and width of each query block. query_shape = block_shape memory_flange: an integer indicating how much to look in height and width from each query block. memory shape = query_shape + (block_flange[0], 2*block_flange[1]) name: an optional string Returns: a Tensor of shape [batch, heads, h, w, depth_v] """ with tf.variable_scope( name, default_name="local_masked_self_attention_2d", values=[q, k, v]): v_shape = common_layers.shape_list(v) # Pad query to ensure multiple of corresponding lengths. q = pad_to_multiple_2d(q, query_shape) # Set up query blocks. q_indices = gather_indices_2d(q, query_shape, query_shape) q_new = gather_blocks_2d(q, q_indices) # Set up key and value blocks. k_flange, k_center = get_memory_region(k, query_shape, memory_flange, q_indices) v_flange, v_center = get_memory_region(v, query_shape, memory_flange, q_indices) if k_flange is not None: k_new = tf.concat([k_flange, k_center], axis=3) v_new = tf.concat([v_flange, v_center], axis=3) else: k_new = k_center v_new = v_center # Set up the masks. query_elements = np.prod(query_shape) padding_mask = None if k_flange is not None: padding_mask = tf.expand_dims( embedding_to_padding(k_flange) * -1e9, axis=-2) padding_mask = tf.tile(padding_mask, [1, 1, 1, query_elements, 1]) center_attention_bias = attention_bias_lower_triangle( np.prod(query_elements)) center_attention_bias = tf.reshape( center_attention_bias, [1, 1, 1, query_elements, query_elements]) v_center_shape = common_layers.shape_list(v_center) center_attention_bias = tf.tile( center_attention_bias, [v_center_shape[0], v_center_shape[1], v_center_shape[2], 1, 1]) if padding_mask is not None: # Combine the mask for padding and visible region. attention_bias = tf.concat([padding_mask, center_attention_bias], axis=4) else: attention_bias = center_attention_bias output = dot_product_attention( q_new, k_new, v_new, attention_bias, dropout_rate=0., name="masked_local_2d", make_image_summary=False) # Put representations back into original shapes. padded_q_shape = common_layers.shape_list(q) output = scatter_blocks_2d(output, q_indices, padded_q_shape) # Remove the padding if introduced. output = tf.slice(output, [0, 0, 0, 0, 0], [-1, -1, v_shape[2], v_shape[3], -1]) return output

python

def masked_local_attention_2d(q, k, v, query_shape=(8, 16), memory_flange=(8, 16), name=None): """Strided block local self-attention. Each position in a query block can attend to all the generated queries in the query block, which are generated in raster scan, and positions that are generated to the left and top. The shapes are specified by query shape and memory flange. Note that if you're using this function, you do not need to right shift. Right shifting happens inside this function separately for each block. Args: q: a Tensor with shape [batch, heads, h, w, depth_k] k: a Tensor with shape [batch, heads, h, w, depth_k] v: a Tensor with shape [batch, heads, h, w, depth_v]. In the current implementation, depth_v must be equal to depth_k. query_shape: an tuple indicating the height and width of each query block. query_shape = block_shape memory_flange: an integer indicating how much to look in height and width from each query block. memory shape = query_shape + (block_flange[0], 2*block_flange[1]) name: an optional string Returns: a Tensor of shape [batch, heads, h, w, depth_v] """ with tf.variable_scope( name, default_name="local_masked_self_attention_2d", values=[q, k, v]): v_shape = common_layers.shape_list(v) # Pad query to ensure multiple of corresponding lengths. q = pad_to_multiple_2d(q, query_shape) # Set up query blocks. q_indices = gather_indices_2d(q, query_shape, query_shape) q_new = gather_blocks_2d(q, q_indices) # Set up key and value blocks. k_flange, k_center = get_memory_region(k, query_shape, memory_flange, q_indices) v_flange, v_center = get_memory_region(v, query_shape, memory_flange, q_indices) if k_flange is not None: k_new = tf.concat([k_flange, k_center], axis=3) v_new = tf.concat([v_flange, v_center], axis=3) else: k_new = k_center v_new = v_center # Set up the masks. query_elements = np.prod(query_shape) padding_mask = None if k_flange is not None: padding_mask = tf.expand_dims( embedding_to_padding(k_flange) * -1e9, axis=-2) padding_mask = tf.tile(padding_mask, [1, 1, 1, query_elements, 1]) center_attention_bias = attention_bias_lower_triangle( np.prod(query_elements)) center_attention_bias = tf.reshape( center_attention_bias, [1, 1, 1, query_elements, query_elements]) v_center_shape = common_layers.shape_list(v_center) center_attention_bias = tf.tile( center_attention_bias, [v_center_shape[0], v_center_shape[1], v_center_shape[2], 1, 1]) if padding_mask is not None: # Combine the mask for padding and visible region. attention_bias = tf.concat([padding_mask, center_attention_bias], axis=4) else: attention_bias = center_attention_bias output = dot_product_attention( q_new, k_new, v_new, attention_bias, dropout_rate=0., name="masked_local_2d", make_image_summary=False) # Put representations back into original shapes. padded_q_shape = common_layers.shape_list(q) output = scatter_blocks_2d(output, q_indices, padded_q_shape) # Remove the padding if introduced. output = tf.slice(output, [0, 0, 0, 0, 0], [-1, -1, v_shape[2], v_shape[3], -1]) return output

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['Strided', 'block', 'local', 'self', '-', 'attention', '.']

train

https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/layers/common_attention.py#L3760-L3850

ueg1990/faker-schema

faker_schema/schema_loader.py

load_json_from_file

def load_json_from_file(file_path): """Load schema from a JSON file""" try: with open(file_path) as f: json_data = json.load(f) except ValueError as e: raise ValueError('Given file {} is not a valid JSON file: {}'.format(file_path, e)) else: return json_data

python

def load_json_from_file(file_path): """Load schema from a JSON file""" try: with open(file_path) as f: json_data = json.load(f) except ValueError as e: raise ValueError('Given file {} is not a valid JSON file: {}'.format(file_path, e)) else: return json_data

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Load schema from a JSON file

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train

https://github.com/ueg1990/faker-schema/blob/419175eaf34baa43b306dd05c17362763948ec49/faker_schema/schema_loader.py#L4-L12

google/grr

grr/server/grr_response_server/gui/api_plugins/report_plugins/server_report_plugins.py

_ExtractHuntIdFromPath

def _ExtractHuntIdFromPath(entry, event): """Extracts a Hunt ID from an APIAuditEntry's HTTP request path.""" match = re.match(r".*hunt/([^/]+).*", entry.http_request_path) if match: event.urn = "aff4:/hunts/{}".format(match.group(1))

python

def _ExtractHuntIdFromPath(entry, event): """Extracts a Hunt ID from an APIAuditEntry's HTTP request path.""" match = re.match(r".*hunt/([^/]+).*", entry.http_request_path) if match: event.urn = "aff4:/hunts/{}".format(match.group(1))

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Extracts a Hunt ID from an APIAuditEntry's HTTP request path.

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tensorflow/mesh

mesh_tensorflow/ops.py

MeshImpl.slice_begin

def slice_begin(self, tensor_shape, pnum): """Begin position for the tensor slice for the given processor. Args: tensor_shape: Shape. pnum: int <= self.size. Returns: list of integers with length tensor_shape.ndims. """ tensor_layout = self.tensor_layout(tensor_shape) coordinates = pnum_to_processor_coordinates(self.shape, pnum) ret = [] for dim_size, mesh_axis in zip( tensor_shape.to_integer_list, tensor_layout.tensor_axis_to_mesh_axis): if mesh_axis is None: ret.append(0) else: ret.append( dim_size // self.shape[mesh_axis].size * coordinates[mesh_axis]) return ret

python

def slice_begin(self, tensor_shape, pnum): """Begin position for the tensor slice for the given processor. Args: tensor_shape: Shape. pnum: int <= self.size. Returns: list of integers with length tensor_shape.ndims. """ tensor_layout = self.tensor_layout(tensor_shape) coordinates = pnum_to_processor_coordinates(self.shape, pnum) ret = [] for dim_size, mesh_axis in zip( tensor_shape.to_integer_list, tensor_layout.tensor_axis_to_mesh_axis): if mesh_axis is None: ret.append(0) else: ret.append( dim_size // self.shape[mesh_axis].size * coordinates[mesh_axis]) return ret

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Begin position for the tensor slice for the given processor. Args: tensor_shape: Shape. pnum: int <= self.size. Returns: list of integers with length tensor_shape.ndims.

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train

https://github.com/tensorflow/mesh/blob/3921196e5e43302e820da0a87329f25d7e2a3016/mesh_tensorflow/ops.py#L859-L879

mottosso/be

be/util.py

ls

def ls(*topic, **kwargs): """List topic from external datastore Arguments: topic (str): One or more topics, e.g. ("project", "item", "task") root (str, optional): Absolute path to where projects reside, defaults to os.getcwd() backend (callable, optional): Function to call with absolute path as argument to retrieve children. Defaults to os.listdir absolute (bool, optional): Whether to return relative or absolute paths Example: >> ls() /projects/thedeal /projects/hulk >> ls("thedeal") /projects/thedeal/assets/ben /projects/thedeal/assets/table >> ls("thedeal", "ben") /projects/thedeal/assets/ben/rigging /projects/thedeal/assets/ben/modeling """ context = dump() root = kwargs.get("root") or context.get("cwd") or os.getcwd() backend = kwargs.get("backend", os.listdir) absolute = kwargs.get("absolute", True) content = { 0: "projects", 1: "inventory", 2: "template" }[min(2, len(topic))] # List projects if content == "projects": projects = lib.list_projects(root=root, backend=backend) if absolute: return map(lambda p: os.path.join(root, p), projects) else: return projects # List items if content == "inventory": project = topic[0] be = _extern.load(project, "be", root=root) inventory = _extern.load(project, "inventory", root=root) inventory = lib.invert_inventory(inventory) templates = _extern.load(project, "templates", root=root) if absolute: paths = list() for item, binding in inventory.iteritems(): template = templates.get(binding) index = len(topic) sliced = lib.slice(index, template) paths.append(sliced.format(*(topic + (item,)), **context)) return paths else: return inventory.keys() # List template if content == "template": project = topic[0] be = _extern.load(project, "be", root=root) templates = _extern.load(project, "templates", root=root) inventory = _extern.load(project, "inventory", root=root) return lib.list_template(root=root, topics=topic, templates=templates, inventory=inventory, be=be, absolute=absolute)

python

def ls(*topic, **kwargs): """List topic from external datastore Arguments: topic (str): One or more topics, e.g. ("project", "item", "task") root (str, optional): Absolute path to where projects reside, defaults to os.getcwd() backend (callable, optional): Function to call with absolute path as argument to retrieve children. Defaults to os.listdir absolute (bool, optional): Whether to return relative or absolute paths Example: >> ls() /projects/thedeal /projects/hulk >> ls("thedeal") /projects/thedeal/assets/ben /projects/thedeal/assets/table >> ls("thedeal", "ben") /projects/thedeal/assets/ben/rigging /projects/thedeal/assets/ben/modeling """ context = dump() root = kwargs.get("root") or context.get("cwd") or os.getcwd() backend = kwargs.get("backend", os.listdir) absolute = kwargs.get("absolute", True) content = { 0: "projects", 1: "inventory", 2: "template" }[min(2, len(topic))] # List projects if content == "projects": projects = lib.list_projects(root=root, backend=backend) if absolute: return map(lambda p: os.path.join(root, p), projects) else: return projects # List items if content == "inventory": project = topic[0] be = _extern.load(project, "be", root=root) inventory = _extern.load(project, "inventory", root=root) inventory = lib.invert_inventory(inventory) templates = _extern.load(project, "templates", root=root) if absolute: paths = list() for item, binding in inventory.iteritems(): template = templates.get(binding) index = len(topic) sliced = lib.slice(index, template) paths.append(sliced.format(*(topic + (item,)), **context)) return paths else: return inventory.keys() # List template if content == "template": project = topic[0] be = _extern.load(project, "be", root=root) templates = _extern.load(project, "templates", root=root) inventory = _extern.load(project, "inventory", root=root) return lib.list_template(root=root, topics=topic, templates=templates, inventory=inventory, be=be, absolute=absolute)

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List topic from external datastore Arguments: topic (str): One or more topics, e.g. ("project", "item", "task") root (str, optional): Absolute path to where projects reside, defaults to os.getcwd() backend (callable, optional): Function to call with absolute path as argument to retrieve children. Defaults to os.listdir absolute (bool, optional): Whether to return relative or absolute paths Example: >> ls() /projects/thedeal /projects/hulk >> ls("thedeal") /projects/thedeal/assets/ben /projects/thedeal/assets/table >> ls("thedeal", "ben") /projects/thedeal/assets/ben/rigging /projects/thedeal/assets/ben/modeling

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train

https://github.com/mottosso/be/blob/0f3d4f3597c71223f616d78c6d9b2c8dffcd8a71/be/util.py#L7-L82

openstack/pyghmi

pyghmi/ipmi/command.py

Command.set_channel_access

def set_channel_access(self, channel=None, access_update_mode='non_volatile', alerting=False, per_msg_auth=False, user_level_auth=False, access_mode='always', privilege_update_mode='non_volatile', privilege_level='administrator'): """Set channel access :param channel: number [1:7] :param access_update_mode: dont_change = don't set or change Channel Access non_volatile = set non-volatile Channel Access volatile = set volatile (active) setting of Channel Access :param alerting: PEF Alerting Enable/Disable True = enable PEF Alerting False = disable PEF Alerting on this channel (Alert Immediate command can still be used to generate alerts) :param per_msg_auth: Per-message Authentication True = enable False = disable Per-message Authentication. [Authentication required to activate any session on this channel, but authentication not used on subsequent packets for the session.] :param user_level_auth: User Level Authentication Enable/Disable. True = enable User Level Authentication. All User Level commands are to be authenticated per the Authentication Type that was negotiated when the session was activated. False = disable User Level Authentication. Allow User Level commands to be executed without being authenticated. If the option to disable User Level Command authentication is accepted, the BMC will accept packets with Authentication Type set to None if they contain user level commands. For outgoing packets, the BMC returns responses with the same Authentication Type that was used for the request. :param access_mode: Access Mode for IPMI messaging (PEF Alerting is enabled/disabled separately from IPMI messaging) disabled = disabled for IPMI messaging pre_boot = pre-boot only channel only available when system is in a powered down state or in BIOS prior to start of boot. always = channel always available regardless of system mode. BIOS typically dedicates the serial connection to the BMC. shared = same as always available, but BIOS typically leaves the serial port available for software use. :param privilege_update_mode: Channel Privilege Level Limit. This value sets the maximum privilege level that can be accepted on the specified channel. dont_change = don't set or change channel Privilege Level Limit non_volatile = non-volatile Privilege Level Limit according volatile = volatile setting of Privilege Level Limit :param privilege_level: Channel Privilege Level Limit * reserved = unused * callback * user * operator * administrator * proprietary = used by OEM """ if channel is None: channel = self.get_network_channel() data = [] data.append(channel & 0b00001111) access_update_modes = { 'dont_change': 0, 'non_volatile': 1, 'volatile': 2, # 'reserved': 3 } b = 0 b |= (access_update_modes[access_update_mode] << 6) & 0b11000000 if alerting: b |= 0b00100000 if per_msg_auth: b |= 0b00010000 if user_level_auth: b |= 0b00001000 access_modes = { 'disabled': 0, 'pre_boot': 1, 'always': 2, 'shared': 3, } b |= access_modes[access_mode] & 0b00000111 data.append(b) b = 0 privilege_update_modes = { 'dont_change': 0, 'non_volatile': 1, 'volatile': 2, # 'reserved': 3 } b |= (privilege_update_modes[privilege_update_mode] << 6) & 0b11000000 privilege_levels = { 'reserved': 0, 'callback': 1, 'user': 2, 'operator': 3, 'administrator': 4, 'proprietary': 5, # 'no_access': 0x0F, } b |= privilege_levels[privilege_level] & 0b00000111 data.append(b) response = self.raw_command(netfn=0x06, command=0x40, data=data) if 'error' in response: raise Exception(response['error']) return True

python

def set_channel_access(self, channel=None, access_update_mode='non_volatile', alerting=False, per_msg_auth=False, user_level_auth=False, access_mode='always', privilege_update_mode='non_volatile', privilege_level='administrator'): """Set channel access :param channel: number [1:7] :param access_update_mode: dont_change = don't set or change Channel Access non_volatile = set non-volatile Channel Access volatile = set volatile (active) setting of Channel Access :param alerting: PEF Alerting Enable/Disable True = enable PEF Alerting False = disable PEF Alerting on this channel (Alert Immediate command can still be used to generate alerts) :param per_msg_auth: Per-message Authentication True = enable False = disable Per-message Authentication. [Authentication required to activate any session on this channel, but authentication not used on subsequent packets for the session.] :param user_level_auth: User Level Authentication Enable/Disable. True = enable User Level Authentication. All User Level commands are to be authenticated per the Authentication Type that was negotiated when the session was activated. False = disable User Level Authentication. Allow User Level commands to be executed without being authenticated. If the option to disable User Level Command authentication is accepted, the BMC will accept packets with Authentication Type set to None if they contain user level commands. For outgoing packets, the BMC returns responses with the same Authentication Type that was used for the request. :param access_mode: Access Mode for IPMI messaging (PEF Alerting is enabled/disabled separately from IPMI messaging) disabled = disabled for IPMI messaging pre_boot = pre-boot only channel only available when system is in a powered down state or in BIOS prior to start of boot. always = channel always available regardless of system mode. BIOS typically dedicates the serial connection to the BMC. shared = same as always available, but BIOS typically leaves the serial port available for software use. :param privilege_update_mode: Channel Privilege Level Limit. This value sets the maximum privilege level that can be accepted on the specified channel. dont_change = don't set or change channel Privilege Level Limit non_volatile = non-volatile Privilege Level Limit according volatile = volatile setting of Privilege Level Limit :param privilege_level: Channel Privilege Level Limit * reserved = unused * callback * user * operator * administrator * proprietary = used by OEM """ if channel is None: channel = self.get_network_channel() data = [] data.append(channel & 0b00001111) access_update_modes = { 'dont_change': 0, 'non_volatile': 1, 'volatile': 2, # 'reserved': 3 } b = 0 b |= (access_update_modes[access_update_mode] << 6) & 0b11000000 if alerting: b |= 0b00100000 if per_msg_auth: b |= 0b00010000 if user_level_auth: b |= 0b00001000 access_modes = { 'disabled': 0, 'pre_boot': 1, 'always': 2, 'shared': 3, } b |= access_modes[access_mode] & 0b00000111 data.append(b) b = 0 privilege_update_modes = { 'dont_change': 0, 'non_volatile': 1, 'volatile': 2, # 'reserved': 3 } b |= (privilege_update_modes[privilege_update_mode] << 6) & 0b11000000 privilege_levels = { 'reserved': 0, 'callback': 1, 'user': 2, 'operator': 3, 'administrator': 4, 'proprietary': 5, # 'no_access': 0x0F, } b |= privilege_levels[privilege_level] & 0b00000111 data.append(b) response = self.raw_command(netfn=0x06, command=0x40, data=data) if 'error' in response: raise Exception(response['error']) return True

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Set channel access :param channel: number [1:7] :param access_update_mode: dont_change = don't set or change Channel Access non_volatile = set non-volatile Channel Access volatile = set volatile (active) setting of Channel Access :param alerting: PEF Alerting Enable/Disable True = enable PEF Alerting False = disable PEF Alerting on this channel (Alert Immediate command can still be used to generate alerts) :param per_msg_auth: Per-message Authentication True = enable False = disable Per-message Authentication. [Authentication required to activate any session on this channel, but authentication not used on subsequent packets for the session.] :param user_level_auth: User Level Authentication Enable/Disable. True = enable User Level Authentication. All User Level commands are to be authenticated per the Authentication Type that was negotiated when the session was activated. False = disable User Level Authentication. Allow User Level commands to be executed without being authenticated. If the option to disable User Level Command authentication is accepted, the BMC will accept packets with Authentication Type set to None if they contain user level commands. For outgoing packets, the BMC returns responses with the same Authentication Type that was used for the request. :param access_mode: Access Mode for IPMI messaging (PEF Alerting is enabled/disabled separately from IPMI messaging) disabled = disabled for IPMI messaging pre_boot = pre-boot only channel only available when system is in a powered down state or in BIOS prior to start of boot. always = channel always available regardless of system mode. BIOS typically dedicates the serial connection to the BMC. shared = same as always available, but BIOS typically leaves the serial port available for software use. :param privilege_update_mode: Channel Privilege Level Limit. This value sets the maximum privilege level that can be accepted on the specified channel. dont_change = don't set or change channel Privilege Level Limit non_volatile = non-volatile Privilege Level Limit according volatile = volatile setting of Privilege Level Limit :param privilege_level: Channel Privilege Level Limit * reserved = unused * callback * user * operator * administrator * proprietary = used by OEM

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nugget/python-insteonplm

insteonplm/tools.py

Commander.do_add_device_override

def do_add_device_override(self, args): """Add a device override to the IM. Usage: add_device_override address cat subcat [firmware] Arguments: address: Insteon address of the device to override cat: Device category subcat: Device subcategory firmware: Optional - Device firmware The device address can be written with our without the dots and in upper or lower case, for example: 1a2b3c or 1A.2B.3C. The category, subcategory and firmware numbers are written in hex format, for example: 0x01 0x1b Example: add_device_override 1a2b3c 0x02 0x1a """ params = args.split() addr = None cat = None subcat = None firmware = None error = None try: addr = Address(params[0]) cat = binascii.unhexlify(params[1][2:]) subcat = binascii.unhexlify(params[2][2:]) firmware = binascii.unhexlify(params[3][2:]) except IndexError: error = 'missing' except ValueError: error = 'value' if addr and cat and subcat: self.tools.add_device_override(addr, cat, subcat, firmware) else: if error == 'missing': _LOGGING.error('Device address, category and subcategory are ' 'required.') else: _LOGGING.error('Check the vales for address, category and ' 'subcategory.') self.do_help('add_device_override')

python

def do_add_device_override(self, args): """Add a device override to the IM. Usage: add_device_override address cat subcat [firmware] Arguments: address: Insteon address of the device to override cat: Device category subcat: Device subcategory firmware: Optional - Device firmware The device address can be written with our without the dots and in upper or lower case, for example: 1a2b3c or 1A.2B.3C. The category, subcategory and firmware numbers are written in hex format, for example: 0x01 0x1b Example: add_device_override 1a2b3c 0x02 0x1a """ params = args.split() addr = None cat = None subcat = None firmware = None error = None try: addr = Address(params[0]) cat = binascii.unhexlify(params[1][2:]) subcat = binascii.unhexlify(params[2][2:]) firmware = binascii.unhexlify(params[3][2:]) except IndexError: error = 'missing' except ValueError: error = 'value' if addr and cat and subcat: self.tools.add_device_override(addr, cat, subcat, firmware) else: if error == 'missing': _LOGGING.error('Device address, category and subcategory are ' 'required.') else: _LOGGING.error('Check the vales for address, category and ' 'subcategory.') self.do_help('add_device_override')

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saltstack/salt

salt/spm/__init__.py

SPMClient._traverse_repos

def _traverse_repos(self, callback, repo_name=None): ''' Traverse through all repo files and apply the functionality provided in the callback to them ''' repo_files = [] if os.path.exists(self.opts['spm_repos_config']): repo_files.append(self.opts['spm_repos_config']) for (dirpath, dirnames, filenames) in salt.utils.path.os_walk('{0}.d'.format(self.opts['spm_repos_config'])): for repo_file in filenames: if not repo_file.endswith('.repo'): continue repo_files.append(repo_file) for repo_file in repo_files: repo_path = '{0}.d/{1}'.format(self.opts['spm_repos_config'], repo_file) with salt.utils.files.fopen(repo_path) as rph: repo_data = salt.utils.yaml.safe_load(rph) for repo in repo_data: if repo_data[repo].get('enabled', True) is False: continue if repo_name is not None and repo != repo_name: continue callback(repo, repo_data[repo])

python

def _traverse_repos(self, callback, repo_name=None): ''' Traverse through all repo files and apply the functionality provided in the callback to them ''' repo_files = [] if os.path.exists(self.opts['spm_repos_config']): repo_files.append(self.opts['spm_repos_config']) for (dirpath, dirnames, filenames) in salt.utils.path.os_walk('{0}.d'.format(self.opts['spm_repos_config'])): for repo_file in filenames: if not repo_file.endswith('.repo'): continue repo_files.append(repo_file) for repo_file in repo_files: repo_path = '{0}.d/{1}'.format(self.opts['spm_repos_config'], repo_file) with salt.utils.files.fopen(repo_path) as rph: repo_data = salt.utils.yaml.safe_load(rph) for repo in repo_data: if repo_data[repo].get('enabled', True) is False: continue if repo_name is not None and repo != repo_name: continue callback(repo, repo_data[repo])

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striglia/pyramid_swagger

pyramid_swagger/tween.py

get_swagger_objects

def get_swagger_objects(settings, route_info, registry): """Returns appropriate swagger handler and swagger spec schema. Swagger Handler contains callables that isolate implementation differences in the tween to handle both Swagger 1.2 and Swagger 2.0. Exception is made when `settings.prefer_20_routes` are non-empty and ['1.2', '2.0'] both are present in available swagger versions. In this special scenario, '2.0' spec is chosen only for requests which are listed in the `prefer_20_routes`. This helps in incremental migration of routes from v1.2 to v2.0 by making moving to v2.0 opt-in. :rtype: (:class:`SwaggerHandler`, :class:`pyramid_swagger.model.SwaggerSchema` OR :class:`bravado_core.spec.Spec`) """ enabled_swagger_versions = get_swagger_versions(registry.settings) schema12 = registry.settings['pyramid_swagger.schema12'] schema20 = registry.settings['pyramid_swagger.schema20'] fallback_to_swagger12_route = ( SWAGGER_20 in enabled_swagger_versions and SWAGGER_12 in enabled_swagger_versions and settings.prefer_20_routes and route_info.get('route') and route_info['route'].name not in settings.prefer_20_routes ) if fallback_to_swagger12_route: return settings.swagger12_handler, schema12 if SWAGGER_20 in enabled_swagger_versions: return settings.swagger20_handler, schema20 if SWAGGER_12 in enabled_swagger_versions: return settings.swagger12_handler, schema12

python

def get_swagger_objects(settings, route_info, registry): """Returns appropriate swagger handler and swagger spec schema. Swagger Handler contains callables that isolate implementation differences in the tween to handle both Swagger 1.2 and Swagger 2.0. Exception is made when `settings.prefer_20_routes` are non-empty and ['1.2', '2.0'] both are present in available swagger versions. In this special scenario, '2.0' spec is chosen only for requests which are listed in the `prefer_20_routes`. This helps in incremental migration of routes from v1.2 to v2.0 by making moving to v2.0 opt-in. :rtype: (:class:`SwaggerHandler`, :class:`pyramid_swagger.model.SwaggerSchema` OR :class:`bravado_core.spec.Spec`) """ enabled_swagger_versions = get_swagger_versions(registry.settings) schema12 = registry.settings['pyramid_swagger.schema12'] schema20 = registry.settings['pyramid_swagger.schema20'] fallback_to_swagger12_route = ( SWAGGER_20 in enabled_swagger_versions and SWAGGER_12 in enabled_swagger_versions and settings.prefer_20_routes and route_info.get('route') and route_info['route'].name not in settings.prefer_20_routes ) if fallback_to_swagger12_route: return settings.swagger12_handler, schema12 if SWAGGER_20 in enabled_swagger_versions: return settings.swagger20_handler, schema20 if SWAGGER_12 in enabled_swagger_versions: return settings.swagger12_handler, schema12

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yero13/na3x

na3x/transformation/transformer.py

Transformation.perform

def perform(self, cfg): """ Performs transformation according to configuration :param cfg: transformation configuration """ self.__src = self._load(cfg[Transformation.__CFG_KEY_LOAD]) self.__transform(cfg[Transformation.__CFG_KEY_TRANSFORM]) self.__cleanup(cfg[Transformation.__CFG_KEY_CLEANUP]) self.__save(cfg[Transformation.__CFG_KEY_SAVE])

python

def perform(self, cfg): """ Performs transformation according to configuration :param cfg: transformation configuration """ self.__src = self._load(cfg[Transformation.__CFG_KEY_LOAD]) self.__transform(cfg[Transformation.__CFG_KEY_TRANSFORM]) self.__cleanup(cfg[Transformation.__CFG_KEY_CLEANUP]) self.__save(cfg[Transformation.__CFG_KEY_SAVE])

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dhylands/rshell

rshell/main.py

extra_info

def extra_info(port): """Collects the serial nunber and manufacturer into a string, if the fields are available.""" extra_items = [] if port.manufacturer: extra_items.append("vendor '{}'".format(port.manufacturer)) if port.serial_number: extra_items.append("serial '{}'".format(port.serial_number)) if port.interface: extra_items.append("intf '{}'".format(port.interface)) if extra_items: return ' with ' + ' '.join(extra_items) return ''

python

def extra_info(port): """Collects the serial nunber and manufacturer into a string, if the fields are available.""" extra_items = [] if port.manufacturer: extra_items.append("vendor '{}'".format(port.manufacturer)) if port.serial_number: extra_items.append("serial '{}'".format(port.serial_number)) if port.interface: extra_items.append("intf '{}'".format(port.interface)) if extra_items: return ' with ' + ' '.join(extra_items) return ''

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train

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mattmakai/underwear

underwear/run_underwear.py

colorize

def colorize(lead, num, color): """ Print 'lead' = 'num' in 'color' """ if num != 0 and ANSIBLE_COLOR and color is not None: return "%s%s%-15s" % (stringc(lead, color), stringc("=", color), stringc(str(num), color)) else: return "%s=%-4s" % (lead, str(num))

python

def colorize(lead, num, color): """ Print 'lead' = 'num' in 'color' """ if num != 0 and ANSIBLE_COLOR and color is not None: return "%s%s%-15s" % (stringc(lead, color), stringc("=", color), stringc(str(num), color)) else: return "%s=%-4s" % (lead, str(num))

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Print 'lead' = 'num' in 'color'

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train

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bartromgens/geojsoncontour

geojsoncontour/utilities/multipoly.py

angle

def angle(v1, v2): """Return the angle in radians between vectors 'v1' and 'v2'.""" v1_u = unit_vector(v1) v2_u = unit_vector(v2) return np.arccos(np.clip(np.dot(v1_u, v2_u), -1.0, 1.0))

python

def angle(v1, v2): """Return the angle in radians between vectors 'v1' and 'v2'.""" v1_u = unit_vector(v1) v2_u = unit_vector(v2) return np.arccos(np.clip(np.dot(v1_u, v2_u), -1.0, 1.0))

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Return the angle in radians between vectors 'v1' and 'v2'.

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train

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mikedh/trimesh

trimesh/triangles.py

points_to_barycentric

def points_to_barycentric(triangles, points, method='cramer'): """ Find the barycentric coordinates of points relative to triangles. The Cramer's rule solution implements: http://blackpawn.com/texts/pointinpoly The cross product solution implements: https://www.cs.ubc.ca/~heidrich/Papers/JGT.05.pdf Parameters ----------- triangles : (n, 3, 3) float Triangles vertices in space points : (n, 3) float Point in space associated with a triangle method : str Which method to compute the barycentric coordinates with: - 'cross': uses a method using cross products, roughly 2x slower but different numerical robustness properties - anything else: uses a cramer's rule solution Returns ----------- barycentric : (n, 3) float Barycentric coordinates of each point """ def method_cross(): n = np.cross(edge_vectors[:, 0], edge_vectors[:, 1]) denominator = util.diagonal_dot(n, n) barycentric = np.zeros((len(triangles), 3), dtype=np.float64) barycentric[:, 2] = util.diagonal_dot( np.cross(edge_vectors[:, 0], w), n) / denominator barycentric[:, 1] = util.diagonal_dot( np.cross(w, edge_vectors[:, 1]), n) / denominator barycentric[:, 0] = 1 - barycentric[:, 1] - barycentric[:, 2] return barycentric def method_cramer(): dot00 = util.diagonal_dot(edge_vectors[:, 0], edge_vectors[:, 0]) dot01 = util.diagonal_dot(edge_vectors[:, 0], edge_vectors[:, 1]) dot02 = util.diagonal_dot(edge_vectors[:, 0], w) dot11 = util.diagonal_dot(edge_vectors[:, 1], edge_vectors[:, 1]) dot12 = util.diagonal_dot(edge_vectors[:, 1], w) inverse_denominator = 1.0 / (dot00 * dot11 - dot01 * dot01) barycentric = np.zeros((len(triangles), 3), dtype=np.float64) barycentric[:, 2] = (dot00 * dot12 - dot01 * dot02) * inverse_denominator barycentric[:, 1] = (dot11 * dot02 - dot01 * dot12) * inverse_denominator barycentric[:, 0] = 1 - barycentric[:, 1] - barycentric[:, 2] return barycentric # establish that input triangles and points are sane triangles = np.asanyarray(triangles, dtype=np.float64) points = np.asanyarray(points, dtype=np.float64) if not util.is_shape(triangles, (-1, 3, 3)): raise ValueError('triangles shape incorrect') if not util.is_shape(points, (len(triangles), 3)): raise ValueError('triangles and points must correspond') edge_vectors = triangles[:, 1:] - triangles[:, :1] w = points - triangles[:, 0].reshape((-1, 3)) if method == 'cross': return method_cross() return method_cramer()

python

def points_to_barycentric(triangles, points, method='cramer'): """ Find the barycentric coordinates of points relative to triangles. The Cramer's rule solution implements: http://blackpawn.com/texts/pointinpoly The cross product solution implements: https://www.cs.ubc.ca/~heidrich/Papers/JGT.05.pdf Parameters ----------- triangles : (n, 3, 3) float Triangles vertices in space points : (n, 3) float Point in space associated with a triangle method : str Which method to compute the barycentric coordinates with: - 'cross': uses a method using cross products, roughly 2x slower but different numerical robustness properties - anything else: uses a cramer's rule solution Returns ----------- barycentric : (n, 3) float Barycentric coordinates of each point """ def method_cross(): n = np.cross(edge_vectors[:, 0], edge_vectors[:, 1]) denominator = util.diagonal_dot(n, n) barycentric = np.zeros((len(triangles), 3), dtype=np.float64) barycentric[:, 2] = util.diagonal_dot( np.cross(edge_vectors[:, 0], w), n) / denominator barycentric[:, 1] = util.diagonal_dot( np.cross(w, edge_vectors[:, 1]), n) / denominator barycentric[:, 0] = 1 - barycentric[:, 1] - barycentric[:, 2] return barycentric def method_cramer(): dot00 = util.diagonal_dot(edge_vectors[:, 0], edge_vectors[:, 0]) dot01 = util.diagonal_dot(edge_vectors[:, 0], edge_vectors[:, 1]) dot02 = util.diagonal_dot(edge_vectors[:, 0], w) dot11 = util.diagonal_dot(edge_vectors[:, 1], edge_vectors[:, 1]) dot12 = util.diagonal_dot(edge_vectors[:, 1], w) inverse_denominator = 1.0 / (dot00 * dot11 - dot01 * dot01) barycentric = np.zeros((len(triangles), 3), dtype=np.float64) barycentric[:, 2] = (dot00 * dot12 - dot01 * dot02) * inverse_denominator barycentric[:, 1] = (dot11 * dot02 - dot01 * dot12) * inverse_denominator barycentric[:, 0] = 1 - barycentric[:, 1] - barycentric[:, 2] return barycentric # establish that input triangles and points are sane triangles = np.asanyarray(triangles, dtype=np.float64) points = np.asanyarray(points, dtype=np.float64) if not util.is_shape(triangles, (-1, 3, 3)): raise ValueError('triangles shape incorrect') if not util.is_shape(points, (len(triangles), 3)): raise ValueError('triangles and points must correspond') edge_vectors = triangles[:, 1:] - triangles[:, :1] w = points - triangles[:, 0].reshape((-1, 3)) if method == 'cross': return method_cross() return method_cramer()

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train

https://github.com/mikedh/trimesh/blob/25e059bf6d4caa74f62ffd58ce4f61a90ee4e518/trimesh/triangles.py#L452-L525

andreikop/qutepart

qutepart/__init__.py

Qutepart.terminate

def terminate(self): """ Terminate Qutepart instance. This method MUST be called before application stop to avoid crashes and some other interesting effects Call it on close to free memory and stop background highlighting """ self.text = '' self._completer.terminate() if self._highlighter is not None: self._highlighter.terminate() if self._vim is not None: self._vim.terminate()

python

def terminate(self): """ Terminate Qutepart instance. This method MUST be called before application stop to avoid crashes and some other interesting effects Call it on close to free memory and stop background highlighting """ self.text = '' self._completer.terminate() if self._highlighter is not None: self._highlighter.terminate() if self._vim is not None: self._vim.terminate()

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Terminate Qutepart instance. This method MUST be called before application stop to avoid crashes and some other interesting effects Call it on close to free memory and stop background highlighting

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train

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Yipit/ejson

ejson/__init__.py

dumps

def dumps(data, escape=False, **kwargs): """A wrapper around `json.dumps` that can handle objects that json module is not aware. This function is aware of a list of custom serializers that can be registered by the API user, making it possible to convert any kind of object to types that the json library can handle. """ if 'sort_keys' not in kwargs: kwargs['sort_keys'] = True converted = json.dumps(data, default=_converter, **kwargs) if escape: # We're escaping the whole dumped string here cause there's no (easy) # way to hook into the native json library and change how they process # values like strings, None objects and some other "literal" stuff. # # Also, we're not escaping quotes here cause they're escaped by the # native json library already. So, we just escape basic html entities, # like <, > and &; return cgi.escape(converted) return converted

python

def dumps(data, escape=False, **kwargs): """A wrapper around `json.dumps` that can handle objects that json module is not aware. This function is aware of a list of custom serializers that can be registered by the API user, making it possible to convert any kind of object to types that the json library can handle. """ if 'sort_keys' not in kwargs: kwargs['sort_keys'] = True converted = json.dumps(data, default=_converter, **kwargs) if escape: # We're escaping the whole dumped string here cause there's no (easy) # way to hook into the native json library and change how they process # values like strings, None objects and some other "literal" stuff. # # Also, we're not escaping quotes here cause they're escaped by the # native json library already. So, we just escape basic html entities, # like <, > and &; return cgi.escape(converted) return converted

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train

https://github.com/Yipit/ejson/blob/6665703f1534923d1c30849e08339f0ff97d8230/ejson/__init__.py#L49-L70

rackerlabs/rackspace-python-neutronclient

neutronclient/v2_0/client.py

Client.list_ext

def list_ext(self, collection, path, retrieve_all, **_params): """Client extension hook for list.""" return self.list(collection, path, retrieve_all, **_params)

python

def list_ext(self, collection, path, retrieve_all, **_params): """Client extension hook for list.""" return self.list(collection, path, retrieve_all, **_params)

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train

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materialsproject/pymatgen

pymatgen/io/abinit/qadapters.py

MpiRunner.string_to_run

def string_to_run(self, qad, executable, stdin=None, stdout=None, stderr=None, exec_args=None): """ Build and return a string with the command required to launch `executable` with the qadapter `qad`. Args qad: Qadapter instance. executable (str): Executable name or path stdin (str): Name of the file to be used as standard input. None means no redirection. stdout (str): Name of the file to be used as standard output. None means no redirection. stderr (str): Name of the file to be used as standard error. None means no redirection. exec_args: Optional list of strings with options passed to `executable`. Return: String with command to execute. """ stdin = "< " + stdin if stdin is not None else "" stdout = "> " + stdout if stdout is not None else "" stderr = "2> " + stderr if stderr is not None else "" if exec_args: executable = executable + " " + " ".join(list_strings(exec_args)) basename = os.path.basename(self.name) if basename in ["mpirun", "mpiexec", "srun"]: if self.type is None: # $MPIRUN -n $MPI_PROCS $EXECUTABLE < $STDIN > $STDOUT 2> $STDERR num_opt = "-n " + str(qad.mpi_procs) cmd = " ".join([self.name, self.options, num_opt, executable, stdin, stdout, stderr]) else: raise NotImplementedError("type %s is not supported!" % self.type) elif basename == "runjob": #runjob --ranks-per-node 2 --exp-env OMP_NUM_THREADS --exe $ABINIT < $STDIN > $STDOUT 2> $STDERR #runjob -n 2 --exp-env=OMP_NUM_THREADS --exe $ABINIT < $STDIN > $STDOUT 2> $STDERR # exe must be absolute path or relative to cwd. bg_size, rpn = qad.bgsize_rankspernode() #num_opt = "-n " + str(qad.mpi_procs) num_opt = "--ranks-per-node " + str(rpn) cmd = " ".join([self.name, self.options, num_opt, "--exp-env OMP_NUM_THREADS", "--exe `which " + executable + "` ", stdin, stdout, stderr]) else: if qad.mpi_procs != 1: raise ValueError("Cannot use mpi_procs > when mpi_runner basename=%s" % basename) cmd = " ".join([executable, stdin, stdout, stderr]) return cmd

python

def string_to_run(self, qad, executable, stdin=None, stdout=None, stderr=None, exec_args=None): """ Build and return a string with the command required to launch `executable` with the qadapter `qad`. Args qad: Qadapter instance. executable (str): Executable name or path stdin (str): Name of the file to be used as standard input. None means no redirection. stdout (str): Name of the file to be used as standard output. None means no redirection. stderr (str): Name of the file to be used as standard error. None means no redirection. exec_args: Optional list of strings with options passed to `executable`. Return: String with command to execute. """ stdin = "< " + stdin if stdin is not None else "" stdout = "> " + stdout if stdout is not None else "" stderr = "2> " + stderr if stderr is not None else "" if exec_args: executable = executable + " " + " ".join(list_strings(exec_args)) basename = os.path.basename(self.name) if basename in ["mpirun", "mpiexec", "srun"]: if self.type is None: # $MPIRUN -n $MPI_PROCS $EXECUTABLE < $STDIN > $STDOUT 2> $STDERR num_opt = "-n " + str(qad.mpi_procs) cmd = " ".join([self.name, self.options, num_opt, executable, stdin, stdout, stderr]) else: raise NotImplementedError("type %s is not supported!" % self.type) elif basename == "runjob": #runjob --ranks-per-node 2 --exp-env OMP_NUM_THREADS --exe $ABINIT < $STDIN > $STDOUT 2> $STDERR #runjob -n 2 --exp-env=OMP_NUM_THREADS --exe $ABINIT < $STDIN > $STDOUT 2> $STDERR # exe must be absolute path or relative to cwd. bg_size, rpn = qad.bgsize_rankspernode() #num_opt = "-n " + str(qad.mpi_procs) num_opt = "--ranks-per-node " + str(rpn) cmd = " ".join([self.name, self.options, num_opt, "--exp-env OMP_NUM_THREADS", "--exe `which " + executable + "` ", stdin, stdout, stderr]) else: if qad.mpi_procs != 1: raise ValueError("Cannot use mpi_procs > when mpi_runner basename=%s" % basename) cmd = " ".join([executable, stdin, stdout, stderr]) return cmd

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train

https://github.com/materialsproject/pymatgen/blob/4ca558cf72f8d5f8a1f21dfdfc0181a971c186da/pymatgen/io/abinit/qadapters.py#L83-L128

O365/python-o365

O365/drive.py

DriveItemPermission.update_roles

def update_roles(self, roles='view'): """ Updates the roles of this permission :return: Success / Failure :rtype: bool """ if not self.object_id: return False url = self.build_url(self._endpoints.get('permission').format( driveitem_id=self.driveitem_id, id=self.object_id)) if roles in {'view', 'read'}: data = {'roles': ['read']} elif roles == {'edit', 'write'}: data = {'roles': ['write']} else: raise ValueError('"{}" is not a valid share_type'.format(roles)) response = self.con.patch(url, data=data) if not response: return False self.roles = data.get('roles', []) return True

python

def update_roles(self, roles='view'): """ Updates the roles of this permission :return: Success / Failure :rtype: bool """ if not self.object_id: return False url = self.build_url(self._endpoints.get('permission').format( driveitem_id=self.driveitem_id, id=self.object_id)) if roles in {'view', 'read'}: data = {'roles': ['read']} elif roles == {'edit', 'write'}: data = {'roles': ['write']} else: raise ValueError('"{}" is not a valid share_type'.format(roles)) response = self.con.patch(url, data=data) if not response: return False self.roles = data.get('roles', []) return True

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Updates the roles of this permission :return: Success / Failure :rtype: bool

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train

https://github.com/O365/python-o365/blob/02a71cf3775cc6a3c042e003365d6a07c8c75a73/O365/drive.py#L357-L381

bokeh/bokeh

bokeh/driving.py

bounce

def bounce(sequence): ''' Return a driver function that can advance a "bounced" sequence of values. .. code-block:: none seq = [0, 1, 2, 3] # bounce(seq) => [0, 1, 2, 3, 3, 2, 1, 0, 0, 1, 2, ...] Args: sequence (seq) : a sequence of values for the driver to bounce ''' N = len(sequence) def f(i): div, mod = divmod(i, N) if div % 2 == 0: return sequence[mod] else: return sequence[N-mod-1] return partial(force, sequence=_advance(f))

python

def bounce(sequence): ''' Return a driver function that can advance a "bounced" sequence of values. .. code-block:: none seq = [0, 1, 2, 3] # bounce(seq) => [0, 1, 2, 3, 3, 2, 1, 0, 0, 1, 2, ...] Args: sequence (seq) : a sequence of values for the driver to bounce ''' N = len(sequence) def f(i): div, mod = divmod(i, N) if div % 2 == 0: return sequence[mod] else: return sequence[N-mod-1] return partial(force, sequence=_advance(f))

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train

https://github.com/bokeh/bokeh/blob/dc8cf49e4e4302fd38537ad089ece81fbcca4737/bokeh/driving.py#L73-L94

Robpol86/libnl

libnl/genl/ctrl.py

genl_ctrl_grp_by_name

def genl_ctrl_grp_by_name(family, grp_name): """https://github.com/thom311/libnl/blob/libnl3_2_25/lib/genl/ctrl.c#L446. Positional arguments: family -- genl_family class instance. grp_name -- bytes. Returns: group ID or negative error code. """ for grp in nl_list_for_each_entry(genl_family_grp(), family.gf_mc_grps, 'list_'): if grp.name == grp_name: return grp.id_ return -NLE_OBJ_NOTFOUND

python

def genl_ctrl_grp_by_name(family, grp_name): """https://github.com/thom311/libnl/blob/libnl3_2_25/lib/genl/ctrl.c#L446. Positional arguments: family -- genl_family class instance. grp_name -- bytes. Returns: group ID or negative error code. """ for grp in nl_list_for_each_entry(genl_family_grp(), family.gf_mc_grps, 'list_'): if grp.name == grp_name: return grp.id_ return -NLE_OBJ_NOTFOUND

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https://github.com/thom311/libnl/blob/libnl3_2_25/lib/genl/ctrl.c#L446. Positional arguments: family -- genl_family class instance. grp_name -- bytes. Returns: group ID or negative error code.

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train

https://github.com/Robpol86/libnl/blob/274e9fdaa39822d06ef70b799ed4a95937a4d923/libnl/genl/ctrl.py#L211-L224

jmbhughes/suvi-trainer

suvitrainer/gui.py

App.make_classify_tab

def make_classify_tab(self): """ initial set up of classification tab""" self.pick_frame = tk.Frame(self.tab_classify) self.pick_frame2 = tk.Frame(self.tab_classify) self.solar_class_var = tk.IntVar() self.solar_class_var.set(0) # initialize to unlabeled buttonnum = 0 frame = [self.pick_frame, self.pick_frame2] for text, value in self.config.solar_classes: b = tk.Radiobutton(frame[buttonnum % 2], text=text, variable=self.solar_class_var, value=value, background=self.config.solar_colors[text], indicatoron=0, width=50, height=2, command=self.change_class) b.pack(fill=tk.BOTH, expand=1) buttonnum += 1 self.pick_frame.grid(row=0, column=0, rowspan=5, sticky=tk.W + tk.E + tk.N + tk.S) self.pick_frame2.grid(row=0, column=1, rowspan=5, sticky=tk.W + tk.E + tk.N + tk.S) undobutton = tk.Button(master=self.tab_classify, text="Undo", command=self.undobutton_action) undobutton.grid(row=6, column=0, columnspan=2, sticky=tk.W + tk.E)

python

def make_classify_tab(self): """ initial set up of classification tab""" self.pick_frame = tk.Frame(self.tab_classify) self.pick_frame2 = tk.Frame(self.tab_classify) self.solar_class_var = tk.IntVar() self.solar_class_var.set(0) # initialize to unlabeled buttonnum = 0 frame = [self.pick_frame, self.pick_frame2] for text, value in self.config.solar_classes: b = tk.Radiobutton(frame[buttonnum % 2], text=text, variable=self.solar_class_var, value=value, background=self.config.solar_colors[text], indicatoron=0, width=50, height=2, command=self.change_class) b.pack(fill=tk.BOTH, expand=1) buttonnum += 1 self.pick_frame.grid(row=0, column=0, rowspan=5, sticky=tk.W + tk.E + tk.N + tk.S) self.pick_frame2.grid(row=0, column=1, rowspan=5, sticky=tk.W + tk.E + tk.N + tk.S) undobutton = tk.Button(master=self.tab_classify, text="Undo", command=self.undobutton_action) undobutton.grid(row=6, column=0, columnspan=2, sticky=tk.W + tk.E)

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train

https://github.com/jmbhughes/suvi-trainer/blob/3d89894a4a037286221974c7eb5634d229b4f5d4/suvitrainer/gui.py#L531-L554

Erotemic/utool

utool/util_dev.py

autopep8_diff

def autopep8_diff(fpath): r""" Args: fpath (str): file path string CommandLine: python -m utool.util_dev --test-autopep8_diff --fpath ingest_data.py Example: >>> # DISABLE_DOCTEST >>> from utool.util_dev import * # NOQA >>> fpath = ut.get_argval('--fpath', type_=str, default='ingest_data.py') >>> result = autopep8_diff(fpath) >>> print(result) """ import utool as ut args = ('autopep8', fpath, '--diff') res = ut.cmd(args, verbose=False) out, err, ret = res ut.print_difftext(out)

python

def autopep8_diff(fpath): r""" Args: fpath (str): file path string CommandLine: python -m utool.util_dev --test-autopep8_diff --fpath ingest_data.py Example: >>> # DISABLE_DOCTEST >>> from utool.util_dev import * # NOQA >>> fpath = ut.get_argval('--fpath', type_=str, default='ingest_data.py') >>> result = autopep8_diff(fpath) >>> print(result) """ import utool as ut args = ('autopep8', fpath, '--diff') res = ut.cmd(args, verbose=False) out, err, ret = res ut.print_difftext(out)

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r""" Args: fpath (str): file path string CommandLine: python -m utool.util_dev --test-autopep8_diff --fpath ingest_data.py Example: >>> # DISABLE_DOCTEST >>> from utool.util_dev import * # NOQA >>> fpath = ut.get_argval('--fpath', type_=str, default='ingest_data.py') >>> result = autopep8_diff(fpath) >>> print(result)

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train

https://github.com/Erotemic/utool/blob/3b27e1f4e6e6fb23cd8744af7b7195b57d99e03a/utool/util_dev.py#L2209-L2228

geertj/gruvi

lib/gruvi/stream.py

Stream.wrap

def wrap(self, encoding, **textio_args): """Return a :class:`io.TextIOWrapper` that wraps the stream. The wrapper provides text IO on top of the byte stream, using the specified *encoding*. The *textio_args* keyword arguments are additional keyword arguments passed to the :class:`~io.TextIOWrapper` constructor. Unless another buffering scheme is specified, the *write_through* option is enabled. """ # By default we want write_through behavior, unless the user specifies # something else. if 'line_buffering' not in textio_args and 'write_through' not in textio_args: textio_args['write_through'] = True return compat.TextIOWrapper(self, encoding, **textio_args)

python

def wrap(self, encoding, **textio_args): """Return a :class:`io.TextIOWrapper` that wraps the stream. The wrapper provides text IO on top of the byte stream, using the specified *encoding*. The *textio_args* keyword arguments are additional keyword arguments passed to the :class:`~io.TextIOWrapper` constructor. Unless another buffering scheme is specified, the *write_through* option is enabled. """ # By default we want write_through behavior, unless the user specifies # something else. if 'line_buffering' not in textio_args and 'write_through' not in textio_args: textio_args['write_through'] = True return compat.TextIOWrapper(self, encoding, **textio_args)

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train

https://github.com/geertj/gruvi/blob/1d77ca439600b6ea7a19aa1ee85dca0f3be3f3f8/lib/gruvi/stream.py#L177-L190

redhat-openstack/python-tripleo-helper

tripleohelper/server.py

Server.yum_update

def yum_update(self, allow_reboot=False): """Do a yum update on the system. :param allow_reboot: If True and if a new kernel has been installed, the system will be rebooted """ self.run('yum clean all') self.run('test -f /usr/bin/subscription-manager && subscription-manager repos --list-enabled', ignore_error=True) self.run('yum repolist') self.run('yum update -y --quiet', retry=3) # reboot if a new initrd has been generated since the boot if allow_reboot: self.run('grubby --set-default $(ls /boot/vmlinuz-*.x86_64|tail -1)') default_kernel = self.run('grubby --default-kernel')[0].rstrip() cur_kernel = self.run('uname -r')[0].rstrip() if cur_kernel not in default_kernel: self.run('reboot', ignore_error=True) self.ssh_pool.stop_all()

python

def yum_update(self, allow_reboot=False): """Do a yum update on the system. :param allow_reboot: If True and if a new kernel has been installed, the system will be rebooted """ self.run('yum clean all') self.run('test -f /usr/bin/subscription-manager && subscription-manager repos --list-enabled', ignore_error=True) self.run('yum repolist') self.run('yum update -y --quiet', retry=3) # reboot if a new initrd has been generated since the boot if allow_reboot: self.run('grubby --set-default $(ls /boot/vmlinuz-*.x86_64|tail -1)') default_kernel = self.run('grubby --default-kernel')[0].rstrip() cur_kernel = self.run('uname -r')[0].rstrip() if cur_kernel not in default_kernel: self.run('reboot', ignore_error=True) self.ssh_pool.stop_all()

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train

https://github.com/redhat-openstack/python-tripleo-helper/blob/bfa165538335edb1088170c7a92f097167225c81/tripleohelper/server.py#L242-L260

bcbio/bcbio-nextgen

bcbio/structural/titancna.py

_run_titancna

def _run_titancna(cn_file, het_file, ploidy, num_clusters, work_dir, data): """Run titanCNA wrapper script on given ploidy and clusters. """ sample = dd.get_sample_name(data) cores = dd.get_num_cores(data) export_cmd = utils.get_R_exports() ploidy_dir = utils.safe_makedir(os.path.join(work_dir, "run_ploidy%s" % ploidy)) cluster_dir = "%s_cluster%02d" % (sample, num_clusters) out_dir = os.path.join(ploidy_dir, cluster_dir) if not utils.file_uptodate(out_dir + ".titan.txt", cn_file): with tx_tmpdir(data) as tmp_dir: with utils.chdir(tmp_dir): cmd = ("{export_cmd} && titanCNA.R --id {sample} --hetFile {het_file} --cnFile {cn_file} " "--numClusters {num_clusters} --ploidy {ploidy} --numCores {cores} --outDir {tmp_dir} " "--libdir None") chroms = ["'%s'" % c.name.replace("chr", "") for c in ref.file_contigs(dd.get_ref_file(data)) if chromhacks.is_autosomal_or_x(c.name)] if "'X'" not in chroms: chroms += ["'X'"] # Use UCSC style naming for human builds to support BSgenome genome_build = ("hg19" if dd.get_genome_build(data) in ["GRCh37", "hg19"] else dd.get_genome_build(data)) cmd += """ --chrs "c(%s)" """ % ",".join(chroms) cmd += " --genomeBuild {genome_build}" if data["genome_build"] in ("hg19", "hg38"): cmd += " --genomeStyle UCSC" if data["genome_build"] in ["hg38"]: data_dir = os.path.normpath(os.path.join( os.path.dirname(os.path.realpath(os.path.join( os.path.dirname(utils.Rscript_cmd()), "titanCNA.R"))), os.pardir, os.pardir, "data")) cytoband_file = os.path.join(data_dir, "cytoBand_hg38.txt") assert os.path.exists(cytoband_file), cytoband_file cmd += " --cytobandFile %s" % cytoband_file # TitanCNA's model is influenced by the variance in read coverage data # and data type: set reasonable defaults for non-WGS runs # (see https://github.com/gavinha/TitanCNA/tree/master/scripts/R_scripts) if dd.get_coverage_interval(data) != "genome": cmd += " --alphaK=2500 --alphaKHigh=2500" do.run(cmd.format(**locals()), "TitanCNA CNV detection: ploidy %s, cluster %s" % (ploidy, num_clusters)) for fname in glob.glob(os.path.join(tmp_dir, cluster_dir + "*")): shutil.move(fname, ploidy_dir) if os.path.exists(os.path.join(tmp_dir, "Rplots.pdf")): shutil.move(os.path.join(tmp_dir, "Rplots.pdf"), os.path.join(ploidy_dir, "%s.Rplots.pdf" % cluster_dir)) return ploidy_dir

python

def _run_titancna(cn_file, het_file, ploidy, num_clusters, work_dir, data): """Run titanCNA wrapper script on given ploidy and clusters. """ sample = dd.get_sample_name(data) cores = dd.get_num_cores(data) export_cmd = utils.get_R_exports() ploidy_dir = utils.safe_makedir(os.path.join(work_dir, "run_ploidy%s" % ploidy)) cluster_dir = "%s_cluster%02d" % (sample, num_clusters) out_dir = os.path.join(ploidy_dir, cluster_dir) if not utils.file_uptodate(out_dir + ".titan.txt", cn_file): with tx_tmpdir(data) as tmp_dir: with utils.chdir(tmp_dir): cmd = ("{export_cmd} && titanCNA.R --id {sample} --hetFile {het_file} --cnFile {cn_file} " "--numClusters {num_clusters} --ploidy {ploidy} --numCores {cores} --outDir {tmp_dir} " "--libdir None") chroms = ["'%s'" % c.name.replace("chr", "") for c in ref.file_contigs(dd.get_ref_file(data)) if chromhacks.is_autosomal_or_x(c.name)] if "'X'" not in chroms: chroms += ["'X'"] # Use UCSC style naming for human builds to support BSgenome genome_build = ("hg19" if dd.get_genome_build(data) in ["GRCh37", "hg19"] else dd.get_genome_build(data)) cmd += """ --chrs "c(%s)" """ % ",".join(chroms) cmd += " --genomeBuild {genome_build}" if data["genome_build"] in ("hg19", "hg38"): cmd += " --genomeStyle UCSC" if data["genome_build"] in ["hg38"]: data_dir = os.path.normpath(os.path.join( os.path.dirname(os.path.realpath(os.path.join( os.path.dirname(utils.Rscript_cmd()), "titanCNA.R"))), os.pardir, os.pardir, "data")) cytoband_file = os.path.join(data_dir, "cytoBand_hg38.txt") assert os.path.exists(cytoband_file), cytoband_file cmd += " --cytobandFile %s" % cytoband_file # TitanCNA's model is influenced by the variance in read coverage data # and data type: set reasonable defaults for non-WGS runs # (see https://github.com/gavinha/TitanCNA/tree/master/scripts/R_scripts) if dd.get_coverage_interval(data) != "genome": cmd += " --alphaK=2500 --alphaKHigh=2500" do.run(cmd.format(**locals()), "TitanCNA CNV detection: ploidy %s, cluster %s" % (ploidy, num_clusters)) for fname in glob.glob(os.path.join(tmp_dir, cluster_dir + "*")): shutil.move(fname, ploidy_dir) if os.path.exists(os.path.join(tmp_dir, "Rplots.pdf")): shutil.move(os.path.join(tmp_dir, "Rplots.pdf"), os.path.join(ploidy_dir, "%s.Rplots.pdf" % cluster_dir)) return ploidy_dir

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train

https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/structural/titancna.py#L97-L143

Erotemic/utool

utool/util_project.py

ensure_user_profile

def ensure_user_profile(user_profile=None): r""" Args: user_profile (UserProfile): (default = None) Returns: UserProfile: user_profile CommandLine: python -m utool.util_project --exec-ensure_user_profile --show Example: >>> # DISABLE_DOCTEST >>> from utool.util_project import * # NOQA >>> import utool as ut >>> user_profile = None >>> user_profile = ensure_user_profile(user_profile) >>> result = ('user_profile = %s' % (ut.repr2(user_profile),)) >>> print(ut.repr3(user_profile.project_dpaths)) >>> print(result) """ global __GLOBAL_PROFILE__ if __GLOBAL_PROFILE__ is None: import utool as ut if ut.is_developer(): __GLOBAL_PROFILE__ = ibeis_user_profile() else: __GLOBAL_PROFILE__ = UserProfile('default') if user_profile is None: user_profile = __GLOBAL_PROFILE__ return user_profile

python

def ensure_user_profile(user_profile=None): r""" Args: user_profile (UserProfile): (default = None) Returns: UserProfile: user_profile CommandLine: python -m utool.util_project --exec-ensure_user_profile --show Example: >>> # DISABLE_DOCTEST >>> from utool.util_project import * # NOQA >>> import utool as ut >>> user_profile = None >>> user_profile = ensure_user_profile(user_profile) >>> result = ('user_profile = %s' % (ut.repr2(user_profile),)) >>> print(ut.repr3(user_profile.project_dpaths)) >>> print(result) """ global __GLOBAL_PROFILE__ if __GLOBAL_PROFILE__ is None: import utool as ut if ut.is_developer(): __GLOBAL_PROFILE__ = ibeis_user_profile() else: __GLOBAL_PROFILE__ = UserProfile('default') if user_profile is None: user_profile = __GLOBAL_PROFILE__ return user_profile

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r""" Args: user_profile (UserProfile): (default = None) Returns: UserProfile: user_profile CommandLine: python -m utool.util_project --exec-ensure_user_profile --show Example: >>> # DISABLE_DOCTEST >>> from utool.util_project import * # NOQA >>> import utool as ut >>> user_profile = None >>> user_profile = ensure_user_profile(user_profile) >>> result = ('user_profile = %s' % (ut.repr2(user_profile),)) >>> print(ut.repr3(user_profile.project_dpaths)) >>> print(result)

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train

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Xython/Linq.py

linq/standard/general.py

Skip

def Skip(self: Iterable, n): """ [ { 'self': [1, 2, 3, 4, 5], 'n': 3, 'assert': lambda ret: list(ret) == [4, 5] } ] """ con = iter(self) for i, _ in enumerate(con): if i == n: break return con

python

def Skip(self: Iterable, n): """ [ { 'self': [1, 2, 3, 4, 5], 'n': 3, 'assert': lambda ret: list(ret) == [4, 5] } ] """ con = iter(self) for i, _ in enumerate(con): if i == n: break return con

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train

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michaelliao/sinaweibopy

weibo.py

APIClient.get_authorize_url

def get_authorize_url(self, redirect_uri=None, **kw): ''' return the authorization url that the user should be redirected to. ''' redirect = redirect_uri if redirect_uri else self.redirect_uri if not redirect: raise APIError('21305', 'Parameter absent: redirect_uri', 'OAuth2 request') response_type = kw.pop('response_type', 'code') return '%s%s?%s' % (self.auth_url, 'authorize', _encode_params(client_id=self.client_id, response_type=response_type, redirect_uri=redirect, **kw))

python

def get_authorize_url(self, redirect_uri=None, **kw): ''' return the authorization url that the user should be redirected to. ''' redirect = redirect_uri if redirect_uri else self.redirect_uri if not redirect: raise APIError('21305', 'Parameter absent: redirect_uri', 'OAuth2 request') response_type = kw.pop('response_type', 'code') return '%s%s?%s' % (self.auth_url, 'authorize', _encode_params(client_id=self.client_id, response_type=response_type, redirect_uri=redirect, **kw))

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influxdata/influxdb-python

influxdb/influxdb08/client.py

InfluxDBClient.get_database_users

def get_database_users(self): """Get list of database users.""" url = "db/{0}/users".format(self._database) response = self.request( url=url, method='GET', expected_response_code=200 ) return response.json()

python

def get_database_users(self): """Get list of database users.""" url = "db/{0}/users".format(self._database) response = self.request( url=url, method='GET', expected_response_code=200 ) return response.json()

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nugget/python-insteonplm

insteonplm/devices/__init__.py

ALDB.find_matching_link

def find_matching_link(self, mode, group, addr): """Find a matching link in the current device. Mode: r | c is the mode of the link in the linked device This method will search for a corresponding link in the reverse direction. group: All-Link group number addr: Inteon address of the linked device """ found_rec = None mode_test = None if mode.lower() in ['c', 'r']: link_group = int(group) link_addr = Address(addr) for mem_addr in self: rec = self[mem_addr] if mode.lower() == 'r': mode_test = rec.control_flags.is_controller else: mode_test = rec.control_flags.is_responder if (mode_test and rec.group == link_group and rec.address == link_addr): found_rec = rec return found_rec

python

def find_matching_link(self, mode, group, addr): """Find a matching link in the current device. Mode: r | c is the mode of the link in the linked device This method will search for a corresponding link in the reverse direction. group: All-Link group number addr: Inteon address of the linked device """ found_rec = None mode_test = None if mode.lower() in ['c', 'r']: link_group = int(group) link_addr = Address(addr) for mem_addr in self: rec = self[mem_addr] if mode.lower() == 'r': mode_test = rec.control_flags.is_controller else: mode_test = rec.control_flags.is_responder if (mode_test and rec.group == link_group and rec.address == link_addr): found_rec = rec return found_rec

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log2timeline/dfvfs

dfvfs/file_io/encoded_stream_io.py

EncodedStream._ReadEncodedData

def _ReadEncodedData(self, read_size): """Reads encoded data from the file-like object. Args: read_size (int): number of bytes of encoded data to read. Returns: int: number of bytes of encoded data read. """ encoded_data = self._file_object.read(read_size) read_count = len(encoded_data) self._encoded_data = b''.join([self._encoded_data, encoded_data]) self._decoded_data, self._encoded_data = ( self._decoder.Decode(self._encoded_data)) self._decoded_data_size = len(self._decoded_data) return read_count

python

def _ReadEncodedData(self, read_size): """Reads encoded data from the file-like object. Args: read_size (int): number of bytes of encoded data to read. Returns: int: number of bytes of encoded data read. """ encoded_data = self._file_object.read(read_size) read_count = len(encoded_data) self._encoded_data = b''.join([self._encoded_data, encoded_data]) self._decoded_data, self._encoded_data = ( self._decoder.Decode(self._encoded_data)) self._decoded_data_size = len(self._decoded_data) return read_count

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Reads encoded data from the file-like object. Args: read_size (int): number of bytes of encoded data to read. Returns: int: number of bytes of encoded data read.

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sporteasy/python-poeditor

poeditor/client.py

POEditorAPI.add_language_to_project

def add_language_to_project(self, project_id, language_code): """ Adds a new language to project """ self._run( url_path="languages/add", id=project_id, language=language_code ) return True

python

def add_language_to_project(self, project_id, language_code): """ Adds a new language to project """ self._run( url_path="languages/add", id=project_id, language=language_code ) return True

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Adds a new language to project

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