Datasets:

jqop

/

python-code-dataset

like 0

fchorney/rpI2C

rpI2C.py

I2C.write_block_data

def write_block_data(self, cmd, block): """ Writes a block of bytes to the bus using I2C format to the specified command register """ self.bus.write_i2c_block_data(self.address, cmd, block) self.log.debug( "write_block_data: Wrote [%s] to command register 0x%02X" % ( ', '.join(['0x%02X' % x for x in block]), cmd ) )

python

def write_block_data(self, cmd, block): """ Writes a block of bytes to the bus using I2C format to the specified command register """ self.bus.write_i2c_block_data(self.address, cmd, block) self.log.debug( "write_block_data: Wrote [%s] to command register 0x%02X" % ( ', '.join(['0x%02X' % x for x in block]), cmd ) )

Writes a block of bytes to the bus using I2C format to the specified command register

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L75-L86

fchorney/rpI2C

rpI2C.py

I2C.read_raw_byte

def read_raw_byte(self): """ Read an 8-bit byte directly from the bus """ result = self.bus.read_byte(self.address) self.log.debug("read_raw_byte: Read 0x%02X from the bus" % result) return result

python

def read_raw_byte(self): """ Read an 8-bit byte directly from the bus """ result = self.bus.read_byte(self.address) self.log.debug("read_raw_byte: Read 0x%02X from the bus" % result) return result

Read an 8-bit byte directly from the bus

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L90-L96

fchorney/rpI2C

rpI2C.py

I2C.read_block_data

def read_block_data(self, cmd, length): """ Read a block of bytes from the bus from the specified command register Amount of bytes read in is defined by length """ results = self.bus.read_i2c_block_data(self.address, cmd, length) self.log.debug( "read_block_data: Read [%s] from command register 0x%02X" % ( ', '.join(['0x%02X' % x for x in results]), cmd ) ) return results

python

def read_block_data(self, cmd, length): """ Read a block of bytes from the bus from the specified command register Amount of bytes read in is defined by length """ results = self.bus.read_i2c_block_data(self.address, cmd, length) self.log.debug( "read_block_data: Read [%s] from command register 0x%02X" % ( ', '.join(['0x%02X' % x for x in results]), cmd ) ) return results

Read a block of bytes from the bus from the specified command register Amount of bytes read in is defined by length

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L98-L110

fchorney/rpI2C

rpI2C.py

I2C.read_unsigned_byte

def read_unsigned_byte(self, cmd): """ Read an unsigned byte from the specified command register """ result = self.bus.read_byte_data(self.address, cmd) self.log.debug( "read_unsigned_byte: Read 0x%02X from command register 0x%02X" % ( result, cmd ) ) return result

python

def read_unsigned_byte(self, cmd): """ Read an unsigned byte from the specified command register """ result = self.bus.read_byte_data(self.address, cmd) self.log.debug( "read_unsigned_byte: Read 0x%02X from command register 0x%02X" % ( result, cmd ) ) return result

Read an unsigned byte from the specified command register

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L112-L122

fchorney/rpI2C

rpI2C.py

I2C.read_unsigned_word

def read_unsigned_word(self, cmd, little_endian=True): """ Read an unsigned word from the specified command register We assume the data is in little endian mode, if it is in big endian mode then set little_endian to False """ result = self.bus.read_word_data(self.address, cmd) if not little_endian: result = ((result << 8) & 0xFF00) + (result >> 8) self.log.debug( "read_unsigned_word: Read 0x%04X from command register 0x%02X" % ( result, cmd ) ) return result

python

def read_unsigned_word(self, cmd, little_endian=True): """ Read an unsigned word from the specified command register We assume the data is in little endian mode, if it is in big endian mode then set little_endian to False """ result = self.bus.read_word_data(self.address, cmd) if not little_endian: result = ((result << 8) & 0xFF00) + (result >> 8) self.log.debug( "read_unsigned_word: Read 0x%04X from command register 0x%02X" % ( result, cmd ) ) return result

Read an unsigned word from the specified command register We assume the data is in little endian mode, if it is in big endian mode then set little_endian to False

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L141-L157

fchorney/rpI2C

rpI2C.py

I2C.__connect_to_bus

def __connect_to_bus(self, bus): """ Attempt to connect to an I2C bus """ def connect(bus_num): try: self.log.debug("Attempting to connect to bus %s..." % bus_num) self.bus = smbus.SMBus(bus_num) self.log.debug("Success") except IOError: self.log.debug("Failed") raise # If the bus is not explicitly stated, try 0 and then try 1 if that # fails if bus is None: try: connect(0) return except IOError: pass try: connect(1) return except IOError: raise else: try: connect(bus) return except IOError: raise

python

def __connect_to_bus(self, bus): """ Attempt to connect to an I2C bus """ def connect(bus_num): try: self.log.debug("Attempting to connect to bus %s..." % bus_num) self.bus = smbus.SMBus(bus_num) self.log.debug("Success") except IOError: self.log.debug("Failed") raise # If the bus is not explicitly stated, try 0 and then try 1 if that # fails if bus is None: try: connect(0) return except IOError: pass try: connect(1) return except IOError: raise else: try: connect(bus) return except IOError: raise

Attempt to connect to an I2C bus

train

https://github.com/fchorney/rpI2C/blob/7c60f82fa8c91496a74182373da0b95a13919d6e/rpI2C.py#L181-L213

developersociety/django-glitter

glitter/reminders/admin.py

ReminderInline.get_formset

def get_formset(self, request, obj=None, **kwargs): """ Default user to the current version owner. """ data = super().get_formset(request, obj, **kwargs) if obj: data.form.base_fields['user'].initial = request.user.id return data

python

def get_formset(self, request, obj=None, **kwargs): """ Default user to the current version owner. """ data = super().get_formset(request, obj, **kwargs) if obj: data.form.base_fields['user'].initial = request.user.id return data

Default user to the current version owner.

train

https://github.com/developersociety/django-glitter/blob/2c0280ec83afee80deee94ee3934fc54239c2e87/glitter/reminders/admin.py#L15-L20

davidblaisonneau-orange/foreman

foreman/objects.py

ForemanObjects.reload

def reload(self): """ Function reload Reload the full object to ensure sync """ realData = self.load() self.clear() self.update(realData)

python

def reload(self): """ Function reload Reload the full object to ensure sync """ realData = self.load() self.clear() self.update(realData)

Function reload Reload the full object to ensure sync

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/objects.py#L61-L67

davidblaisonneau-orange/foreman

foreman/objects.py

ForemanObjects.updateAfterDecorator

def updateAfterDecorator(function): """ Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman """ def _updateAfterDecorator(self, *args, **kwargs): ret = function(self, *args, **kwargs) self.reload() return ret return _updateAfterDecorator

python

def updateAfterDecorator(function): """ Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman """ def _updateAfterDecorator(self, *args, **kwargs): ret = function(self, *args, **kwargs) self.reload() return ret return _updateAfterDecorator

Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/objects.py#L70-L78

davidblaisonneau-orange/foreman

foreman/objects.py

ForemanObjects.updateBeforeDecorator

def updateBeforeDecorator(function): """ Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman """ def _updateBeforeDecorator(self, *args, **kwargs): if self.forceFullSync: self.reload() return function(self, *args, **kwargs) return _updateBeforeDecorator

python

def updateBeforeDecorator(function): """ Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman """ def _updateBeforeDecorator(self, *args, **kwargs): if self.forceFullSync: self.reload() return function(self, *args, **kwargs) return _updateBeforeDecorator

Function updateAfterDecorator Decorator to ensure local dict is sync with remote foreman

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/objects.py#L80-L88

davidblaisonneau-orange/foreman

foreman/objects.py

ForemanObjects.load

def load(self): """ Function load Get the list of all objects @return RETURN: A ForemanItem list """ return {x[self.index]: self.itemType(self.api, x['id'], self.objName, self.payloadObj, x) for x in self.api.list(self.objName, limit=self.searchLimit)}

python

def load(self): """ Function load Get the list of all objects @return RETURN: A ForemanItem list """ return {x[self.index]: self.itemType(self.api, x['id'], self.objName, self.payloadObj, x) for x in self.api.list(self.objName, limit=self.searchLimit)}

Function load Get the list of all objects @return RETURN: A ForemanItem list

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/objects.py#L141-L151

davidblaisonneau-orange/foreman

foreman/objects.py

ForemanObjects.checkAndCreate

def checkAndCreate(self, key, payload): """ Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object """ if key not in self: self[key] = payload return self[key]['id']

python

def checkAndCreate(self, key, payload): """ Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object """ if key not in self: self[key] = payload return self[key]['id']

Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/objects.py#L163-L173

qubell/contrib-python-qubell-client

qubell/api/private/__init__.py

operations

def operations(): """ Class decorator stores all calls into list. Can be used until .invalidate() is called. :return: decorated class """ def decorator(func): @wraps(func) def wrapped_func(*args, **kwargs): self = args[0] assert self.__can_use, "User operation queue only in 'with' block" def defaults_dict(): f_args, varargs, keywords, defaults = inspect.getargspec(func) defaults = defaults or [] return dict(zip(f_args[-len(defaults)+len(args[1:]):], defaults[len(args[1:]):])) route_args = dict(defaults_dict().items() + kwargs.items()) func(*args, **kwargs) self.operations.append((func.__name__, args[1:], route_args, )) return wrapped_func def decorate(clazz): for attr in clazz.__dict__: if callable(getattr(clazz, attr)): setattr(clazz, attr, decorator(getattr(clazz, attr))) def __init__(self): # simple parameter-less constructor self.operations = [] self.__can_use = True def invalidate(self): self.__can_use = False clazz.__init__ = __init__ clazz.invalidate = invalidate return clazz return decorate

python

def operations(): """ Class decorator stores all calls into list. Can be used until .invalidate() is called. :return: decorated class """ def decorator(func): @wraps(func) def wrapped_func(*args, **kwargs): self = args[0] assert self.__can_use, "User operation queue only in 'with' block" def defaults_dict(): f_args, varargs, keywords, defaults = inspect.getargspec(func) defaults = defaults or [] return dict(zip(f_args[-len(defaults)+len(args[1:]):], defaults[len(args[1:]):])) route_args = dict(defaults_dict().items() + kwargs.items()) func(*args, **kwargs) self.operations.append((func.__name__, args[1:], route_args, )) return wrapped_func def decorate(clazz): for attr in clazz.__dict__: if callable(getattr(clazz, attr)): setattr(clazz, attr, decorator(getattr(clazz, attr))) def __init__(self): # simple parameter-less constructor self.operations = [] self.__can_use = True def invalidate(self): self.__can_use = False clazz.__init__ = __init__ clazz.invalidate = invalidate return clazz return decorate

Class decorator stores all calls into list. Can be used until .invalidate() is called. :return: decorated class

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/__init__.py#L39-L76

developersociety/django-glitter

glitter/publisher/utils.py

process_actions

def process_actions(action_ids=None): """ Process actions in the publishing schedule. Returns the number of actions processed. """ actions_taken = 0 action_list = PublishAction.objects.prefetch_related( 'content_object', ).filter( scheduled_time__lte=timezone.now(), ) if action_ids is not None: action_list = action_list.filter(id__in=action_ids) for action in action_list: action.process_action() action.delete() actions_taken += 1 return actions_taken

python

def process_actions(action_ids=None): """ Process actions in the publishing schedule. Returns the number of actions processed. """ actions_taken = 0 action_list = PublishAction.objects.prefetch_related( 'content_object', ).filter( scheduled_time__lte=timezone.now(), ) if action_ids is not None: action_list = action_list.filter(id__in=action_ids) for action in action_list: action.process_action() action.delete() actions_taken += 1 return actions_taken

Process actions in the publishing schedule. Returns the number of actions processed.

train

https://github.com/developersociety/django-glitter/blob/2c0280ec83afee80deee94ee3934fc54239c2e87/glitter/publisher/utils.py#L7-L28

developersociety/django-glitter

glitter/publisher/utils.py

celery_enabled

def celery_enabled(): """ Return a boolean if Celery tasks are enabled for this app. If the ``GLITTER_PUBLISHER_CELERY`` setting is ``True`` or ``False`` - then that value will be used. However if the setting isn't defined, then this will be enabled automatically if Celery is installed. """ enabled = getattr(settings, 'GLITTER_PUBLISHER_CELERY', None) if enabled is None: try: import celery # noqa enabled = True except ImportError: enabled = False return enabled

python

def celery_enabled(): """ Return a boolean if Celery tasks are enabled for this app. If the ``GLITTER_PUBLISHER_CELERY`` setting is ``True`` or ``False`` - then that value will be used. However if the setting isn't defined, then this will be enabled automatically if Celery is installed. """ enabled = getattr(settings, 'GLITTER_PUBLISHER_CELERY', None) if enabled is None: try: import celery # noqa enabled = True except ImportError: enabled = False return enabled

Return a boolean if Celery tasks are enabled for this app. If the ``GLITTER_PUBLISHER_CELERY`` setting is ``True`` or ``False`` - then that value will be used. However if the setting isn't defined, then this will be enabled automatically if Celery is installed.

train

https://github.com/developersociety/django-glitter/blob/2c0280ec83afee80deee94ee3934fc54239c2e87/glitter/publisher/utils.py#L31-L48

davidblaisonneau-orange/foreman

foreman/operatingsystems.py

OperatingSystems.checkAndCreate

def checkAndCreate(self, key, payload): """ Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object """ if key not in self: if 'templates' in payload: templates = payload.pop('templates') self[key] = payload self.reload() return self[key]['id']

python

def checkAndCreate(self, key, payload): """ Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object """ if key not in self: if 'templates' in payload: templates = payload.pop('templates') self[key] = payload self.reload() return self[key]['id']

Function checkAndCreate Check if an object exists and create it if not @param key: The targeted object @param payload: The targeted object description @return RETURN: The id of the object

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/operatingsystems.py#L51-L64

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance.__collect_interfaces_return

def __collect_interfaces_return(interfaces): """Collect new style (44.1+) return values to old-style kv-list""" acc = [] for (interfaceName, interfaceData) in interfaces.items(): signalValues = interfaceData.get("signals", {}) for (signalName, signalValue) in signalValues.items(): pinName = "{0}.{1}".format(interfaceName, signalName) acc.append({'id': pinName, 'value': signalValue}) return acc

python

def __collect_interfaces_return(interfaces): """Collect new style (44.1+) return values to old-style kv-list""" acc = [] for (interfaceName, interfaceData) in interfaces.items(): signalValues = interfaceData.get("signals", {}) for (signalName, signalValue) in signalValues.items(): pinName = "{0}.{1}".format(interfaceName, signalName) acc.append({'id': pinName, 'value': signalValue}) return acc

Collect new style (44.1+) return values to old-style kv-list

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L113-L121

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance.return_values

def return_values(self): """ Guess what api we are using and return as public api does. Private has {'id':'key', 'value':'keyvalue'} format, public has {'key':'keyvalue'} """ j = self.json() #TODO: FIXME: get rid of old API when its support will be removed public_api_value = j.get('returnValues') old_private_value = j.get('endpoints') new_private_value = self.__collect_interfaces_return(j.get('interfaces', {})) retvals = new_private_value or old_private_value or public_api_value or [] # TODO: Public api hack. if self._router.public_api_in_use: return retvals return self.__parse(retvals)

python

def return_values(self): """ Guess what api we are using and return as public api does. Private has {'id':'key', 'value':'keyvalue'} format, public has {'key':'keyvalue'} """ j = self.json() #TODO: FIXME: get rid of old API when its support will be removed public_api_value = j.get('returnValues') old_private_value = j.get('endpoints') new_private_value = self.__collect_interfaces_return(j.get('interfaces', {})) retvals = new_private_value or old_private_value or public_api_value or [] # TODO: Public api hack. if self._router.public_api_in_use: return retvals return self.__parse(retvals)

Guess what api we are using and return as public api does. Private has {'id':'key', 'value':'keyvalue'} format, public has {'key':'keyvalue'}

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L124-L139

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance.get_activitylog

def get_activitylog(self, after=None, severity=None, start=None, end=None): """ Returns activitylog object severity - filter severity ('INFO', DEBUG') start/end - time or log text """ if after: log_raw = self._router.get_instance_activitylog(org_id=self.organizationId, instance_id=self.instanceId, params={"after": after}).json() else: log_raw = self._router.get_instance_activitylog(org_id=self.organizationId, instance_id=self.instanceId).json() return ActivityLog(log_raw, severity=severity, start=start, end=end)

python

def get_activitylog(self, after=None, severity=None, start=None, end=None): """ Returns activitylog object severity - filter severity ('INFO', DEBUG') start/end - time or log text """ if after: log_raw = self._router.get_instance_activitylog(org_id=self.organizationId, instance_id=self.instanceId, params={"after": after}).json() else: log_raw = self._router.get_instance_activitylog(org_id=self.organizationId, instance_id=self.instanceId).json() return ActivityLog(log_raw, severity=severity, start=start, end=end)

Returns activitylog object severity - filter severity ('INFO', DEBUG') start/end - time or log text

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L149-L164

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance.json

def json(self): """ return __cached_json, if accessed withing 300 ms. This allows to optimize calls when many parameters of entity requires withing short time. """ if self.fresh(): return self.__cached_json # noinspection PyAttributeOutsideInit self.__last_read_time = time.time() self.__cached_json = self._router.get_instance(org_id=self.organizationId, instance_id=self.instanceId).json() return self.__cached_json

python

def json(self): """ return __cached_json, if accessed withing 300 ms. This allows to optimize calls when many parameters of entity requires withing short time. """ if self.fresh(): return self.__cached_json # noinspection PyAttributeOutsideInit self.__last_read_time = time.time() self.__cached_json = self._router.get_instance(org_id=self.organizationId, instance_id=self.instanceId).json() return self.__cached_json

return __cached_json, if accessed withing 300 ms. This allows to optimize calls when many parameters of entity requires withing short time.

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L264-L276

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance.get_most_recent_update_time

def get_most_recent_update_time(self): """ Indicated most recent update of the instance, assumption based on: - if currentWorkflow exists, its startedAt time is most recent update. - else max of workflowHistory startedAt is most recent update. """ def parse_time(t): if t: return time.gmtime(t/1000) return None try: max_wf_started_at = max([i.get('startedAt') for i in self.workflowHistory]) return parse_time(max_wf_started_at) except ValueError: return None

python

def get_most_recent_update_time(self): """ Indicated most recent update of the instance, assumption based on: - if currentWorkflow exists, its startedAt time is most recent update. - else max of workflowHistory startedAt is most recent update. """ def parse_time(t): if t: return time.gmtime(t/1000) return None try: max_wf_started_at = max([i.get('startedAt') for i in self.workflowHistory]) return parse_time(max_wf_started_at) except ValueError: return None

Indicated most recent update of the instance, assumption based on: - if currentWorkflow exists, its startedAt time is most recent update. - else max of workflowHistory startedAt is most recent update.

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L508-L522

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

Instance._is_projection_updated_instance

def _is_projection_updated_instance(self): """ This method tries to guess if instance was update since last time. If return True, definitely Yes, if False, this means more unknown :return: bool """ last = self._last_workflow_started_time if not self._router.public_api_in_use: most_recent = self.get_most_recent_update_time() else: most_recent = None if last and most_recent: return last < most_recent return False

python

def _is_projection_updated_instance(self): """ This method tries to guess if instance was update since last time. If return True, definitely Yes, if False, this means more unknown :return: bool """ last = self._last_workflow_started_time if not self._router.public_api_in_use: most_recent = self.get_most_recent_update_time() else: most_recent = None if last and most_recent: return last < most_recent return False

This method tries to guess if instance was update since last time. If return True, definitely Yes, if False, this means more unknown :return: bool

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L524-L537

qubell/contrib-python-qubell-client

qubell/api/private/instance.py

ActivityLog.find

def find(self, item, description='', event_type=''): """ Find regexp in activitylog find record as if type are in description. """ # TODO: should be refactored, dumb logic if ': ' in item: splited = item.split(': ', 1) if splited[0] in self.TYPES: description = item.split(': ')[1] event_type = item.split(': ')[0] else: description = item else: if not description: description = item if event_type: found = [x['time'] for x in self.log if re.search(description, x['description']) and x['eventTypeText'] == event_type] else: found = [x['time'] for x in self.log if re.search(description, x['description'])] if len(found): return found raise exceptions.NotFoundError("Item '{}' is not found with (description='{}', event_type='{}')". format(item, description, event_type))

python

def find(self, item, description='', event_type=''): """ Find regexp in activitylog find record as if type are in description. """ # TODO: should be refactored, dumb logic if ': ' in item: splited = item.split(': ', 1) if splited[0] in self.TYPES: description = item.split(': ')[1] event_type = item.split(': ')[0] else: description = item else: if not description: description = item if event_type: found = [x['time'] for x in self.log if re.search(description, x['description']) and x['eventTypeText'] == event_type] else: found = [x['time'] for x in self.log if re.search(description, x['description'])] if len(found): return found raise exceptions.NotFoundError("Item '{}' is not found with (description='{}', event_type='{}')". format(item, description, event_type))

Find regexp in activitylog find record as if type are in description.

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/private/instance.py#L621-L647

jamescooke/flake8-aaa

src/flake8_aaa/command_line.py

do_command_line

def do_command_line(infile: typing.IO[str]) -> int: """ Currently a small stub to create an instance of Checker for the passed ``infile`` and run its test functions through linting. Args: infile Returns: int: Number of flake8 errors raised. """ lines = infile.readlines() tree = ast.parse(''.join(lines)) checker = Checker(tree, lines, infile.name) checker.load() errors = [] # type: typing.List[AAAError] for func in checker.all_funcs(skip_noqa=True): try: errors = list(func.check_all()) except ValidationError as error: errors = [error.to_aaa()] print(func.__str__(errors), end='') return len(errors)

python

def do_command_line(infile: typing.IO[str]) -> int: """ Currently a small stub to create an instance of Checker for the passed ``infile`` and run its test functions through linting. Args: infile Returns: int: Number of flake8 errors raised. """ lines = infile.readlines() tree = ast.parse(''.join(lines)) checker = Checker(tree, lines, infile.name) checker.load() errors = [] # type: typing.List[AAAError] for func in checker.all_funcs(skip_noqa=True): try: errors = list(func.check_all()) except ValidationError as error: errors = [error.to_aaa()] print(func.__str__(errors), end='') return len(errors)

Currently a small stub to create an instance of Checker for the passed ``infile`` and run its test functions through linting. Args: infile Returns: int: Number of flake8 errors raised.

train

https://github.com/jamescooke/flake8-aaa/blob/29938b96845fe32ced4358ba66af3b3be2a37794/src/flake8_aaa/command_line.py#L8-L30

aroberge/experimental

experimental/core/import_hook.py

MyMetaFinder.find_spec

def find_spec(self, fullname, path, target=None): '''finds the appropriate properties (spec) of a module, and sets its loader.''' if not path: path = [os.getcwd()] if "." in fullname: name = fullname.split(".")[-1] else: name = fullname for entry in path: if os.path.isdir(os.path.join(entry, name)): # this module has child modules filename = os.path.join(entry, name, "__init__.py") submodule_locations = [os.path.join(entry, name)] else: filename = os.path.join(entry, name + ".py") submodule_locations = None if not os.path.exists(filename): continue return spec_from_file_location(fullname, filename, loader=MyLoader(filename), submodule_search_locations=submodule_locations) return None

python

def find_spec(self, fullname, path, target=None): '''finds the appropriate properties (spec) of a module, and sets its loader.''' if not path: path = [os.getcwd()] if "." in fullname: name = fullname.split(".")[-1] else: name = fullname for entry in path: if os.path.isdir(os.path.join(entry, name)): # this module has child modules filename = os.path.join(entry, name, "__init__.py") submodule_locations = [os.path.join(entry, name)] else: filename = os.path.join(entry, name + ".py") submodule_locations = None if not os.path.exists(filename): continue return spec_from_file_location(fullname, filename, loader=MyLoader(filename), submodule_search_locations=submodule_locations) return None

finds the appropriate properties (spec) of a module, and sets its loader.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/core/import_hook.py#L47-L70

aroberge/experimental

experimental/core/import_hook.py

MyLoader.exec_module

def exec_module(self, module): '''import the source code, transforma it before executing it so that it is known to Python.''' global MAIN_MODULE_NAME if module.__name__ == MAIN_MODULE_NAME: module.__name__ = "__main__" MAIN_MODULE_NAME = None with open(self.filename) as f: source = f.read() if transforms.transformers: source = transforms.transform(source) else: for line in source.split('\n'): if transforms.FROM_EXPERIMENTAL.match(line): ## transforms.transform will extract all such relevant ## lines and add them all relevant transformers source = transforms.transform(source) break exec(source, vars(module))

python

def exec_module(self, module): '''import the source code, transforma it before executing it so that it is known to Python.''' global MAIN_MODULE_NAME if module.__name__ == MAIN_MODULE_NAME: module.__name__ = "__main__" MAIN_MODULE_NAME = None with open(self.filename) as f: source = f.read() if transforms.transformers: source = transforms.transform(source) else: for line in source.split('\n'): if transforms.FROM_EXPERIMENTAL.match(line): ## transforms.transform will extract all such relevant ## lines and add them all relevant transformers source = transforms.transform(source) break exec(source, vars(module))

import the source code, transforma it before executing it so that it is known to Python.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/core/import_hook.py#L83-L103

astroduff/commah

commah/commah.py

_izip

def _izip(*iterables): """ Iterate through multiple lists or arrays of equal size """ # This izip routine is from itertools # izip('ABCD', 'xy') --> Ax By iterators = map(iter, iterables) while iterators: yield tuple(map(next, iterators))

python

def _izip(*iterables): """ Iterate through multiple lists or arrays of equal size """ # This izip routine is from itertools # izip('ABCD', 'xy') --> Ax By iterators = map(iter, iterables) while iterators: yield tuple(map(next, iterators))

Iterate through multiple lists or arrays of equal size

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L17-L24

astroduff/commah

commah/commah.py

_checkinput

def _checkinput(zi, Mi, z=False, verbose=None): """ Check and convert any input scalar or array to numpy array """ # How many halo redshifts provided? zi = np.array(zi, ndmin=1, dtype=float) # How many halo masses provided? Mi = np.array(Mi, ndmin=1, dtype=float) # Check the input sizes for zi and Mi make sense, if not then exit unless # one axis is length one, then replicate values to the size of the other if (zi.size > 1) and (Mi.size > 1): if(zi.size != Mi.size): print("Error ambiguous request") print("Need individual redshifts for all haloes provided ") print("Or have all haloes at same redshift ") return(-1) elif (zi.size == 1) and (Mi.size > 1): if verbose: print("Assume zi is the same for all Mi halo masses provided") # Replicate redshift for all halo masses zi = np.ones_like(Mi)*zi[0] elif (Mi.size == 1) and (zi.size > 1): if verbose: print("Assume Mi halo masses are the same for all zi provided") # Replicate redshift for all halo masses Mi = np.ones_like(zi)*Mi[0] else: if verbose: print("A single Mi and zi provided") # Very simple test for size / type of incoming array # just in case numpy / list given if z is False: # Didn't pass anything, set zi = z lenzout = 1 else: # If something was passed, convert to 1D NumPy array z = np.array(z, ndmin=1, dtype=float) lenzout = z.size return(zi, Mi, z, zi.size, Mi.size, lenzout)

python

def _checkinput(zi, Mi, z=False, verbose=None): """ Check and convert any input scalar or array to numpy array """ # How many halo redshifts provided? zi = np.array(zi, ndmin=1, dtype=float) # How many halo masses provided? Mi = np.array(Mi, ndmin=1, dtype=float) # Check the input sizes for zi and Mi make sense, if not then exit unless # one axis is length one, then replicate values to the size of the other if (zi.size > 1) and (Mi.size > 1): if(zi.size != Mi.size): print("Error ambiguous request") print("Need individual redshifts for all haloes provided ") print("Or have all haloes at same redshift ") return(-1) elif (zi.size == 1) and (Mi.size > 1): if verbose: print("Assume zi is the same for all Mi halo masses provided") # Replicate redshift for all halo masses zi = np.ones_like(Mi)*zi[0] elif (Mi.size == 1) and (zi.size > 1): if verbose: print("Assume Mi halo masses are the same for all zi provided") # Replicate redshift for all halo masses Mi = np.ones_like(zi)*Mi[0] else: if verbose: print("A single Mi and zi provided") # Very simple test for size / type of incoming array # just in case numpy / list given if z is False: # Didn't pass anything, set zi = z lenzout = 1 else: # If something was passed, convert to 1D NumPy array z = np.array(z, ndmin=1, dtype=float) lenzout = z.size return(zi, Mi, z, zi.size, Mi.size, lenzout)

Check and convert any input scalar or array to numpy array

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L27-L67

astroduff/commah

commah/commah.py

getcosmo

def getcosmo(cosmology): """ Find cosmological parameters for named cosmo in cosmology.py list """ defaultcosmologies = {'dragons': cg.DRAGONS(), 'wmap1': cg.WMAP1_Mill(), 'wmap3': cg.WMAP3_ML(), 'wmap5': cg.WMAP5_mean(), 'wmap7': cg.WMAP7_ML(), 'wmap9': cg.WMAP9_ML(), 'wmap1_lss': cg.WMAP1_2dF_mean(), 'wmap3_mean': cg.WMAP3_mean(), 'wmap5_ml': cg.WMAP5_ML(), 'wmap5_lss': cg.WMAP5_BAO_SN_mean(), 'wmap7_lss': cg.WMAP7_BAO_H0_mean(), 'planck13': cg.Planck_2013(), 'planck15': cg.Planck_2015()} if isinstance(cosmology, dict): # User providing their own variables cosmo = cosmology if 'A_scaling' not in cosmology.keys(): A_scaling = getAscaling(cosmology, newcosmo=True) cosmo.update({'A_scaling': A_scaling}) # Add extra variables by hand that cosmolopy requires # note that they aren't used (set to zero) for paramnames in cg.WMAP5_mean().keys(): if paramnames not in cosmology.keys(): cosmo.update({paramnames: 0}) elif cosmology.lower() in defaultcosmologies.keys(): # Load by name of cosmology instead cosmo = defaultcosmologies[cosmology.lower()] A_scaling = getAscaling(cosmology) cosmo.update({'A_scaling': A_scaling}) else: print("You haven't passed a dict of cosmological parameters ") print("OR a recognised cosmology, you gave %s" % (cosmology)) # No idea why this has to be done by hand but should be O_k = 0 cosmo = cp.distance.set_omega_k_0(cosmo) # Use the cosmology as **cosmo passed to cosmolopy routines return(cosmo)

python

def getcosmo(cosmology): """ Find cosmological parameters for named cosmo in cosmology.py list """ defaultcosmologies = {'dragons': cg.DRAGONS(), 'wmap1': cg.WMAP1_Mill(), 'wmap3': cg.WMAP3_ML(), 'wmap5': cg.WMAP5_mean(), 'wmap7': cg.WMAP7_ML(), 'wmap9': cg.WMAP9_ML(), 'wmap1_lss': cg.WMAP1_2dF_mean(), 'wmap3_mean': cg.WMAP3_mean(), 'wmap5_ml': cg.WMAP5_ML(), 'wmap5_lss': cg.WMAP5_BAO_SN_mean(), 'wmap7_lss': cg.WMAP7_BAO_H0_mean(), 'planck13': cg.Planck_2013(), 'planck15': cg.Planck_2015()} if isinstance(cosmology, dict): # User providing their own variables cosmo = cosmology if 'A_scaling' not in cosmology.keys(): A_scaling = getAscaling(cosmology, newcosmo=True) cosmo.update({'A_scaling': A_scaling}) # Add extra variables by hand that cosmolopy requires # note that they aren't used (set to zero) for paramnames in cg.WMAP5_mean().keys(): if paramnames not in cosmology.keys(): cosmo.update({paramnames: 0}) elif cosmology.lower() in defaultcosmologies.keys(): # Load by name of cosmology instead cosmo = defaultcosmologies[cosmology.lower()] A_scaling = getAscaling(cosmology) cosmo.update({'A_scaling': A_scaling}) else: print("You haven't passed a dict of cosmological parameters ") print("OR a recognised cosmology, you gave %s" % (cosmology)) # No idea why this has to be done by hand but should be O_k = 0 cosmo = cp.distance.set_omega_k_0(cosmo) # Use the cosmology as **cosmo passed to cosmolopy routines return(cosmo)

Find cosmological parameters for named cosmo in cosmology.py list

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L70-L108

astroduff/commah

commah/commah.py

_getcosmoheader

def _getcosmoheader(cosmo): """ Output the cosmology to a string for writing to file """ cosmoheader = ("# Cosmology (flat) Om:{0:.3f}, Ol:{1:.3f}, h:{2:.2f}, " "sigma8:{3:.3f}, ns:{4:.2f}".format( cosmo['omega_M_0'], cosmo['omega_lambda_0'], cosmo['h'], cosmo['sigma_8'], cosmo['n'])) return(cosmoheader)

python

def _getcosmoheader(cosmo): """ Output the cosmology to a string for writing to file """ cosmoheader = ("# Cosmology (flat) Om:{0:.3f}, Ol:{1:.3f}, h:{2:.2f}, " "sigma8:{3:.3f}, ns:{4:.2f}".format( cosmo['omega_M_0'], cosmo['omega_lambda_0'], cosmo['h'], cosmo['sigma_8'], cosmo['n'])) return(cosmoheader)

Output the cosmology to a string for writing to file

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L111-L119

astroduff/commah

commah/commah.py

cduffy

def cduffy(z, M, vir='200crit', relaxed=True): """ NFW conc from Duffy 08 Table 1 for halo mass and redshift""" if(vir == '200crit'): if relaxed: params = [6.71, -0.091, -0.44] else: params = [5.71, -0.084, -0.47] elif(vir == 'tophat'): if relaxed: params = [9.23, -0.090, -0.69] else: params = [7.85, -0.081, -0.71] elif(vir == '200mean'): if relaxed: params = [11.93, -0.090, -0.99] else: params = [10.14, -0.081, -1.01] else: print("Didn't recognise the halo boundary definition provided %s" % (vir)) return(params[0] * ((M/(2e12/0.72))**params[1]) * ((1+z)**params[2]))

python

def cduffy(z, M, vir='200crit', relaxed=True): """ NFW conc from Duffy 08 Table 1 for halo mass and redshift""" if(vir == '200crit'): if relaxed: params = [6.71, -0.091, -0.44] else: params = [5.71, -0.084, -0.47] elif(vir == 'tophat'): if relaxed: params = [9.23, -0.090, -0.69] else: params = [7.85, -0.081, -0.71] elif(vir == '200mean'): if relaxed: params = [11.93, -0.090, -0.99] else: params = [10.14, -0.081, -1.01] else: print("Didn't recognise the halo boundary definition provided %s" % (vir)) return(params[0] * ((M/(2e12/0.72))**params[1]) * ((1+z)**params[2]))

NFW conc from Duffy 08 Table 1 for halo mass and redshift

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L122-L144

astroduff/commah

commah/commah.py

_delta_sigma

def _delta_sigma(**cosmo): """ Perturb best-fit constant of proportionality Ascaling for rho_crit - rho_2 relation for unknown cosmology (Correa et al 2015c) Parameters ---------- cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float The perturbed 'A' relation between rho_2 and rho_crit for the cosmology Raises ------ """ M8_cosmo = cp.perturbation.radius_to_mass(8, **cosmo) perturbed_A = (0.796/cosmo['sigma_8']) * \ (M8_cosmo/2.5e14)**((cosmo['n']-0.963)/6) return(perturbed_A)

python

def _delta_sigma(**cosmo): """ Perturb best-fit constant of proportionality Ascaling for rho_crit - rho_2 relation for unknown cosmology (Correa et al 2015c) Parameters ---------- cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float The perturbed 'A' relation between rho_2 and rho_crit for the cosmology Raises ------ """ M8_cosmo = cp.perturbation.radius_to_mass(8, **cosmo) perturbed_A = (0.796/cosmo['sigma_8']) * \ (M8_cosmo/2.5e14)**((cosmo['n']-0.963)/6) return(perturbed_A)

Perturb best-fit constant of proportionality Ascaling for rho_crit - rho_2 relation for unknown cosmology (Correa et al 2015c) Parameters ---------- cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float The perturbed 'A' relation between rho_2 and rho_crit for the cosmology Raises ------

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L147-L172

astroduff/commah

commah/commah.py

getAscaling

def getAscaling(cosmology, newcosmo=None): """ Returns the normalisation constant between Rho_-2 and Rho_mean(z_formation) for a given cosmology Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} newcosmo : str, optional If cosmology is not from predefined list have to perturbation A_scaling variable. Defaults to None. Returns ------- float The scaled 'A' relation between rho_2 and rho_crit for the cosmology """ # Values from Correa 15c defaultcosmologies = {'dragons': 887, 'wmap1': 853, 'wmap3': 850, 'wmap5': 887, 'wmap7': 887, 'wmap9': 950, 'wmap1_lss': 853, 'wmap3_mean': 850, 'wmap5_ml': 887, 'wmap5_lss': 887, 'wmap7_lss': 887, 'planck13': 880, 'planck15': 880} if newcosmo: # Scale from default WMAP5 cosmology using Correa et al 14b eqn C1 A_scaling = defaultcosmologies['wmap5'] * _delta_sigma(**cosmology) else: if cosmology.lower() in defaultcosmologies.keys(): A_scaling = defaultcosmologies[cosmology.lower()] else: print("Error, don't recognise your cosmology for A_scaling ") print("You provided %s" % (cosmology)) return(A_scaling)

python

def getAscaling(cosmology, newcosmo=None): """ Returns the normalisation constant between Rho_-2 and Rho_mean(z_formation) for a given cosmology Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} newcosmo : str, optional If cosmology is not from predefined list have to perturbation A_scaling variable. Defaults to None. Returns ------- float The scaled 'A' relation between rho_2 and rho_crit for the cosmology """ # Values from Correa 15c defaultcosmologies = {'dragons': 887, 'wmap1': 853, 'wmap3': 850, 'wmap5': 887, 'wmap7': 887, 'wmap9': 950, 'wmap1_lss': 853, 'wmap3_mean': 850, 'wmap5_ml': 887, 'wmap5_lss': 887, 'wmap7_lss': 887, 'planck13': 880, 'planck15': 880} if newcosmo: # Scale from default WMAP5 cosmology using Correa et al 14b eqn C1 A_scaling = defaultcosmologies['wmap5'] * _delta_sigma(**cosmology) else: if cosmology.lower() in defaultcosmologies.keys(): A_scaling = defaultcosmologies[cosmology.lower()] else: print("Error, don't recognise your cosmology for A_scaling ") print("You provided %s" % (cosmology)) return(A_scaling)

Returns the normalisation constant between Rho_-2 and Rho_mean(z_formation) for a given cosmology Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} newcosmo : str, optional If cosmology is not from predefined list have to perturbation A_scaling variable. Defaults to None. Returns ------- float The scaled 'A' relation between rho_2 and rho_crit for the cosmology

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L175-L216

astroduff/commah

commah/commah.py

_int_growth

def _int_growth(z, **cosmo): """ Returns integral of the linear growth factor from z=200 to z=z """ zmax = 200 if hasattr(z, "__len__"): for zval in z: assert(zval < zmax) else: assert(z < zmax) y, yerr = scipy.integrate.quad( lambda z: (1 + z)/(cosmo['omega_M_0']*(1 + z)**3 + cosmo['omega_lambda_0'])**(1.5), z, zmax) return(y)

python

def _int_growth(z, **cosmo): """ Returns integral of the linear growth factor from z=200 to z=z """ zmax = 200 if hasattr(z, "__len__"): for zval in z: assert(zval < zmax) else: assert(z < zmax) y, yerr = scipy.integrate.quad( lambda z: (1 + z)/(cosmo['omega_M_0']*(1 + z)**3 + cosmo['omega_lambda_0'])**(1.5), z, zmax) return(y)

Returns integral of the linear growth factor from z=200 to z=z

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L219-L235

astroduff/commah

commah/commah.py

_deriv_growth

def _deriv_growth(z, **cosmo): """ Returns derivative of the linear growth factor at z for a given cosmology **cosmo """ inv_h = (cosmo['omega_M_0']*(1 + z)**3 + cosmo['omega_lambda_0'])**(-0.5) fz = (1 + z) * inv_h**3 deriv_g = growthfactor(z, norm=True, **cosmo)*(inv_h**2) *\ 1.5 * cosmo['omega_M_0'] * (1 + z)**2 -\ fz * growthfactor(z, norm=True, **cosmo)/_int_growth(z, **cosmo) return(deriv_g)

python

def _deriv_growth(z, **cosmo): """ Returns derivative of the linear growth factor at z for a given cosmology **cosmo """ inv_h = (cosmo['omega_M_0']*(1 + z)**3 + cosmo['omega_lambda_0'])**(-0.5) fz = (1 + z) * inv_h**3 deriv_g = growthfactor(z, norm=True, **cosmo)*(inv_h**2) *\ 1.5 * cosmo['omega_M_0'] * (1 + z)**2 -\ fz * growthfactor(z, norm=True, **cosmo)/_int_growth(z, **cosmo) return(deriv_g)

Returns derivative of the linear growth factor at z for a given cosmology **cosmo

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L238-L249

astroduff/commah

commah/commah.py

growthfactor

def growthfactor(z, norm=True, **cosmo): """ Returns linear growth factor at a given redshift, normalised to z=0 by default, for a given cosmology Parameters ---------- z : float or numpy array The redshift at which the growth factor should be calculated norm : boolean, optional If true then normalise the growth factor to z=0 case defaults True cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float or numpy array The growth factor at a range of redshifts 'z' Raises ------ """ H = np.sqrt(cosmo['omega_M_0'] * (1 + z)**3 + cosmo['omega_lambda_0']) growthval = H * _int_growth(z, **cosmo) if norm: growthval /= _int_growth(0, **cosmo) return(growthval)

python

def growthfactor(z, norm=True, **cosmo): """ Returns linear growth factor at a given redshift, normalised to z=0 by default, for a given cosmology Parameters ---------- z : float or numpy array The redshift at which the growth factor should be calculated norm : boolean, optional If true then normalise the growth factor to z=0 case defaults True cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float or numpy array The growth factor at a range of redshifts 'z' Raises ------ """ H = np.sqrt(cosmo['omega_M_0'] * (1 + z)**3 + cosmo['omega_lambda_0']) growthval = H * _int_growth(z, **cosmo) if norm: growthval /= _int_growth(0, **cosmo) return(growthval)

Returns linear growth factor at a given redshift, normalised to z=0 by default, for a given cosmology Parameters ---------- z : float or numpy array The redshift at which the growth factor should be calculated norm : boolean, optional If true then normalise the growth factor to z=0 case defaults True cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- float or numpy array The growth factor at a range of redshifts 'z' Raises ------

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L252-L284

astroduff/commah

commah/commah.py

_minimize_c

def _minimize_c(c, z=0, a_tilde=1, b_tilde=-1, Ascaling=900, omega_M_0=0.25, omega_lambda_0=0.75): """ Trial function to solve 2 eqns (17 and 18) from Correa et al. (2015c) for 1 unknown, i.e. concentration, returned by a minimisation call """ # Fn 1 (LHS of Eqn 18) Y1 = np.log(2) - 0.5 Yc = np.log(1+c) - c/(1+c) f1 = Y1/Yc # Fn 2 (RHS of Eqn 18) # Eqn 14 - Define the mean inner density rho_2 = 200 * c**3 * Y1 / Yc # Eqn 17 rearranged to solve for Formation Redshift # essentially when universe had rho_2 density zf = (((1 + z)**3 + omega_lambda_0/omega_M_0) * (rho_2/Ascaling) - omega_lambda_0/omega_M_0)**(1/3) - 1 # RHS of Eqn 19 f2 = ((1 + zf - z)**a_tilde) * np.exp((zf - z) * b_tilde) # LHS - RHS should be zero for the correct concentration return(f1-f2)

python

def _minimize_c(c, z=0, a_tilde=1, b_tilde=-1, Ascaling=900, omega_M_0=0.25, omega_lambda_0=0.75): """ Trial function to solve 2 eqns (17 and 18) from Correa et al. (2015c) for 1 unknown, i.e. concentration, returned by a minimisation call """ # Fn 1 (LHS of Eqn 18) Y1 = np.log(2) - 0.5 Yc = np.log(1+c) - c/(1+c) f1 = Y1/Yc # Fn 2 (RHS of Eqn 18) # Eqn 14 - Define the mean inner density rho_2 = 200 * c**3 * Y1 / Yc # Eqn 17 rearranged to solve for Formation Redshift # essentially when universe had rho_2 density zf = (((1 + z)**3 + omega_lambda_0/omega_M_0) * (rho_2/Ascaling) - omega_lambda_0/omega_M_0)**(1/3) - 1 # RHS of Eqn 19 f2 = ((1 + zf - z)**a_tilde) * np.exp((zf - z) * b_tilde) # LHS - RHS should be zero for the correct concentration return(f1-f2)

Trial function to solve 2 eqns (17 and 18) from Correa et al. (2015c) for 1 unknown, i.e. concentration, returned by a minimisation call

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L287-L312

astroduff/commah

commah/commah.py

formationz

def formationz(c, z, Ascaling=900, omega_M_0=0.25, omega_lambda_0=0.75): """ Rearrange eqn 18 from Correa et al (2015c) to return formation redshift for a concentration at a given redshift Parameters ---------- c : float / numpy array Concentration of halo z : float / numpy array Redshift of halo with concentration c Ascaling : float Cosmological dependent scaling between densities, use function getAscaling('WMAP5') if unsure. Default is 900. omega_M_0 : float Mass density of the universe. Default is 0.25 omega_lambda_0 : float Dark Energy density of the universe. Default is 0.75 Returns ------- zf : float / numpy array Formation redshift for halo of concentration 'c' at redshift 'z' """ Y1 = np.log(2) - 0.5 Yc = np.log(1+c) - c/(1+c) rho_2 = 200*(c**3)*Y1/Yc zf = (((1+z)**3 + omega_lambda_0/omega_M_0) * (rho_2/Ascaling) - omega_lambda_0/omega_M_0)**(1/3) - 1 return(zf)

python

def formationz(c, z, Ascaling=900, omega_M_0=0.25, omega_lambda_0=0.75): """ Rearrange eqn 18 from Correa et al (2015c) to return formation redshift for a concentration at a given redshift Parameters ---------- c : float / numpy array Concentration of halo z : float / numpy array Redshift of halo with concentration c Ascaling : float Cosmological dependent scaling between densities, use function getAscaling('WMAP5') if unsure. Default is 900. omega_M_0 : float Mass density of the universe. Default is 0.25 omega_lambda_0 : float Dark Energy density of the universe. Default is 0.75 Returns ------- zf : float / numpy array Formation redshift for halo of concentration 'c' at redshift 'z' """ Y1 = np.log(2) - 0.5 Yc = np.log(1+c) - c/(1+c) rho_2 = 200*(c**3)*Y1/Yc zf = (((1+z)**3 + omega_lambda_0/omega_M_0) * (rho_2/Ascaling) - omega_lambda_0/omega_M_0)**(1/3) - 1 return(zf)

Rearrange eqn 18 from Correa et al (2015c) to return formation redshift for a concentration at a given redshift Parameters ---------- c : float / numpy array Concentration of halo z : float / numpy array Redshift of halo with concentration c Ascaling : float Cosmological dependent scaling between densities, use function getAscaling('WMAP5') if unsure. Default is 900. omega_M_0 : float Mass density of the universe. Default is 0.25 omega_lambda_0 : float Dark Energy density of the universe. Default is 0.75 Returns ------- zf : float / numpy array Formation redshift for halo of concentration 'c' at redshift 'z'

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L315-L346

astroduff/commah

commah/commah.py

calc_ab

def calc_ab(zi, Mi, **cosmo): """ Calculate growth rate indices a_tilde and b_tilde Parameters ---------- zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (a_tilde, b_tilde) : float """ # When zi = 0, the a_tilde becomes alpha and b_tilde becomes beta # Eqn 23 of Correa et al 2015a (analytically solve from Eqn 16 and 17) # Arbitray formation redshift, z_-2 in COM is more physically motivated zf = -0.0064 * (np.log10(Mi))**2 + 0.0237 * (np.log10(Mi)) + 1.8837 # Eqn 22 of Correa et al 2015a q = 4.137 * zf**(-0.9476) # Radius of a mass Mi R_Mass = cp.perturbation.mass_to_radius(Mi, **cosmo) # [Mpc] # Radius of a mass Mi/q Rq_Mass = cp.perturbation.mass_to_radius(Mi/q, **cosmo) # [Mpc] # Mass variance 'sigma' evaluate at z=0 to a good approximation sig, err_sig = cp.perturbation.sigma_r(R_Mass, 0, **cosmo) # [Mpc] sigq, err_sigq = cp.perturbation.sigma_r(Rq_Mass, 0, **cosmo) # [Mpc] f = (sigq**2 - sig**2)**(-0.5) # Eqn 9 and 10 from Correa et al 2015c # (generalised to zi from Correa et al 2015a's z=0 special case) # a_tilde is power law growth rate a_tilde = (np.sqrt(2/np.pi) * 1.686 * _deriv_growth(zi, **cosmo) / growthfactor(zi, norm=True, **cosmo)**2 + 1)*f # b_tilde is exponential growth rate b_tilde = -f return(a_tilde, b_tilde)

python

def calc_ab(zi, Mi, **cosmo): """ Calculate growth rate indices a_tilde and b_tilde Parameters ---------- zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (a_tilde, b_tilde) : float """ # When zi = 0, the a_tilde becomes alpha and b_tilde becomes beta # Eqn 23 of Correa et al 2015a (analytically solve from Eqn 16 and 17) # Arbitray formation redshift, z_-2 in COM is more physically motivated zf = -0.0064 * (np.log10(Mi))**2 + 0.0237 * (np.log10(Mi)) + 1.8837 # Eqn 22 of Correa et al 2015a q = 4.137 * zf**(-0.9476) # Radius of a mass Mi R_Mass = cp.perturbation.mass_to_radius(Mi, **cosmo) # [Mpc] # Radius of a mass Mi/q Rq_Mass = cp.perturbation.mass_to_radius(Mi/q, **cosmo) # [Mpc] # Mass variance 'sigma' evaluate at z=0 to a good approximation sig, err_sig = cp.perturbation.sigma_r(R_Mass, 0, **cosmo) # [Mpc] sigq, err_sigq = cp.perturbation.sigma_r(Rq_Mass, 0, **cosmo) # [Mpc] f = (sigq**2 - sig**2)**(-0.5) # Eqn 9 and 10 from Correa et al 2015c # (generalised to zi from Correa et al 2015a's z=0 special case) # a_tilde is power law growth rate a_tilde = (np.sqrt(2/np.pi) * 1.686 * _deriv_growth(zi, **cosmo) / growthfactor(zi, norm=True, **cosmo)**2 + 1)*f # b_tilde is exponential growth rate b_tilde = -f return(a_tilde, b_tilde)

Calculate growth rate indices a_tilde and b_tilde Parameters ---------- zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (a_tilde, b_tilde) : float

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L349-L397

astroduff/commah

commah/commah.py

acc_rate

def acc_rate(z, zi, Mi, **cosmo): """ Calculate accretion rate and mass history of a halo at any redshift 'z' with mass 'Mi' at a lower redshift 'z' Parameters ---------- z : float Redshift to solve acc_rate / mass history. Note zi<z zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z' """ # Find parameters a_tilde and b_tilde for initial redshift # use Eqn 9 and 10 of Correa et al. (2015c) a_tilde, b_tilde = calc_ab(zi, Mi, **cosmo) # Halo mass at z, in Msol # use Eqn 8 in Correa et al. (2015c) Mz = Mi * ((1 + z - zi)**a_tilde) * (np.exp(b_tilde * (z - zi))) # Accretion rate at z, Msol yr^-1 # use Eqn 11 from Correa et al. (2015c) dMdt = 71.6 * (Mz/1e12) * (cosmo['h']/0.7) *\ (-a_tilde / (1 + z - zi) - b_tilde) * (1 + z) *\ np.sqrt(cosmo['omega_M_0']*(1 + z)**3+cosmo['omega_lambda_0']) return(dMdt, Mz)

python

def acc_rate(z, zi, Mi, **cosmo): """ Calculate accretion rate and mass history of a halo at any redshift 'z' with mass 'Mi' at a lower redshift 'z' Parameters ---------- z : float Redshift to solve acc_rate / mass history. Note zi<z zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z' """ # Find parameters a_tilde and b_tilde for initial redshift # use Eqn 9 and 10 of Correa et al. (2015c) a_tilde, b_tilde = calc_ab(zi, Mi, **cosmo) # Halo mass at z, in Msol # use Eqn 8 in Correa et al. (2015c) Mz = Mi * ((1 + z - zi)**a_tilde) * (np.exp(b_tilde * (z - zi))) # Accretion rate at z, Msol yr^-1 # use Eqn 11 from Correa et al. (2015c) dMdt = 71.6 * (Mz/1e12) * (cosmo['h']/0.7) *\ (-a_tilde / (1 + z - zi) - b_tilde) * (1 + z) *\ np.sqrt(cosmo['omega_M_0']*(1 + z)**3+cosmo['omega_lambda_0']) return(dMdt, Mz)

Calculate accretion rate and mass history of a halo at any redshift 'z' with mass 'Mi' at a lower redshift 'z' Parameters ---------- z : float Redshift to solve acc_rate / mass history. Note zi<z zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z'

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L400-L438

astroduff/commah

commah/commah.py

MAH

def MAH(z, zi, Mi, **cosmo): """ Calculate mass accretion history by looping function acc_rate over redshift steps 'z' for halo of mass 'Mi' at redshift 'zi' Parameters ---------- z : float / numpy array Redshift to output MAH over. Note zi<z always zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float / numpy arrays of equivalent size to 'z' Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z' """ # Ensure that z is a 1D NumPy array z = np.array(z, ndmin=1, dtype=float) # Create a full array dMdt_array = np.empty_like(z) Mz_array = np.empty_like(z) for i_ind, zval in enumerate(z): # Solve the accretion rate and halo mass at each redshift step dMdt, Mz = acc_rate(zval, zi, Mi, **cosmo) dMdt_array[i_ind] = dMdt Mz_array[i_ind] = Mz return(dMdt_array, Mz_array)

python

def MAH(z, zi, Mi, **cosmo): """ Calculate mass accretion history by looping function acc_rate over redshift steps 'z' for halo of mass 'Mi' at redshift 'zi' Parameters ---------- z : float / numpy array Redshift to output MAH over. Note zi<z always zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float / numpy arrays of equivalent size to 'z' Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z' """ # Ensure that z is a 1D NumPy array z = np.array(z, ndmin=1, dtype=float) # Create a full array dMdt_array = np.empty_like(z) Mz_array = np.empty_like(z) for i_ind, zval in enumerate(z): # Solve the accretion rate and halo mass at each redshift step dMdt, Mz = acc_rate(zval, zi, Mi, **cosmo) dMdt_array[i_ind] = dMdt Mz_array[i_ind] = Mz return(dMdt_array, Mz_array)

Calculate mass accretion history by looping function acc_rate over redshift steps 'z' for halo of mass 'Mi' at redshift 'zi' Parameters ---------- z : float / numpy array Redshift to output MAH over. Note zi<z always zi : float Redshift Mi : float Halo mass at redshift 'zi' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (dMdt, Mz) : float / numpy arrays of equivalent size to 'z' Accretion rate [Msol/yr], halo mass [Msol] at redshift 'z'

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L441-L480

astroduff/commah

commah/commah.py

COM

def COM(z, M, **cosmo): """ Calculate concentration for halo of mass 'M' at redshift 'z' Parameters ---------- z : float / numpy array Redshift to find concentration of halo M : float / numpy array Halo mass at redshift 'z'. Must be same size as 'z' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (c_array, sig_array, nu_array, zf_array) : float / numpy arrays of equivalent size to 'z' and 'M'. Variables are Concentration, Mass Variance 'sigma' this corresponds too, the dimnesionless fluctuation this represents and formation redshift """ # Check that z and M are arrays z = np.array(z, ndmin=1, dtype=float) M = np.array(M, ndmin=1, dtype=float) # Create array c_array = np.empty_like(z) sig_array = np.empty_like(z) nu_array = np.empty_like(z) zf_array = np.empty_like(z) for i_ind, (zval, Mval) in enumerate(_izip(z, M)): # Evaluate the indices at each redshift and mass combination # that you want a concentration for, different to MAH which # uses one a_tilde and b_tilde at the starting redshift only a_tilde, b_tilde = calc_ab(zval, Mval, **cosmo) # Minimize equation to solve for 1 unknown, 'c' c = scipy.optimize.brentq(_minimize_c, 2, 1000, args=(zval, a_tilde, b_tilde, cosmo['A_scaling'], cosmo['omega_M_0'], cosmo['omega_lambda_0'])) if np.isclose(c, 0): print("Error solving for concentration with given redshift and " "(probably) too small a mass") c = -1 sig = -1 nu = -1 zf = -1 else: # Calculate formation redshift for this concentration, # redshift at which the scale radius = virial radius: z_-2 zf = formationz(c, zval, Ascaling=cosmo['A_scaling'], omega_M_0=cosmo['omega_M_0'], omega_lambda_0=cosmo['omega_lambda_0']) R_Mass = cp.perturbation.mass_to_radius(Mval, **cosmo) sig, err_sig = cp.perturbation.sigma_r(R_Mass, 0, **cosmo) nu = 1.686/(sig*growthfactor(zval, norm=True, **cosmo)) c_array[i_ind] = c sig_array[i_ind] = sig nu_array[i_ind] = nu zf_array[i_ind] = zf return(c_array, sig_array, nu_array, zf_array)

python

def COM(z, M, **cosmo): """ Calculate concentration for halo of mass 'M' at redshift 'z' Parameters ---------- z : float / numpy array Redshift to find concentration of halo M : float / numpy array Halo mass at redshift 'z'. Must be same size as 'z' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (c_array, sig_array, nu_array, zf_array) : float / numpy arrays of equivalent size to 'z' and 'M'. Variables are Concentration, Mass Variance 'sigma' this corresponds too, the dimnesionless fluctuation this represents and formation redshift """ # Check that z and M are arrays z = np.array(z, ndmin=1, dtype=float) M = np.array(M, ndmin=1, dtype=float) # Create array c_array = np.empty_like(z) sig_array = np.empty_like(z) nu_array = np.empty_like(z) zf_array = np.empty_like(z) for i_ind, (zval, Mval) in enumerate(_izip(z, M)): # Evaluate the indices at each redshift and mass combination # that you want a concentration for, different to MAH which # uses one a_tilde and b_tilde at the starting redshift only a_tilde, b_tilde = calc_ab(zval, Mval, **cosmo) # Minimize equation to solve for 1 unknown, 'c' c = scipy.optimize.brentq(_minimize_c, 2, 1000, args=(zval, a_tilde, b_tilde, cosmo['A_scaling'], cosmo['omega_M_0'], cosmo['omega_lambda_0'])) if np.isclose(c, 0): print("Error solving for concentration with given redshift and " "(probably) too small a mass") c = -1 sig = -1 nu = -1 zf = -1 else: # Calculate formation redshift for this concentration, # redshift at which the scale radius = virial radius: z_-2 zf = formationz(c, zval, Ascaling=cosmo['A_scaling'], omega_M_0=cosmo['omega_M_0'], omega_lambda_0=cosmo['omega_lambda_0']) R_Mass = cp.perturbation.mass_to_radius(Mval, **cosmo) sig, err_sig = cp.perturbation.sigma_r(R_Mass, 0, **cosmo) nu = 1.686/(sig*growthfactor(zval, norm=True, **cosmo)) c_array[i_ind] = c sig_array[i_ind] = sig nu_array[i_ind] = nu zf_array[i_ind] = zf return(c_array, sig_array, nu_array, zf_array)

Calculate concentration for halo of mass 'M' at redshift 'z' Parameters ---------- z : float / numpy array Redshift to find concentration of halo M : float / numpy array Halo mass at redshift 'z'. Must be same size as 'z' cosmo : dict Dictionary of cosmological parameters, similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} Returns ------- (c_array, sig_array, nu_array, zf_array) : float / numpy arrays of equivalent size to 'z' and 'M'. Variables are Concentration, Mass Variance 'sigma' this corresponds too, the dimnesionless fluctuation this represents and formation redshift

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L483-L552

astroduff/commah

commah/commah.py

run

def run(cosmology, zi=0, Mi=1e12, z=False, com=True, mah=True, filename=None, verbose=None, retcosmo=None): """ Run commah code on halo of mass 'Mi' at redshift 'zi' with accretion and profile history at higher redshifts 'z' This is based on Correa et al. (2015a,b,c) Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} zi : float / numpy array, optional Redshift at which halo has mass 'Mi'. If float then all halo masses 'Mi' are assumed to be at this redshift. If array but Mi is float, then this halo mass is used across all starting redshifts. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 0. Mi : float / numpy array, optional Halo mass 'Mi' at a redshift 'zi'. If float then all redshifts 'zi' are solved for this halo mass. If array but zi is float, then this redshift is applied to all halo masses. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 1e12 Msol. z : float / numpy array, optional Redshift to solve commah code at. Must have zi<z else these steps are skipped. Default is False, meaning commah is solved at z=zi com : bool, optional If true then solve for concentration-mass, default is True. mah : bool, optional If true then solve for accretion rate and halo mass history, default is True. filename : bool / str, optional If str is passed this is used as a filename for output of commah verbose : bool, optional If true then give comments, default is None. retcosmo : bool, optional Return cosmological parameters used as a dict if retcosmo = True, default is None. Returns ------- dataset : structured dataset dataset contains structured columns of size (size(Mi) > size(z)) by size(z) If mah = True and com = False then columns are ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'dMdt' is accretion rate [Msol/yr] and 'Mz' is the halo mass at 'z' for a halo which was 'Mi' massive at starting redshift 'zi' If mah = False and com = True then columns are ('zi',float),('Mi',float),('z',float),('c',float),('sig',float),('nu',float),('zf',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'c' is NFW concentration of halo at the redshift 'z', 'sig' is the mass variance 'sigma', 'nu' is the dimensionless fluctuation for halo mass 'Mi' at 'zi', 'zf' is the formation redshift for a halo of mass 'Mi' at redshift 'zi' If mah = True and com = True then columns are: ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float), ('c',float),('sig',float),('nu',float),('zf',float) file : structured dataset with name 'filename' if passed Raises ------ Output -1 If com = False and mah = False as user has to select something. Output -1 If 'zi' and 'Mi' are arrays of unequal size. Impossible to match corresponding masses and redshifts of output. Examples -------- Examples should be written in doctest format, and should illustrate how to use the function. >>> import examples >>> examples.runcommands() # A series of ways to query structured dataset >>> examples.plotcommands() # Examples to plot data """ # Check user choices... if not com and not mah: print("User has to choose com=True and / or mah=True ") return(-1) # Convert arrays / lists to np.array # and inflate redshift / mass axis # to match each other for later loop results = _checkinput(zi, Mi, z=z, verbose=verbose) # Return if results is -1 if(results == -1): return(-1) # If not, unpack the returned iterable else: zi, Mi, z, lenz, lenm, lenzout = results # At this point we will have lenm objects to iterate over # Get the cosmological parameters for the given cosmology cosmo = getcosmo(cosmology) # Create output file if desired if filename: print("Output to file %r" % (filename)) fout = open(filename, 'wb') # Create the structured dataset try: if mah and com: if verbose: print("Output requested is zi, Mi, z, dMdt, Mz, c, sig, nu, " "zf") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z - " " Accretion - Final Halo - concentration - " " Mass - Peak - Formation z "+'\n') fout.write("# - mass - -" " rate - mass - - " " Variance - Height - "+'\n') fout.write("# - (M200) - - " " (dM/dt) - (M200) - - " " (sigma) - (nu) - "+'\n') fout.write("# - [Msol] - - " " [Msol/yr] - [Msol] - - " " - - "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('dMdt', float), ('Mz', float), ('c', float), ('sig', float), ('nu', float), ('zf', float)]) elif mah: if verbose: print("Output requested is zi, Mi, z, dMdt, Mz") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z -" " Accretion - Final Halo "+'\n') fout.write("# - mass - -" " rate - mass "+'\n') fout.write("# - (M200) - -" " (dm/dt) - (M200) "+'\n') fout.write("# - [Msol] - -" " [Msol/yr] - [Msol] "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('dMdt', float), ('Mz', float)]) else: if verbose: print("Output requested is zi, Mi, z, c, sig, nu, zf") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z - " " concentration - " " Mass - Peak - Formation z "+'\n') fout.write("# - mass - -" " -" " Variance - Height - "+'\n') fout.write("# - (M200) - - " " - " " (sigma) - (nu) - "+'\n') fout.write("# - [Msol] - - " " - " " - - "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('c', float), ('sig', float), ('nu', float), ('zf', float)]) # Now loop over the combination of initial redshift and halo mamss for i_ind, (zval, Mval) in enumerate(_izip(zi, Mi)): if verbose: print("Output Halo of Mass Mi=%s at zi=%s" % (Mval, zval)) # For a given halo mass Mi at redshift zi need to know # output redshifts 'z' # Check that all requested redshifts are greater than # input redshift, except if z is False, in which case # only solve z at zi, i.e. remove a loop if z is False: ztemp = np.array(zval, ndmin=1, dtype=float) else: ztemp = np.array(z[z >= zval], dtype=float) # Loop over the output redshifts if ztemp.size: # Return accretion rates and halo mass progenitors at # redshifts 'z' for object of mass Mi at zi dMdt, Mz = MAH(ztemp, zval, Mval, **cosmo) if mah and com: # More expensive to return concentrations c, sig, nu, zf = COM(ztemp, Mz, **cosmo) # Save all arrays for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind]) if filename: fout.write( "{}, {}, {}, {}, {}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind])) elif mah: # Save only MAH arrays for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind]) if filename: fout.write("{}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind])) else: # Output only COM arrays c, sig, nu, zf = COM(ztemp, Mz, **cosmo) # For any halo mass Mi at redshift zi # solve for c, sig, nu and zf for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind]) if filename: fout.write("{}, {}, {}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind])) # Make sure to close the file if it was opened finally: fout.close() if filename else None if retcosmo: return(dataset, cosmo) else: return(dataset)

python

def run(cosmology, zi=0, Mi=1e12, z=False, com=True, mah=True, filename=None, verbose=None, retcosmo=None): """ Run commah code on halo of mass 'Mi' at redshift 'zi' with accretion and profile history at higher redshifts 'z' This is based on Correa et al. (2015a,b,c) Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} zi : float / numpy array, optional Redshift at which halo has mass 'Mi'. If float then all halo masses 'Mi' are assumed to be at this redshift. If array but Mi is float, then this halo mass is used across all starting redshifts. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 0. Mi : float / numpy array, optional Halo mass 'Mi' at a redshift 'zi'. If float then all redshifts 'zi' are solved for this halo mass. If array but zi is float, then this redshift is applied to all halo masses. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 1e12 Msol. z : float / numpy array, optional Redshift to solve commah code at. Must have zi<z else these steps are skipped. Default is False, meaning commah is solved at z=zi com : bool, optional If true then solve for concentration-mass, default is True. mah : bool, optional If true then solve for accretion rate and halo mass history, default is True. filename : bool / str, optional If str is passed this is used as a filename for output of commah verbose : bool, optional If true then give comments, default is None. retcosmo : bool, optional Return cosmological parameters used as a dict if retcosmo = True, default is None. Returns ------- dataset : structured dataset dataset contains structured columns of size (size(Mi) > size(z)) by size(z) If mah = True and com = False then columns are ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'dMdt' is accretion rate [Msol/yr] and 'Mz' is the halo mass at 'z' for a halo which was 'Mi' massive at starting redshift 'zi' If mah = False and com = True then columns are ('zi',float),('Mi',float),('z',float),('c',float),('sig',float),('nu',float),('zf',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'c' is NFW concentration of halo at the redshift 'z', 'sig' is the mass variance 'sigma', 'nu' is the dimensionless fluctuation for halo mass 'Mi' at 'zi', 'zf' is the formation redshift for a halo of mass 'Mi' at redshift 'zi' If mah = True and com = True then columns are: ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float), ('c',float),('sig',float),('nu',float),('zf',float) file : structured dataset with name 'filename' if passed Raises ------ Output -1 If com = False and mah = False as user has to select something. Output -1 If 'zi' and 'Mi' are arrays of unequal size. Impossible to match corresponding masses and redshifts of output. Examples -------- Examples should be written in doctest format, and should illustrate how to use the function. >>> import examples >>> examples.runcommands() # A series of ways to query structured dataset >>> examples.plotcommands() # Examples to plot data """ # Check user choices... if not com and not mah: print("User has to choose com=True and / or mah=True ") return(-1) # Convert arrays / lists to np.array # and inflate redshift / mass axis # to match each other for later loop results = _checkinput(zi, Mi, z=z, verbose=verbose) # Return if results is -1 if(results == -1): return(-1) # If not, unpack the returned iterable else: zi, Mi, z, lenz, lenm, lenzout = results # At this point we will have lenm objects to iterate over # Get the cosmological parameters for the given cosmology cosmo = getcosmo(cosmology) # Create output file if desired if filename: print("Output to file %r" % (filename)) fout = open(filename, 'wb') # Create the structured dataset try: if mah and com: if verbose: print("Output requested is zi, Mi, z, dMdt, Mz, c, sig, nu, " "zf") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z - " " Accretion - Final Halo - concentration - " " Mass - Peak - Formation z "+'\n') fout.write("# - mass - -" " rate - mass - - " " Variance - Height - "+'\n') fout.write("# - (M200) - - " " (dM/dt) - (M200) - - " " (sigma) - (nu) - "+'\n') fout.write("# - [Msol] - - " " [Msol/yr] - [Msol] - - " " - - "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('dMdt', float), ('Mz', float), ('c', float), ('sig', float), ('nu', float), ('zf', float)]) elif mah: if verbose: print("Output requested is zi, Mi, z, dMdt, Mz") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z -" " Accretion - Final Halo "+'\n') fout.write("# - mass - -" " rate - mass "+'\n') fout.write("# - (M200) - -" " (dm/dt) - (M200) "+'\n') fout.write("# - [Msol] - -" " [Msol/yr] - [Msol] "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('dMdt', float), ('Mz', float)]) else: if verbose: print("Output requested is zi, Mi, z, c, sig, nu, zf") if filename: fout.write(_getcosmoheader(cosmo)+'\n') fout.write("# Initial z - Initial Halo - Output z - " " concentration - " " Mass - Peak - Formation z "+'\n') fout.write("# - mass - -" " -" " Variance - Height - "+'\n') fout.write("# - (M200) - - " " - " " (sigma) - (nu) - "+'\n') fout.write("# - [Msol] - - " " - " " - - "+'\n') dataset = np.zeros((lenm, lenzout), dtype=[('zi', float), ('Mi', float), ('z', float), ('c', float), ('sig', float), ('nu', float), ('zf', float)]) # Now loop over the combination of initial redshift and halo mamss for i_ind, (zval, Mval) in enumerate(_izip(zi, Mi)): if verbose: print("Output Halo of Mass Mi=%s at zi=%s" % (Mval, zval)) # For a given halo mass Mi at redshift zi need to know # output redshifts 'z' # Check that all requested redshifts are greater than # input redshift, except if z is False, in which case # only solve z at zi, i.e. remove a loop if z is False: ztemp = np.array(zval, ndmin=1, dtype=float) else: ztemp = np.array(z[z >= zval], dtype=float) # Loop over the output redshifts if ztemp.size: # Return accretion rates and halo mass progenitors at # redshifts 'z' for object of mass Mi at zi dMdt, Mz = MAH(ztemp, zval, Mval, **cosmo) if mah and com: # More expensive to return concentrations c, sig, nu, zf = COM(ztemp, Mz, **cosmo) # Save all arrays for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind]) if filename: fout.write( "{}, {}, {}, {}, {}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind])) elif mah: # Save only MAH arrays for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind]) if filename: fout.write("{}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], dMdt[j_ind], Mz[j_ind])) else: # Output only COM arrays c, sig, nu, zf = COM(ztemp, Mz, **cosmo) # For any halo mass Mi at redshift zi # solve for c, sig, nu and zf for j_ind, j_val in enumerate(ztemp): dataset[i_ind, j_ind] =\ (zval, Mval, ztemp[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind]) if filename: fout.write("{}, {}, {}, {}, {}, {}, {} \n".format( zval, Mval, ztemp[j_ind], c[j_ind], sig[j_ind], nu[j_ind], zf[j_ind])) # Make sure to close the file if it was opened finally: fout.close() if filename else None if retcosmo: return(dataset, cosmo) else: return(dataset)

Run commah code on halo of mass 'Mi' at redshift 'zi' with accretion and profile history at higher redshifts 'z' This is based on Correa et al. (2015a,b,c) Parameters ---------- cosmology : str or dict Can be named cosmology, default WMAP7 (aka DRAGONS), or DRAGONS, WMAP1, WMAP3, WMAP5, WMAP7, WMAP9, Planck13, Planck15 or dictionary similar in format to: {'N_nu': 0,'Y_He': 0.24, 'h': 0.702, 'n': 0.963,'omega_M_0': 0.275, 'omega_b_0': 0.0458,'omega_lambda_0': 0.725,'omega_n_0': 0.0, 'sigma_8': 0.816, 't_0': 13.76, 'tau': 0.088,'z_reion': 10.6} zi : float / numpy array, optional Redshift at which halo has mass 'Mi'. If float then all halo masses 'Mi' are assumed to be at this redshift. If array but Mi is float, then this halo mass is used across all starting redshifts. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 0. Mi : float / numpy array, optional Halo mass 'Mi' at a redshift 'zi'. If float then all redshifts 'zi' are solved for this halo mass. If array but zi is float, then this redshift is applied to all halo masses. If both Mi and zi are arrays then they have to be the same size for one - to - one correspondence between halo mass and the redshift at which it has that mass. Default is 1e12 Msol. z : float / numpy array, optional Redshift to solve commah code at. Must have zi<z else these steps are skipped. Default is False, meaning commah is solved at z=zi com : bool, optional If true then solve for concentration-mass, default is True. mah : bool, optional If true then solve for accretion rate and halo mass history, default is True. filename : bool / str, optional If str is passed this is used as a filename for output of commah verbose : bool, optional If true then give comments, default is None. retcosmo : bool, optional Return cosmological parameters used as a dict if retcosmo = True, default is None. Returns ------- dataset : structured dataset dataset contains structured columns of size (size(Mi) > size(z)) by size(z) If mah = True and com = False then columns are ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'dMdt' is accretion rate [Msol/yr] and 'Mz' is the halo mass at 'z' for a halo which was 'Mi' massive at starting redshift 'zi' If mah = False and com = True then columns are ('zi',float),('Mi',float),('z',float),('c',float),('sig',float),('nu',float),('zf',float) where 'zi' is the starting redshift, 'Mi' is halo mass at zi 'z' is output redshift (NB z>zi), 'c' is NFW concentration of halo at the redshift 'z', 'sig' is the mass variance 'sigma', 'nu' is the dimensionless fluctuation for halo mass 'Mi' at 'zi', 'zf' is the formation redshift for a halo of mass 'Mi' at redshift 'zi' If mah = True and com = True then columns are: ('zi',float),('Mi',float),('z',float),('dMdt',float),('Mz',float), ('c',float),('sig',float),('nu',float),('zf',float) file : structured dataset with name 'filename' if passed Raises ------ Output -1 If com = False and mah = False as user has to select something. Output -1 If 'zi' and 'Mi' are arrays of unequal size. Impossible to match corresponding masses and redshifts of output. Examples -------- Examples should be written in doctest format, and should illustrate how to use the function. >>> import examples >>> examples.runcommands() # A series of ways to query structured dataset >>> examples.plotcommands() # Examples to plot data

train

https://github.com/astroduff/commah/blob/3ec70338c5123a053c79ddcf2cb3beac26bc9137/commah/commah.py#L555-L799

MatterMiners/cobald

cobald/daemon/core/config.py

load

def load(config_path: str): """ Load a configuration and keep it alive for the given context :param config_path: path to a configuration file """ # we bind the config to _ to keep it alive if os.path.splitext(config_path)[1] in ('.yaml', '.yml'): _ = load_yaml_configuration(config_path, translator=PipelineTranslator()) elif os.path.splitext(config_path)[1] == '.py': _ = load_python_configuration(config_path) else: raise ValueError('Unknown configuration extension: %r' % os.path.splitext(config_path)[1]) yield

python

def load(config_path: str): """ Load a configuration and keep it alive for the given context :param config_path: path to a configuration file """ # we bind the config to _ to keep it alive if os.path.splitext(config_path)[1] in ('.yaml', '.yml'): _ = load_yaml_configuration(config_path, translator=PipelineTranslator()) elif os.path.splitext(config_path)[1] == '.py': _ = load_python_configuration(config_path) else: raise ValueError('Unknown configuration extension: %r' % os.path.splitext(config_path)[1]) yield

Load a configuration and keep it alive for the given context :param config_path: path to a configuration file

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/core/config.py#L10-L23

aroberge/experimental

experimental/transformers/repeat_keyword.py

transform_source

def transform_source(text): '''Replaces instances of repeat n: by for __VAR_i in range(n): where __VAR_i is a string that does not appear elsewhere in the code sample. ''' loop_keyword = 'repeat' nb = text.count(loop_keyword) if nb == 0: return text var_names = get_unique_variable_names(text, nb) toks = tokenize.generate_tokens(StringIO(text).readline) result = [] replacing_keyword = False for toktype, tokvalue, _, _, _ in toks: if toktype == tokenize.NAME and tokvalue == loop_keyword: result.extend([ (tokenize.NAME, 'for'), (tokenize.NAME, var_names.pop()), (tokenize.NAME, 'in'), (tokenize.NAME, 'range'), (tokenize.OP, '(') ]) replacing_keyword = True elif replacing_keyword and tokvalue == ':': result.extend([ (tokenize.OP, ')'), (tokenize.OP, ':') ]) replacing_keyword = False else: result.append((toktype, tokvalue)) return tokenize.untokenize(result)

python

def transform_source(text): '''Replaces instances of repeat n: by for __VAR_i in range(n): where __VAR_i is a string that does not appear elsewhere in the code sample. ''' loop_keyword = 'repeat' nb = text.count(loop_keyword) if nb == 0: return text var_names = get_unique_variable_names(text, nb) toks = tokenize.generate_tokens(StringIO(text).readline) result = [] replacing_keyword = False for toktype, tokvalue, _, _, _ in toks: if toktype == tokenize.NAME and tokvalue == loop_keyword: result.extend([ (tokenize.NAME, 'for'), (tokenize.NAME, var_names.pop()), (tokenize.NAME, 'in'), (tokenize.NAME, 'range'), (tokenize.OP, '(') ]) replacing_keyword = True elif replacing_keyword and tokvalue == ':': result.extend([ (tokenize.OP, ')'), (tokenize.OP, ':') ]) replacing_keyword = False else: result.append((toktype, tokvalue)) return tokenize.untokenize(result)

Replaces instances of repeat n: by for __VAR_i in range(n): where __VAR_i is a string that does not appear elsewhere in the code sample.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/transformers/repeat_keyword.py#L29-L70

aroberge/experimental

experimental/transformers/repeat_keyword.py

get_unique_variable_names

def get_unique_variable_names(text, nb): '''returns a list of possible variables names that are not found in the original text.''' base_name = '__VAR_' var_names = [] i = 0 j = 0 while j < nb: tentative_name = base_name + str(i) if text.count(tentative_name) == 0 and tentative_name not in ALL_NAMES: var_names.append(tentative_name) ALL_NAMES.append(tentative_name) j += 1 i += 1 return var_names

python

def get_unique_variable_names(text, nb): '''returns a list of possible variables names that are not found in the original text.''' base_name = '__VAR_' var_names = [] i = 0 j = 0 while j < nb: tentative_name = base_name + str(i) if text.count(tentative_name) == 0 and tentative_name not in ALL_NAMES: var_names.append(tentative_name) ALL_NAMES.append(tentative_name) j += 1 i += 1 return var_names

returns a list of possible variables names that are not found in the original text.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/transformers/repeat_keyword.py#L75-L89

quantmind/agile-toolkit

agiletoolkit/api/releases.py

Releases.tag

def tag(self, tag): """Get a release by tag """ url = '%s/tags/%s' % (self, tag) response = self.http.get(url, auth=self.auth) response.raise_for_status() return response.json()

python

def tag(self, tag): """Get a release by tag """ url = '%s/tags/%s' % (self, tag) response = self.http.get(url, auth=self.auth) response.raise_for_status() return response.json()

Get a release by tag

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/api/releases.py#L37-L43

quantmind/agile-toolkit

agiletoolkit/api/releases.py

Releases.release_assets

def release_assets(self, release): """Assets for a given release """ release = self.as_id(release) return self.get_list(url='%s/%s/assets' % (self, release))

python

def release_assets(self, release): """Assets for a given release """ release = self.as_id(release) return self.get_list(url='%s/%s/assets' % (self, release))

Assets for a given release

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/api/releases.py#L53-L57

quantmind/agile-toolkit

agiletoolkit/api/releases.py

Releases.upload

def upload(self, release, filename, content_type=None): """Upload a file to a release :param filename: filename to upload :param content_type: optional content type :return: json object from github """ release = self.as_id(release) name = os.path.basename(filename) if not content_type: content_type, _ = mimetypes.guess_type(name) if not content_type: raise ValueError('content_type not known') inputs = {'name': name} url = '%s%s/%s/assets' % (self.uploads_url, urlsplit(self.api_url).path, release) info = os.stat(filename) size = info[stat.ST_SIZE] response = self.http.post( url, data=stream_upload(filename), auth=self.auth, params=inputs, headers={'content-type': content_type, 'content-length': str(size)}) response.raise_for_status() return response.json()

python

def upload(self, release, filename, content_type=None): """Upload a file to a release :param filename: filename to upload :param content_type: optional content type :return: json object from github """ release = self.as_id(release) name = os.path.basename(filename) if not content_type: content_type, _ = mimetypes.guess_type(name) if not content_type: raise ValueError('content_type not known') inputs = {'name': name} url = '%s%s/%s/assets' % (self.uploads_url, urlsplit(self.api_url).path, release) info = os.stat(filename) size = info[stat.ST_SIZE] response = self.http.post( url, data=stream_upload(filename), auth=self.auth, params=inputs, headers={'content-type': content_type, 'content-length': str(size)}) response.raise_for_status() return response.json()

Upload a file to a release :param filename: filename to upload :param content_type: optional content type :return: json object from github

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/api/releases.py#L59-L84

quantmind/agile-toolkit

agiletoolkit/api/releases.py

Releases.validate_tag

def validate_tag(self, tag_name, prefix=None): """Validate ``tag_name`` with the latest tag from github If ``tag_name`` is a valid candidate, return the latest tag from github """ new_version = semantic_version(tag_name) current = self.latest() if current: tag_name = current['tag_name'] if prefix: tag_name = tag_name[len(prefix):] tag_name = semantic_version(tag_name) if tag_name >= new_version: what = 'equal to' if tag_name == new_version else 'older than' raise GithubException( 'Your local version "%s" is %s ' 'the current github version "%s".\n' 'Bump the local version to ' 'continue.' % ( str(new_version), what, str(tag_name) ) ) return current

python

def validate_tag(self, tag_name, prefix=None): """Validate ``tag_name`` with the latest tag from github If ``tag_name`` is a valid candidate, return the latest tag from github """ new_version = semantic_version(tag_name) current = self.latest() if current: tag_name = current['tag_name'] if prefix: tag_name = tag_name[len(prefix):] tag_name = semantic_version(tag_name) if tag_name >= new_version: what = 'equal to' if tag_name == new_version else 'older than' raise GithubException( 'Your local version "%s" is %s ' 'the current github version "%s".\n' 'Bump the local version to ' 'continue.' % ( str(new_version), what, str(tag_name) ) ) return current

Validate ``tag_name`` with the latest tag from github If ``tag_name`` is a valid candidate, return the latest tag from github

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/api/releases.py#L86-L111

teaearlgraycold/puni

puni/base.py

Note.full_url

def full_url(self): """Return the full reddit URL associated with the usernote. Arguments: subreddit: the subreddit name for the note (PRAW Subreddit object) """ if self.link == '': return None else: return Note._expand_url(self.link, self.subreddit)

python

def full_url(self): """Return the full reddit URL associated with the usernote. Arguments: subreddit: the subreddit name for the note (PRAW Subreddit object) """ if self.link == '': return None else: return Note._expand_url(self.link, self.subreddit)

Return the full reddit URL associated with the usernote. Arguments: subreddit: the subreddit name for the note (PRAW Subreddit object)

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L87-L96

teaearlgraycold/puni

puni/base.py

Note._compress_url

def _compress_url(link): """Convert a reddit URL into the short-hand used by usernotes. Arguments: link: a link to a comment, submission, or message (str) Returns a String of the shorthand URL """ comment_re = re.compile(r'/comments/([A-Za-z\d]{2,})(?:/[^\s]+/([A-Za-z\d]+))?') message_re = re.compile(r'/message/messages/([A-Za-z\d]+)') matches = re.findall(comment_re, link) if len(matches) == 0: matches = re.findall(message_re, link) if len(matches) == 0: return None else: return 'm,' + matches[0] else: if matches[0][1] == '': return 'l,' + matches[0][0] else: return 'l,' + matches[0][0] + ',' + matches[0][1]

python

def _compress_url(link): """Convert a reddit URL into the short-hand used by usernotes. Arguments: link: a link to a comment, submission, or message (str) Returns a String of the shorthand URL """ comment_re = re.compile(r'/comments/([A-Za-z\d]{2,})(?:/[^\s]+/([A-Za-z\d]+))?') message_re = re.compile(r'/message/messages/([A-Za-z\d]+)') matches = re.findall(comment_re, link) if len(matches) == 0: matches = re.findall(message_re, link) if len(matches) == 0: return None else: return 'm,' + matches[0] else: if matches[0][1] == '': return 'l,' + matches[0][0] else: return 'l,' + matches[0][0] + ',' + matches[0][1]

Convert a reddit URL into the short-hand used by usernotes. Arguments: link: a link to a comment, submission, or message (str) Returns a String of the shorthand URL

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L99-L122

teaearlgraycold/puni

puni/base.py

Note._expand_url

def _expand_url(short_link, subreddit=None): """Convert a usernote's URL short-hand into a full reddit URL. Arguments: subreddit: the subreddit the URL is for (PRAW Subreddit object or str) short_link: the compressed link from a usernote (str) Returns a String of the full URL. """ # Some URL structures for notes message_scheme = 'https://reddit.com/message/messages/{}' comment_scheme = 'https://reddit.com/r/{}/comments/{}/-/{}' post_scheme = 'https://reddit.com/r/{}/comments/{}/' if short_link == '': return None else: parts = short_link.split(',') if parts[0] == 'm': return message_scheme.format(parts[1]) if parts[0] == 'l' and subreddit: if len(parts) > 2: return comment_scheme.format(subreddit, parts[1], parts[2]) else: return post_scheme.format(subreddit, parts[1]) elif not subreddit: raise ValueError('Subreddit name must be provided') else: return None

python

def _expand_url(short_link, subreddit=None): """Convert a usernote's URL short-hand into a full reddit URL. Arguments: subreddit: the subreddit the URL is for (PRAW Subreddit object or str) short_link: the compressed link from a usernote (str) Returns a String of the full URL. """ # Some URL structures for notes message_scheme = 'https://reddit.com/message/messages/{}' comment_scheme = 'https://reddit.com/r/{}/comments/{}/-/{}' post_scheme = 'https://reddit.com/r/{}/comments/{}/' if short_link == '': return None else: parts = short_link.split(',') if parts[0] == 'm': return message_scheme.format(parts[1]) if parts[0] == 'l' and subreddit: if len(parts) > 2: return comment_scheme.format(subreddit, parts[1], parts[2]) else: return post_scheme.format(subreddit, parts[1]) elif not subreddit: raise ValueError('Subreddit name must be provided') else: return None

Convert a usernote's URL short-hand into a full reddit URL. Arguments: subreddit: the subreddit the URL is for (PRAW Subreddit object or str) short_link: the compressed link from a usernote (str) Returns a String of the full URL.

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L125-L154

teaearlgraycold/puni

puni/base.py

UserNotes.get_json

def get_json(self): """Get the JSON stored on the usernotes wiki page. Returns a dict representation of the usernotes (with the notes BLOB decoded). Raises: RuntimeError if the usernotes version is incompatible with this version of puni. """ try: usernotes = self.subreddit.wiki[self.page_name].content_md notes = json.loads(usernotes) except NotFound: self._init_notes() else: if notes['ver'] != self.schema: raise RuntimeError( 'Usernotes schema is v{0}, puni requires v{1}'. format(notes['ver'], self.schema) ) self.cached_json = self._expand_json(notes) return self.cached_json

python

def get_json(self): """Get the JSON stored on the usernotes wiki page. Returns a dict representation of the usernotes (with the notes BLOB decoded). Raises: RuntimeError if the usernotes version is incompatible with this version of puni. """ try: usernotes = self.subreddit.wiki[self.page_name].content_md notes = json.loads(usernotes) except NotFound: self._init_notes() else: if notes['ver'] != self.schema: raise RuntimeError( 'Usernotes schema is v{0}, puni requires v{1}'. format(notes['ver'], self.schema) ) self.cached_json = self._expand_json(notes) return self.cached_json

Get the JSON stored on the usernotes wiki page. Returns a dict representation of the usernotes (with the notes BLOB decoded). Raises: RuntimeError if the usernotes version is incompatible with this version of puni.

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L186-L210

teaearlgraycold/puni

puni/base.py

UserNotes._init_notes

def _init_notes(self): """Set up the UserNotes page with the initial JSON schema.""" self.cached_json = { 'ver': self.schema, 'users': {}, 'constants': { 'users': [x.name for x in self.subreddit.moderator()], 'warnings': Note.warnings } } self.set_json('Initializing JSON via puni', True)

python

def _init_notes(self): """Set up the UserNotes page with the initial JSON schema.""" self.cached_json = { 'ver': self.schema, 'users': {}, 'constants': { 'users': [x.name for x in self.subreddit.moderator()], 'warnings': Note.warnings } } self.set_json('Initializing JSON via puni', True)

Set up the UserNotes page with the initial JSON schema.

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L212-L223

teaearlgraycold/puni

puni/base.py

UserNotes.set_json

def set_json(self, reason='', new_page=False): """Send the JSON from the cache to the usernotes wiki page. Arguments: reason: the change reason that will be posted to the wiki changelog (str) Raises: OverflowError if the new JSON data is greater than max_page_size """ compressed_json = json.dumps(self._compress_json(self.cached_json)) if len(compressed_json) > self.max_page_size: raise OverflowError( 'Usernotes page is too large (>{0} characters)'. format(self.max_page_size) ) if new_page: self.subreddit.wiki.create( self.page_name, compressed_json, reason ) # Set the page as hidden and available to moderators only self.subreddit.wiki[self.page_name].mod.update(False, permlevel=2) else: self.subreddit.wiki[self.page_name].edit( compressed_json, reason )

python

def set_json(self, reason='', new_page=False): """Send the JSON from the cache to the usernotes wiki page. Arguments: reason: the change reason that will be posted to the wiki changelog (str) Raises: OverflowError if the new JSON data is greater than max_page_size """ compressed_json = json.dumps(self._compress_json(self.cached_json)) if len(compressed_json) > self.max_page_size: raise OverflowError( 'Usernotes page is too large (>{0} characters)'. format(self.max_page_size) ) if new_page: self.subreddit.wiki.create( self.page_name, compressed_json, reason ) # Set the page as hidden and available to moderators only self.subreddit.wiki[self.page_name].mod.update(False, permlevel=2) else: self.subreddit.wiki[self.page_name].edit( compressed_json, reason )

Send the JSON from the cache to the usernotes wiki page. Arguments: reason: the change reason that will be posted to the wiki changelog (str) Raises: OverflowError if the new JSON data is greater than max_page_size

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L225-L254

teaearlgraycold/puni

puni/base.py

UserNotes.get_notes

def get_notes(self, user): """Return a list of Note objects for the given user. Return an empty list if no notes are found. Arguments: user: the user to search for in the usernotes (str) """ # Try to search for all notes on a user, return an empty list if none # are found. try: users_notes = [] for note in self.cached_json['users'][user]['ns']: users_notes.append(Note( user=user, note=note['n'], subreddit=self.subreddit, mod=self._mod_from_index(note['m']), link=note['l'], warning=self._warning_from_index(note['w']), note_time=note['t'] )) return users_notes except KeyError: # User not found return []

python

def get_notes(self, user): """Return a list of Note objects for the given user. Return an empty list if no notes are found. Arguments: user: the user to search for in the usernotes (str) """ # Try to search for all notes on a user, return an empty list if none # are found. try: users_notes = [] for note in self.cached_json['users'][user]['ns']: users_notes.append(Note( user=user, note=note['n'], subreddit=self.subreddit, mod=self._mod_from_index(note['m']), link=note['l'], warning=self._warning_from_index(note['w']), note_time=note['t'] )) return users_notes except KeyError: # User not found return []

Return a list of Note objects for the given user. Return an empty list if no notes are found. Arguments: user: the user to search for in the usernotes (str)

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L257-L284

teaearlgraycold/puni

puni/base.py

UserNotes._expand_json

def _expand_json(self, j): """Decompress the BLOB portion of the usernotes. Arguments: j: the JSON returned from the wiki page (dict) Returns a Dict with the 'blob' key removed and a 'users' key added """ decompressed_json = copy.copy(j) decompressed_json.pop('blob', None) # Remove BLOB portion of JSON # Decode and decompress JSON compressed_data = base64.b64decode(j['blob']) original_json = zlib.decompress(compressed_data).decode('utf-8') decompressed_json['users'] = json.loads(original_json) # Insert users return decompressed_json

python

def _expand_json(self, j): """Decompress the BLOB portion of the usernotes. Arguments: j: the JSON returned from the wiki page (dict) Returns a Dict with the 'blob' key removed and a 'users' key added """ decompressed_json = copy.copy(j) decompressed_json.pop('blob', None) # Remove BLOB portion of JSON # Decode and decompress JSON compressed_data = base64.b64decode(j['blob']) original_json = zlib.decompress(compressed_data).decode('utf-8') decompressed_json['users'] = json.loads(original_json) # Insert users return decompressed_json

Decompress the BLOB portion of the usernotes. Arguments: j: the JSON returned from the wiki page (dict) Returns a Dict with the 'blob' key removed and a 'users' key added

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L307-L324

teaearlgraycold/puni

puni/base.py

UserNotes._compress_json

def _compress_json(self, j): """Compress the BLOB data portion of the usernotes. Arguments: j: the JSON in Schema v5 format (dict) Returns a dict with the 'users' key removed and 'blob' key added """ compressed_json = copy.copy(j) compressed_json.pop('users', None) compressed_data = zlib.compress( json.dumps(j['users']).encode('utf-8'), self.zlib_compression_strength ) b64_data = base64.b64encode(compressed_data).decode('utf-8') compressed_json['blob'] = b64_data return compressed_json

python

def _compress_json(self, j): """Compress the BLOB data portion of the usernotes. Arguments: j: the JSON in Schema v5 format (dict) Returns a dict with the 'users' key removed and 'blob' key added """ compressed_json = copy.copy(j) compressed_json.pop('users', None) compressed_data = zlib.compress( json.dumps(j['users']).encode('utf-8'), self.zlib_compression_strength ) b64_data = base64.b64encode(compressed_data).decode('utf-8') compressed_json['blob'] = b64_data return compressed_json

Compress the BLOB data portion of the usernotes. Arguments: j: the JSON in Schema v5 format (dict) Returns a dict with the 'users' key removed and 'blob' key added

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L326-L345

teaearlgraycold/puni

puni/base.py

UserNotes.add_note

def add_note(self, note): """Add a note to the usernotes wiki page. Arguments: note: the note to be added (Note) Returns the update message for the usernotes wiki Raises: ValueError when the warning type of the note can not be found in the stored list of warnings. """ notes = self.cached_json if not note.moderator: note.moderator = self.r.user.me().name # Get index of moderator in mod list from usernotes # Add moderator to list if not already there try: mod_index = notes['constants']['users'].index(note.moderator) except ValueError: notes['constants']['users'].append(note.moderator) mod_index = notes['constants']['users'].index(note.moderator) # Get index of warning type from warnings list # Add warning type to list if not already there try: warn_index = notes['constants']['warnings'].index(note.warning) except ValueError: if note.warning in Note.warnings: notes['constants']['warnings'].append(note.warning) warn_index = notes['constants']['warnings'].index(note.warning) else: raise ValueError('Warning type not valid: ' + note.warning) new_note = { 'n': note.note, 't': note.time, 'm': mod_index, 'l': note.link, 'w': warn_index } try: notes['users'][note.username]['ns'].insert(0, new_note) except KeyError: notes['users'][note.username] = {'ns': [new_note]} return '"create new note on user {}" via puni'.format(note.username)

python

def add_note(self, note): """Add a note to the usernotes wiki page. Arguments: note: the note to be added (Note) Returns the update message for the usernotes wiki Raises: ValueError when the warning type of the note can not be found in the stored list of warnings. """ notes = self.cached_json if not note.moderator: note.moderator = self.r.user.me().name # Get index of moderator in mod list from usernotes # Add moderator to list if not already there try: mod_index = notes['constants']['users'].index(note.moderator) except ValueError: notes['constants']['users'].append(note.moderator) mod_index = notes['constants']['users'].index(note.moderator) # Get index of warning type from warnings list # Add warning type to list if not already there try: warn_index = notes['constants']['warnings'].index(note.warning) except ValueError: if note.warning in Note.warnings: notes['constants']['warnings'].append(note.warning) warn_index = notes['constants']['warnings'].index(note.warning) else: raise ValueError('Warning type not valid: ' + note.warning) new_note = { 'n': note.note, 't': note.time, 'm': mod_index, 'l': note.link, 'w': warn_index } try: notes['users'][note.username]['ns'].insert(0, new_note) except KeyError: notes['users'][note.username] = {'ns': [new_note]} return '"create new note on user {}" via puni'.format(note.username)

Add a note to the usernotes wiki page. Arguments: note: the note to be added (Note) Returns the update message for the usernotes wiki Raises: ValueError when the warning type of the note can not be found in the stored list of warnings.

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L348-L397

teaearlgraycold/puni

puni/base.py

UserNotes.remove_note

def remove_note(self, username, index): """Remove a single usernote from the usernotes. Arguments: username: the user that for whom you're removing a note (str) index: the index of the note which is to be removed (int) Returns the update message for the usernotes wiki """ self.cached_json['users'][username]['ns'].pop(index) # Go ahead and remove the user's entry if they have no more notes left if len(self.cached_json['users'][username]['ns']) == 0: del self.cached_json['users'][username] return '"delete note #{} on user {}" via puni'.format(index, username)

python

def remove_note(self, username, index): """Remove a single usernote from the usernotes. Arguments: username: the user that for whom you're removing a note (str) index: the index of the note which is to be removed (int) Returns the update message for the usernotes wiki """ self.cached_json['users'][username]['ns'].pop(index) # Go ahead and remove the user's entry if they have no more notes left if len(self.cached_json['users'][username]['ns']) == 0: del self.cached_json['users'][username] return '"delete note #{} on user {}" via puni'.format(index, username)

Remove a single usernote from the usernotes. Arguments: username: the user that for whom you're removing a note (str) index: the index of the note which is to be removed (int) Returns the update message for the usernotes wiki

train

https://github.com/teaearlgraycold/puni/blob/f6d0bfde99942b29a6f91273e48abcd2d7a94c93/puni/base.py#L400-L415

davidblaisonneau-orange/foreman

foreman/puppetClasses.py

PuppetClasses.load

def load(self): """ Function load Get the list of all objects @return RETURN: A ForemanItem list """ cl_tmp = self.api.list(self.objName, limit=self.searchLimit).values() cl = [] for i in cl_tmp: cl.extend(i) return {x[self.index]: ItemPuppetClass(self.api, x['id'], self.objName, self.payloadObj, x) for x in cl}

python

def load(self): """ Function load Get the list of all objects @return RETURN: A ForemanItem list """ cl_tmp = self.api.list(self.objName, limit=self.searchLimit).values() cl = [] for i in cl_tmp: cl.extend(i) return {x[self.index]: ItemPuppetClass(self.api, x['id'], self.objName, self.payloadObj, x) for x in cl}

Function load Get the list of all objects @return RETURN: A ForemanItem list

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/puppetClasses.py#L32-L45

mozilla-services/amo2kinto

amo2kinto/exporter.py

is_related_to

def is_related_to(item, app_id, app_ver=None): """Return True if the item relates to the given app_id (and app_ver, if passed).""" versionRange = item.get('versionRange') if not versionRange: return True for vR in versionRange: if not vR.get('targetApplication'): return True if get_related_targetApplication(vR, app_id, app_ver) is not None: return True return False

python

def is_related_to(item, app_id, app_ver=None): """Return True if the item relates to the given app_id (and app_ver, if passed).""" versionRange = item.get('versionRange') if not versionRange: return True for vR in versionRange: if not vR.get('targetApplication'): return True if get_related_targetApplication(vR, app_id, app_ver) is not None: return True return False

Return True if the item relates to the given app_id (and app_ver, if passed).

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L46-L57

mozilla-services/amo2kinto

amo2kinto/exporter.py

get_related_targetApplication

def get_related_targetApplication(vR, app_id, app_ver): """Return the first matching target application in this version range. Returns None if there are no target applications or no matching ones.""" targetApplication = vR.get('targetApplication') if not targetApplication: return None for tA in targetApplication: guid = tA.get('guid') if not guid or guid == app_id: if not app_ver: return tA # We purposefully use maxVersion only, so that the blocklist contains items # whose minimum version is ahead of the version we get passed. This means # the blocklist we serve is "future-proof" for app upgrades. if between(version_int(app_ver), '0', tA.get('maxVersion', '*')): return tA return None

python

def get_related_targetApplication(vR, app_id, app_ver): """Return the first matching target application in this version range. Returns None if there are no target applications or no matching ones.""" targetApplication = vR.get('targetApplication') if not targetApplication: return None for tA in targetApplication: guid = tA.get('guid') if not guid or guid == app_id: if not app_ver: return tA # We purposefully use maxVersion only, so that the blocklist contains items # whose minimum version is ahead of the version we get passed. This means # the blocklist we serve is "future-proof" for app upgrades. if between(version_int(app_ver), '0', tA.get('maxVersion', '*')): return tA return None

Return the first matching target application in this version range. Returns None if there are no target applications or no matching ones.

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L60-L78

mozilla-services/amo2kinto

amo2kinto/exporter.py

write_addons_items

def write_addons_items(xml_tree, records, app_id, api_ver=3, app_ver=None): """Generate the addons blocklists. <emItem blockID="i372" id="[email protected]"> <versionRange minVersion="0" maxVersion="*" severity="3"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="39.0a1" maxVersion="*"/> </targetApplication> </versionRange> <prefs> <pref>browser.startup.homepage</pref> <pref>browser.search.defaultenginename</pref> </prefs> </emItem> """ if not records: return emItems = etree.SubElement(xml_tree, 'emItems') groupby = {} for item in records: if is_related_to(item, app_id, app_ver): if item['guid'] in groupby: emItem = groupby[item['guid']] # When creating new records from the Kinto Admin we don't have proper blockID. if 'blockID' in item: # Remove the first caracter which is the letter i to # compare the numeric value i45 < i356. current_blockID = int(item['blockID'][1:]) previous_blockID = int(emItem.attrib['blockID'][1:]) # Group by and keep the biggest blockID in the XML file. if current_blockID > previous_blockID: emItem.attrib['blockID'] = item['blockID'] else: # If the latest entry does not have any blockID attribute, its # ID should be used. (the list of records is sorted by ascending # last_modified). # See https://bugzilla.mozilla.org/show_bug.cgi?id=1473194 emItem.attrib['blockID'] = item['id'] else: emItem = etree.SubElement(emItems, 'emItem', blockID=item.get('blockID', item['id'])) groupby[item['guid']] = emItem prefs = etree.SubElement(emItem, 'prefs') for p in item['prefs']: pref = etree.SubElement(prefs, 'pref') pref.text = p # Set the add-on ID emItem.set('id', item['guid']) for field in ['name', 'os']: if field in item: emItem.set(field, item[field]) build_version_range(emItem, item, app_id)

python

def write_addons_items(xml_tree, records, app_id, api_ver=3, app_ver=None): """Generate the addons blocklists. <emItem blockID="i372" id="[email protected]"> <versionRange minVersion="0" maxVersion="*" severity="3"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="39.0a1" maxVersion="*"/> </targetApplication> </versionRange> <prefs> <pref>browser.startup.homepage</pref> <pref>browser.search.defaultenginename</pref> </prefs> </emItem> """ if not records: return emItems = etree.SubElement(xml_tree, 'emItems') groupby = {} for item in records: if is_related_to(item, app_id, app_ver): if item['guid'] in groupby: emItem = groupby[item['guid']] # When creating new records from the Kinto Admin we don't have proper blockID. if 'blockID' in item: # Remove the first caracter which is the letter i to # compare the numeric value i45 < i356. current_blockID = int(item['blockID'][1:]) previous_blockID = int(emItem.attrib['blockID'][1:]) # Group by and keep the biggest blockID in the XML file. if current_blockID > previous_blockID: emItem.attrib['blockID'] = item['blockID'] else: # If the latest entry does not have any blockID attribute, its # ID should be used. (the list of records is sorted by ascending # last_modified). # See https://bugzilla.mozilla.org/show_bug.cgi?id=1473194 emItem.attrib['blockID'] = item['id'] else: emItem = etree.SubElement(emItems, 'emItem', blockID=item.get('blockID', item['id'])) groupby[item['guid']] = emItem prefs = etree.SubElement(emItem, 'prefs') for p in item['prefs']: pref = etree.SubElement(prefs, 'pref') pref.text = p # Set the add-on ID emItem.set('id', item['guid']) for field in ['name', 'os']: if field in item: emItem.set(field, item[field]) build_version_range(emItem, item, app_id)

Generate the addons blocklists. <emItem blockID="i372" id="[email protected]"> <versionRange minVersion="0" maxVersion="*" severity="3"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="39.0a1" maxVersion="*"/> </targetApplication> </versionRange> <prefs> <pref>browser.startup.homepage</pref> <pref>browser.search.defaultenginename</pref> </prefs> </emItem>

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L88-L143

mozilla-services/amo2kinto

amo2kinto/exporter.py

write_plugin_items

def write_plugin_items(xml_tree, records, app_id, api_ver=3, app_ver=None): """Generate the plugin blocklists. <pluginItem blockID="p422"> <match name="filename" exp="JavaAppletPlugin\\.plugin"/> <versionRange minVersion="Java 7 Update 16" maxVersion="Java 7 Update 24" severity="0" vulnerabilitystatus="1"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="17.0" maxVersion="*"/> </targetApplication> </versionRange> </pluginItem> """ if not records: return pluginItems = etree.SubElement(xml_tree, 'pluginItems') for item in records: for versionRange in item.get('versionRange', []): if not versionRange.get('targetApplication'): add_plugin_item(pluginItems, item, versionRange, app_id=app_id, api_ver=api_ver, app_ver=app_ver) else: targetApplication = get_related_targetApplication(versionRange, app_id, app_ver) if targetApplication is not None: add_plugin_item(pluginItems, item, versionRange, targetApplication, app_id=app_id, api_ver=api_ver, app_ver=app_ver)

python

def write_plugin_items(xml_tree, records, app_id, api_ver=3, app_ver=None): """Generate the plugin blocklists. <pluginItem blockID="p422"> <match name="filename" exp="JavaAppletPlugin\\.plugin"/> <versionRange minVersion="Java 7 Update 16" maxVersion="Java 7 Update 24" severity="0" vulnerabilitystatus="1"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="17.0" maxVersion="*"/> </targetApplication> </versionRange> </pluginItem> """ if not records: return pluginItems = etree.SubElement(xml_tree, 'pluginItems') for item in records: for versionRange in item.get('versionRange', []): if not versionRange.get('targetApplication'): add_plugin_item(pluginItems, item, versionRange, app_id=app_id, api_ver=api_ver, app_ver=app_ver) else: targetApplication = get_related_targetApplication(versionRange, app_id, app_ver) if targetApplication is not None: add_plugin_item(pluginItems, item, versionRange, targetApplication, app_id=app_id, api_ver=api_ver, app_ver=app_ver)

Generate the plugin blocklists. <pluginItem blockID="p422"> <match name="filename" exp="JavaAppletPlugin\\.plugin"/> <versionRange minVersion="Java 7 Update 16" maxVersion="Java 7 Update 24" severity="0" vulnerabilitystatus="1"> <targetApplication id="{ec8030f7-c20a-464f-9b0e-13a3a9e97384}"> <versionRange minVersion="17.0" maxVersion="*"/> </targetApplication> </versionRange> </pluginItem>

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L152-L182

mozilla-services/amo2kinto

amo2kinto/exporter.py

write_gfx_items

def write_gfx_items(xml_tree, records, app_id, api_ver=3): """Generate the gfxBlacklistEntry. <gfxBlacklistEntry blockID="g35"> <os>WINNT 6.1</os> <vendor>0x10de</vendor> <devices> <device>0x0a6c</device> </devices> <feature>DIRECT2D</feature> <featureStatus>BLOCKED_DRIVER_VERSION</featureStatus> <driverVersion>8.17.12.5896</driverVersion> <driverVersionComparator>LESS_THAN_OR_EQUAL</driverVersionComparator> <versionRange minVersion="3.2" maxVersion="3.4" /> </gfxBlacklistEntry> """ if not records: return gfxItems = etree.SubElement(xml_tree, 'gfxItems') for item in records: is_record_related = ('guid' not in item or item['guid'] == app_id) if is_record_related: entry = etree.SubElement(gfxItems, 'gfxBlacklistEntry', blockID=item.get('blockID', item['id'])) fields = ['os', 'vendor', 'feature', 'featureStatus', 'driverVersion', 'driverVersionComparator'] for field in fields: if field in item: node = etree.SubElement(entry, field) node.text = item[field] # Devices if item['devices']: devices = etree.SubElement(entry, 'devices') for d in item['devices']: device = etree.SubElement(devices, 'device') device.text = d if 'versionRange' in item: version = item['versionRange'] versionRange = etree.SubElement(entry, 'versionRange') for field in ['minVersion', 'maxVersion']: value = version.get(field) if value: versionRange.set(field, str(value))

python

def write_gfx_items(xml_tree, records, app_id, api_ver=3): """Generate the gfxBlacklistEntry. <gfxBlacklistEntry blockID="g35"> <os>WINNT 6.1</os> <vendor>0x10de</vendor> <devices> <device>0x0a6c</device> </devices> <feature>DIRECT2D</feature> <featureStatus>BLOCKED_DRIVER_VERSION</featureStatus> <driverVersion>8.17.12.5896</driverVersion> <driverVersionComparator>LESS_THAN_OR_EQUAL</driverVersionComparator> <versionRange minVersion="3.2" maxVersion="3.4" /> </gfxBlacklistEntry> """ if not records: return gfxItems = etree.SubElement(xml_tree, 'gfxItems') for item in records: is_record_related = ('guid' not in item or item['guid'] == app_id) if is_record_related: entry = etree.SubElement(gfxItems, 'gfxBlacklistEntry', blockID=item.get('blockID', item['id'])) fields = ['os', 'vendor', 'feature', 'featureStatus', 'driverVersion', 'driverVersionComparator'] for field in fields: if field in item: node = etree.SubElement(entry, field) node.text = item[field] # Devices if item['devices']: devices = etree.SubElement(entry, 'devices') for d in item['devices']: device = etree.SubElement(devices, 'device') device.text = d if 'versionRange' in item: version = item['versionRange'] versionRange = etree.SubElement(entry, 'versionRange') for field in ['minVersion', 'maxVersion']: value = version.get(field) if value: versionRange.set(field, str(value))

Generate the gfxBlacklistEntry. <gfxBlacklistEntry blockID="g35"> <os>WINNT 6.1</os> <vendor>0x10de</vendor> <devices> <device>0x0a6c</device> </devices> <feature>DIRECT2D</feature> <featureStatus>BLOCKED_DRIVER_VERSION</featureStatus> <driverVersion>8.17.12.5896</driverVersion> <driverVersionComparator>LESS_THAN_OR_EQUAL</driverVersionComparator> <versionRange minVersion="3.2" maxVersion="3.4" /> </gfxBlacklistEntry>

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L276-L323

mozilla-services/amo2kinto

amo2kinto/exporter.py

write_cert_items

def write_cert_items(xml_tree, records, api_ver=3, app_id=None, app_ver=None): """Generate the certificate blocklists. <certItem issuerName="MIGQMQswCQYD...IENB"> <serialNumber>UoRGnb96CUDTxIqVry6LBg==</serialNumber> </certItem> or <certItem subject='MCIxIDAeBgNVBAMMF0Fub3RoZXIgVGVzdCBFbmQtZW50aXR5' pubKeyHash='VCIlmPM9NkgFQtrs4Oa5TeFcDu6MWRTKSNdePEhOgD8='> </certItem> """ if not records or not should_include_certs(app_id, app_ver): return certItems = etree.SubElement(xml_tree, 'certItems') for item in records: if item.get('subject') and item.get('pubKeyHash'): cert = etree.SubElement(certItems, 'certItem', subject=item['subject'], pubKeyHash=item['pubKeyHash']) else: cert = etree.SubElement(certItems, 'certItem', issuerName=item['issuerName']) serialNumber = etree.SubElement(cert, 'serialNumber') serialNumber.text = item['serialNumber']

python

def write_cert_items(xml_tree, records, api_ver=3, app_id=None, app_ver=None): """Generate the certificate blocklists. <certItem issuerName="MIGQMQswCQYD...IENB"> <serialNumber>UoRGnb96CUDTxIqVry6LBg==</serialNumber> </certItem> or <certItem subject='MCIxIDAeBgNVBAMMF0Fub3RoZXIgVGVzdCBFbmQtZW50aXR5' pubKeyHash='VCIlmPM9NkgFQtrs4Oa5TeFcDu6MWRTKSNdePEhOgD8='> </certItem> """ if not records or not should_include_certs(app_id, app_ver): return certItems = etree.SubElement(xml_tree, 'certItems') for item in records: if item.get('subject') and item.get('pubKeyHash'): cert = etree.SubElement(certItems, 'certItem', subject=item['subject'], pubKeyHash=item['pubKeyHash']) else: cert = etree.SubElement(certItems, 'certItem', issuerName=item['issuerName']) serialNumber = etree.SubElement(cert, 'serialNumber') serialNumber.text = item['serialNumber']

Generate the certificate blocklists. <certItem issuerName="MIGQMQswCQYD...IENB"> <serialNumber>UoRGnb96CUDTxIqVry6LBg==</serialNumber> </certItem> or <certItem subject='MCIxIDAeBgNVBAMMF0Fub3RoZXIgVGVzdCBFbmQtZW50aXR5' pubKeyHash='VCIlmPM9NkgFQtrs4Oa5TeFcDu6MWRTKSNdePEhOgD8='> </certItem>

train

https://github.com/mozilla-services/amo2kinto/blob/1ec40647e77cf89badbea4a58d328243daed49a9/amo2kinto/exporter.py#L326-L352

quantmind/agile-toolkit

agiletoolkit/api/repo.py

GitRepo.label

def label(self, name, color, update=True): """Create or update a label """ url = '%s/labels' % self data = dict(name=name, color=color) response = self.http.post( url, json=data, auth=self.auth, headers=self.headers ) if response.status_code == 201: return True elif response.status_code == 422 and update: url = '%s/%s' % (url, name) response = self.http.patch( url, json=data, auth=self.auth, headers=self.headers ) response.raise_for_status() return False

python

def label(self, name, color, update=True): """Create or update a label """ url = '%s/labels' % self data = dict(name=name, color=color) response = self.http.post( url, json=data, auth=self.auth, headers=self.headers ) if response.status_code == 201: return True elif response.status_code == 422 and update: url = '%s/%s' % (url, name) response = self.http.patch( url, json=data, auth=self.auth, headers=self.headers ) response.raise_for_status() return False

Create or update a label

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/api/repo.py#L25-L41

aroberge/experimental

experimental/transformers/utils/one2one.py

translate

def translate(source, dictionary): '''A dictionary with a one-to-one translation of keywords is used to provide the transformation. ''' toks = tokenize.generate_tokens(StringIO(source).readline) result = [] for toktype, tokvalue, _, _, _ in toks: if toktype == tokenize.NAME and tokvalue in dictionary: result.append((toktype, dictionary[tokvalue])) else: result.append((toktype, tokvalue)) return tokenize.untokenize(result)

python

def translate(source, dictionary): '''A dictionary with a one-to-one translation of keywords is used to provide the transformation. ''' toks = tokenize.generate_tokens(StringIO(source).readline) result = [] for toktype, tokvalue, _, _, _ in toks: if toktype == tokenize.NAME and tokvalue in dictionary: result.append((toktype, dictionary[tokvalue])) else: result.append((toktype, tokvalue)) return tokenize.untokenize(result)

A dictionary with a one-to-one translation of keywords is used to provide the transformation.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/transformers/utils/one2one.py#L12-L23

davidblaisonneau-orange/foreman

foreman/itemComputeRessource.py

ItemComputeRessource.enhance

def enhance(self): """ Function enhance Enhance the object with new item or enhanced items """ self.update({'images': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemImages)})

python

def enhance(self): """ Function enhance Enhance the object with new item or enhanced items """ self.update({'images': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemImages)})

Function enhance Enhance the object with new item or enhanced items

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/itemComputeRessource.py#L34-L41

MatterMiners/cobald

cobald/daemon/runners/asyncio_runner.py

AsyncioRunner._run_payloads

async def _run_payloads(self): """Async component of _run""" delay = 0.0 try: while self.running.is_set(): await self._start_payloads() await self._reap_payloads() await asyncio.sleep(delay) delay = min(delay + 0.1, 1.0) except Exception: await self._cancel_payloads() raise

python

async def _run_payloads(self): """Async component of _run""" delay = 0.0 try: while self.running.is_set(): await self._start_payloads() await self._reap_payloads() await asyncio.sleep(delay) delay = min(delay + 0.1, 1.0) except Exception: await self._cancel_payloads() raise

Async component of _run

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_runner.py#L29-L40

MatterMiners/cobald

cobald/daemon/runners/asyncio_runner.py

AsyncioRunner._start_payloads

async def _start_payloads(self): """Start all queued payloads""" with self._lock: for coroutine in self._payloads: task = self.event_loop.create_task(coroutine()) self._tasks.add(task) self._payloads.clear() await asyncio.sleep(0)

python

async def _start_payloads(self): """Start all queued payloads""" with self._lock: for coroutine in self._payloads: task = self.event_loop.create_task(coroutine()) self._tasks.add(task) self._payloads.clear() await asyncio.sleep(0)

Start all queued payloads

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_runner.py#L42-L49

MatterMiners/cobald

cobald/daemon/runners/asyncio_runner.py

AsyncioRunner._reap_payloads

async def _reap_payloads(self): """Clean up all finished payloads""" for task in self._tasks.copy(): if task.done(): self._tasks.remove(task) if task.exception() is not None: raise task.exception() await asyncio.sleep(0)

python

async def _reap_payloads(self): """Clean up all finished payloads""" for task in self._tasks.copy(): if task.done(): self._tasks.remove(task) if task.exception() is not None: raise task.exception() await asyncio.sleep(0)

Clean up all finished payloads

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_runner.py#L51-L58

MatterMiners/cobald

cobald/daemon/runners/asyncio_runner.py

AsyncioRunner._cancel_payloads

async def _cancel_payloads(self): """Cancel all remaining payloads""" for task in self._tasks: task.cancel() await asyncio.sleep(0) for task in self._tasks: while not task.done(): await asyncio.sleep(0.1) task.cancel()

python

async def _cancel_payloads(self): """Cancel all remaining payloads""" for task in self._tasks: task.cancel() await asyncio.sleep(0) for task in self._tasks: while not task.done(): await asyncio.sleep(0.1) task.cancel()

Cancel all remaining payloads

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_runner.py#L60-L68

Karaage-Cluster/python-tldap

tldap/ldap_passwd.py

check_password

def check_password(password: str, encrypted: str) -> bool: """ Check a plaintext password against a hashed password. """ # some old passwords have {crypt} in lower case, and passlib wants it to be # in upper case. if encrypted.startswith("{crypt}"): encrypted = "{CRYPT}" + encrypted[7:] return pwd_context.verify(password, encrypted)

python

def check_password(password: str, encrypted: str) -> bool: """ Check a plaintext password against a hashed password. """ # some old passwords have {crypt} in lower case, and passlib wants it to be # in upper case. if encrypted.startswith("{crypt}"): encrypted = "{CRYPT}" + encrypted[7:] return pwd_context.verify(password, encrypted)

Check a plaintext password against a hashed password.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/ldap_passwd.py#L36-L42

quantmind/agile-toolkit

agiletoolkit/github/validate.py

validate

def validate(ctx, sandbox): """Check if version of repository is semantic """ m = RepoManager(ctx.obj['agile']) if not sandbox or m.can_release('sandbox'): click.echo(m.validate_version())

python

def validate(ctx, sandbox): """Check if version of repository is semantic """ m = RepoManager(ctx.obj['agile']) if not sandbox or m.can_release('sandbox'): click.echo(m.validate_version())

Check if version of repository is semantic

train

https://github.com/quantmind/agile-toolkit/blob/96028e36a842c57b171907c20583a60d1045fec1/agiletoolkit/github/validate.py#L11-L16

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.reset

def reset(self, force_flush_cache: bool = False) -> None: """ Reset transaction back to original state, discarding all uncompleted transactions. """ super(LDAPwrapper, self).reset() if len(self._transactions) == 0: raise RuntimeError("reset called outside a transaction.") self._transactions[-1] = []

python

def reset(self, force_flush_cache: bool = False) -> None: """ Reset transaction back to original state, discarding all uncompleted transactions. """ super(LDAPwrapper, self).reset() if len(self._transactions) == 0: raise RuntimeError("reset called outside a transaction.") self._transactions[-1] = []

Reset transaction back to original state, discarding all uncompleted transactions.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L68-L76

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper._cache_get_for_dn

def _cache_get_for_dn(self, dn: str) -> Dict[str, bytes]: """ Object state is cached. When an update is required the update will be simulated on this cache, so that rollback information can be correct. This function retrieves the cached data. """ # no cached item, retrieve from ldap self._do_with_retry( lambda obj: obj.search( dn, '(objectclass=*)', ldap3.BASE, attributes=['*', '+'])) results = self._obj.response if len(results) < 1: raise NoSuchObject("No results finding current value") if len(results) > 1: raise RuntimeError("Too many results finding current value") return results[0]['raw_attributes']

python

def _cache_get_for_dn(self, dn: str) -> Dict[str, bytes]: """ Object state is cached. When an update is required the update will be simulated on this cache, so that rollback information can be correct. This function retrieves the cached data. """ # no cached item, retrieve from ldap self._do_with_retry( lambda obj: obj.search( dn, '(objectclass=*)', ldap3.BASE, attributes=['*', '+'])) results = self._obj.response if len(results) < 1: raise NoSuchObject("No results finding current value") if len(results) > 1: raise RuntimeError("Too many results finding current value") return results[0]['raw_attributes']

Object state is cached. When an update is required the update will be simulated on this cache, so that rollback information can be correct. This function retrieves the cached data.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L78-L98

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.is_dirty

def is_dirty(self) -> bool: """ Are there uncommitted changes? """ if len(self._transactions) == 0: raise RuntimeError("is_dirty called outside a transaction.") if len(self._transactions[-1]) > 0: return True return False

python

def is_dirty(self) -> bool: """ Are there uncommitted changes? """ if len(self._transactions) == 0: raise RuntimeError("is_dirty called outside a transaction.") if len(self._transactions[-1]) > 0: return True return False

Are there uncommitted changes?

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L104-L110

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.leave_transaction_management

def leave_transaction_management(self) -> None: """ End a transaction. Must not be dirty when doing so. ie. commit() or rollback() must be called if changes made. If dirty, changes will be discarded. """ if len(self._transactions) == 0: raise RuntimeError("leave_transaction_management called outside transaction") elif len(self._transactions[-1]) > 0: raise RuntimeError("leave_transaction_management called with uncommited rollbacks") else: self._transactions.pop()

python

def leave_transaction_management(self) -> None: """ End a transaction. Must not be dirty when doing so. ie. commit() or rollback() must be called if changes made. If dirty, changes will be discarded. """ if len(self._transactions) == 0: raise RuntimeError("leave_transaction_management called outside transaction") elif len(self._transactions[-1]) > 0: raise RuntimeError("leave_transaction_management called with uncommited rollbacks") else: self._transactions.pop()

End a transaction. Must not be dirty when doing so. ie. commit() or rollback() must be called if changes made. If dirty, changes will be discarded.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L120-L131

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.commit

def commit(self) -> None: """ Attempt to commit all changes to LDAP database. i.e. forget all rollbacks. However stay inside transaction management. """ if len(self._transactions) == 0: raise RuntimeError("commit called outside transaction") # If we have nested transactions, we don't actually commit, but push # rollbacks up to previous transaction. if len(self._transactions) > 1: for on_rollback in reversed(self._transactions[-1]): self._transactions[-2].insert(0, on_rollback) _debug("commit") self.reset()

python

def commit(self) -> None: """ Attempt to commit all changes to LDAP database. i.e. forget all rollbacks. However stay inside transaction management. """ if len(self._transactions) == 0: raise RuntimeError("commit called outside transaction") # If we have nested transactions, we don't actually commit, but push # rollbacks up to previous transaction. if len(self._transactions) > 1: for on_rollback in reversed(self._transactions[-1]): self._transactions[-2].insert(0, on_rollback) _debug("commit") self.reset()

Attempt to commit all changes to LDAP database. i.e. forget all rollbacks. However stay inside transaction management.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L133-L148

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.rollback

def rollback(self) -> None: """ Roll back to previous database state. However stay inside transaction management. """ if len(self._transactions) == 0: raise RuntimeError("rollback called outside transaction") _debug("rollback:", self._transactions[-1]) # if something goes wrong here, nothing we can do about it, leave # database as is. try: # for every rollback action ... for on_rollback in self._transactions[-1]: # execute it _debug("--> rolling back", on_rollback) self._do_with_retry(on_rollback) except: # noqa: E722 _debug("--> rollback failed") exc_class, exc, tb = sys.exc_info() raise tldap.exceptions.RollbackError( "FATAL Unrecoverable rollback error: %r" % exc) finally: # reset everything to clean state _debug("--> rollback success") self.reset()

python

def rollback(self) -> None: """ Roll back to previous database state. However stay inside transaction management. """ if len(self._transactions) == 0: raise RuntimeError("rollback called outside transaction") _debug("rollback:", self._transactions[-1]) # if something goes wrong here, nothing we can do about it, leave # database as is. try: # for every rollback action ... for on_rollback in self._transactions[-1]: # execute it _debug("--> rolling back", on_rollback) self._do_with_retry(on_rollback) except: # noqa: E722 _debug("--> rollback failed") exc_class, exc, tb = sys.exc_info() raise tldap.exceptions.RollbackError( "FATAL Unrecoverable rollback error: %r" % exc) finally: # reset everything to clean state _debug("--> rollback success") self.reset()

Roll back to previous database state. However stay inside transaction management.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L150-L175

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper._process

def _process(self, on_commit: UpdateCallable, on_rollback: UpdateCallable) -> Any: """ Process action. oncommit is a callback to execute action, onrollback is a callback to execute if the oncommit() has been called and a rollback is required """ _debug("---> commiting", on_commit) result = self._do_with_retry(on_commit) if len(self._transactions) > 0: # add statement to rollback log in case something goes wrong self._transactions[-1].insert(0, on_rollback) return result

python

def _process(self, on_commit: UpdateCallable, on_rollback: UpdateCallable) -> Any: """ Process action. oncommit is a callback to execute action, onrollback is a callback to execute if the oncommit() has been called and a rollback is required """ _debug("---> commiting", on_commit) result = self._do_with_retry(on_commit) if len(self._transactions) > 0: # add statement to rollback log in case something goes wrong self._transactions[-1].insert(0, on_rollback) return result

Process action. oncommit is a callback to execute action, onrollback is a callback to execute if the oncommit() has been called and a rollback is required

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L177-L191

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.add

def add(self, dn: str, mod_list: dict) -> None: """ Add a DN to the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("add", self, dn, mod_list) # if rollback of add required, delete it def on_commit(obj): obj.add(dn, None, mod_list) def on_rollback(obj): obj.delete(dn) # process this action return self._process(on_commit, on_rollback)

python

def add(self, dn: str, mod_list: dict) -> None: """ Add a DN to the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("add", self, dn, mod_list) # if rollback of add required, delete it def on_commit(obj): obj.add(dn, None, mod_list) def on_rollback(obj): obj.delete(dn) # process this action return self._process(on_commit, on_rollback)

Add a DN to the LDAP database; See ldap module. Doesn't return a result if transactions enabled.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L197-L213

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.modify

def modify(self, dn: str, mod_list: dict) -> None: """ Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("modify", self, dn, mod_list) # need to work out how to reverse changes in mod_list; result in revlist revlist = {} # get the current cached attributes result = self._cache_get_for_dn(dn) # find the how to reverse mod_list (for rollback) and put result in # revlist. Also simulate actions on cache. for mod_type, l in six.iteritems(mod_list): for mod_op, mod_vals in l: _debug("attribute:", mod_type) if mod_type in result: _debug("attribute cache:", result[mod_type]) else: _debug("attribute cache is empty") _debug("attribute modify:", (mod_op, mod_vals)) if mod_vals is not None: if not isinstance(mod_vals, list): mod_vals = [mod_vals] if mod_op == ldap3.MODIFY_ADD: # reverse of MODIFY_ADD is MODIFY_DELETE reverse = (ldap3.MODIFY_DELETE, mod_vals) elif mod_op == ldap3.MODIFY_DELETE and len(mod_vals) > 0: # Reverse of MODIFY_DELETE is MODIFY_ADD, but only if value # is given if mod_vals is None, this means all values where # deleted. reverse = (ldap3.MODIFY_ADD, mod_vals) elif mod_op == ldap3.MODIFY_DELETE \ or mod_op == ldap3.MODIFY_REPLACE: if mod_type in result: # If MODIFY_DELETE with no values or MODIFY_REPLACE # then we have to replace all attributes with cached # state reverse = ( ldap3.MODIFY_REPLACE, tldap.modlist.escape_list(result[mod_type]) ) else: # except if we have no cached state for this DN, in # which case we delete it. reverse = (ldap3.MODIFY_DELETE, []) else: raise RuntimeError("mod_op of %d not supported" % mod_op) reverse = [reverse] _debug("attribute reverse:", reverse) if mod_type in result: _debug("attribute cache:", result[mod_type]) else: _debug("attribute cache is empty") revlist[mod_type] = reverse _debug("--") _debug("mod_list:", mod_list) _debug("revlist:", revlist) _debug("--") # now the hard stuff is over, we get to the easy stuff def on_commit(obj): obj.modify(dn, mod_list) def on_rollback(obj): obj.modify(dn, revlist) return self._process(on_commit, on_rollback)

python

def modify(self, dn: str, mod_list: dict) -> None: """ Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("modify", self, dn, mod_list) # need to work out how to reverse changes in mod_list; result in revlist revlist = {} # get the current cached attributes result = self._cache_get_for_dn(dn) # find the how to reverse mod_list (for rollback) and put result in # revlist. Also simulate actions on cache. for mod_type, l in six.iteritems(mod_list): for mod_op, mod_vals in l: _debug("attribute:", mod_type) if mod_type in result: _debug("attribute cache:", result[mod_type]) else: _debug("attribute cache is empty") _debug("attribute modify:", (mod_op, mod_vals)) if mod_vals is not None: if not isinstance(mod_vals, list): mod_vals = [mod_vals] if mod_op == ldap3.MODIFY_ADD: # reverse of MODIFY_ADD is MODIFY_DELETE reverse = (ldap3.MODIFY_DELETE, mod_vals) elif mod_op == ldap3.MODIFY_DELETE and len(mod_vals) > 0: # Reverse of MODIFY_DELETE is MODIFY_ADD, but only if value # is given if mod_vals is None, this means all values where # deleted. reverse = (ldap3.MODIFY_ADD, mod_vals) elif mod_op == ldap3.MODIFY_DELETE \ or mod_op == ldap3.MODIFY_REPLACE: if mod_type in result: # If MODIFY_DELETE with no values or MODIFY_REPLACE # then we have to replace all attributes with cached # state reverse = ( ldap3.MODIFY_REPLACE, tldap.modlist.escape_list(result[mod_type]) ) else: # except if we have no cached state for this DN, in # which case we delete it. reverse = (ldap3.MODIFY_DELETE, []) else: raise RuntimeError("mod_op of %d not supported" % mod_op) reverse = [reverse] _debug("attribute reverse:", reverse) if mod_type in result: _debug("attribute cache:", result[mod_type]) else: _debug("attribute cache is empty") revlist[mod_type] = reverse _debug("--") _debug("mod_list:", mod_list) _debug("revlist:", revlist) _debug("--") # now the hard stuff is over, we get to the easy stuff def on_commit(obj): obj.modify(dn, mod_list) def on_rollback(obj): obj.modify(dn, revlist) return self._process(on_commit, on_rollback)

Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L215-L294

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.modify_no_rollback

def modify_no_rollback(self, dn: str, mod_list: dict): """ Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("modify_no_rollback", self, dn, mod_list) result = self._do_with_retry(lambda obj: obj.modify_s(dn, mod_list)) _debug("--") return result

python

def modify_no_rollback(self, dn: str, mod_list: dict): """ Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled. """ _debug("modify_no_rollback", self, dn, mod_list) result = self._do_with_retry(lambda obj: obj.modify_s(dn, mod_list)) _debug("--") return result

Modify a DN in the LDAP database; See ldap module. Doesn't return a result if transactions enabled.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L296-L306

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.delete

def delete(self, dn: str) -> None: """ delete a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled. """ _debug("delete", self) # get copy of cache result = self._cache_get_for_dn(dn) # remove special values that can't be added def delete_attribute(name): if name in result: del result[name] delete_attribute('entryUUID') delete_attribute('structuralObjectClass') delete_attribute('modifiersName') delete_attribute('subschemaSubentry') delete_attribute('entryDN') delete_attribute('modifyTimestamp') delete_attribute('entryCSN') delete_attribute('createTimestamp') delete_attribute('creatorsName') delete_attribute('hasSubordinates') delete_attribute('pwdFailureTime') delete_attribute('pwdChangedTime') # turn into mod_list list. mod_list = tldap.modlist.addModlist(result) _debug("revlist:", mod_list) # on commit carry out action; on rollback restore cached state def on_commit(obj): obj.delete(dn) def on_rollback(obj): obj.add(dn, None, mod_list) return self._process(on_commit, on_rollback)

python

def delete(self, dn: str) -> None: """ delete a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled. """ _debug("delete", self) # get copy of cache result = self._cache_get_for_dn(dn) # remove special values that can't be added def delete_attribute(name): if name in result: del result[name] delete_attribute('entryUUID') delete_attribute('structuralObjectClass') delete_attribute('modifiersName') delete_attribute('subschemaSubentry') delete_attribute('entryDN') delete_attribute('modifyTimestamp') delete_attribute('entryCSN') delete_attribute('createTimestamp') delete_attribute('creatorsName') delete_attribute('hasSubordinates') delete_attribute('pwdFailureTime') delete_attribute('pwdChangedTime') # turn into mod_list list. mod_list = tldap.modlist.addModlist(result) _debug("revlist:", mod_list) # on commit carry out action; on rollback restore cached state def on_commit(obj): obj.delete(dn) def on_rollback(obj): obj.add(dn, None, mod_list) return self._process(on_commit, on_rollback)

delete a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L308-L347

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.rename

def rename(self, dn: str, new_rdn: str, new_base_dn: Optional[str] = None) -> None: """ rename a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled. """ _debug("rename", self, dn, new_rdn, new_base_dn) # split up the parameters split_dn = tldap.dn.str2dn(dn) split_newrdn = tldap.dn.str2dn(new_rdn) assert(len(split_newrdn) == 1) # make dn unqualified rdn = tldap.dn.dn2str(split_dn[0:1]) # make newrdn fully qualified dn tmplist = [split_newrdn[0]] if new_base_dn is not None: tmplist.extend(tldap.dn.str2dn(new_base_dn)) old_base_dn = tldap.dn.dn2str(split_dn[1:]) else: tmplist.extend(split_dn[1:]) old_base_dn = None newdn = tldap.dn.dn2str(tmplist) _debug("--> commit ", self, dn, new_rdn, new_base_dn) _debug("--> rollback", self, newdn, rdn, old_base_dn) # on commit carry out action; on rollback reverse rename def on_commit(obj): obj.modify_dn(dn, new_rdn, new_superior=new_base_dn) def on_rollback(obj): obj.modify_dn(newdn, rdn, new_superior=old_base_dn) return self._process(on_commit, on_rollback)

python

def rename(self, dn: str, new_rdn: str, new_base_dn: Optional[str] = None) -> None: """ rename a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled. """ _debug("rename", self, dn, new_rdn, new_base_dn) # split up the parameters split_dn = tldap.dn.str2dn(dn) split_newrdn = tldap.dn.str2dn(new_rdn) assert(len(split_newrdn) == 1) # make dn unqualified rdn = tldap.dn.dn2str(split_dn[0:1]) # make newrdn fully qualified dn tmplist = [split_newrdn[0]] if new_base_dn is not None: tmplist.extend(tldap.dn.str2dn(new_base_dn)) old_base_dn = tldap.dn.dn2str(split_dn[1:]) else: tmplist.extend(split_dn[1:]) old_base_dn = None newdn = tldap.dn.dn2str(tmplist) _debug("--> commit ", self, dn, new_rdn, new_base_dn) _debug("--> rollback", self, newdn, rdn, old_base_dn) # on commit carry out action; on rollback reverse rename def on_commit(obj): obj.modify_dn(dn, new_rdn, new_superior=new_base_dn) def on_rollback(obj): obj.modify_dn(newdn, rdn, new_superior=old_base_dn) return self._process(on_commit, on_rollback)

rename a dn in the ldap database; see ldap module. doesn't return a result if transactions enabled.

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L349-L385

Karaage-Cluster/python-tldap

tldap/backend/fake_transactions.py

LDAPwrapper.fail

def fail(self) -> None: """ for testing purposes only. always fail in commit """ _debug("fail") # on commit carry out action; on rollback reverse rename def on_commit(_obj): raise_testfailure("commit") def on_rollback(_obj): raise_testfailure("rollback") return self._process(on_commit, on_rollback)

python

def fail(self) -> None: """ for testing purposes only. always fail in commit """ _debug("fail") # on commit carry out action; on rollback reverse rename def on_commit(_obj): raise_testfailure("commit") def on_rollback(_obj): raise_testfailure("rollback") return self._process(on_commit, on_rollback)

for testing purposes only. always fail in commit

train

https://github.com/Karaage-Cluster/python-tldap/blob/61f1af74a3648cb6491e7eeb1ee2eb395d67bf59/tldap/backend/fake_transactions.py#L387-L399

aroberge/experimental

experimental/transformers/int_seq.py

__experimental_range

def __experimental_range(start, stop, var, cond, loc={}): '''Utility function made to reproduce range() with unit integer step but with the added possibility of specifying a condition on the looping variable (e.g. var % 2 == 0) ''' locals().update(loc) if start < stop: for __ in range(start, stop): locals()[var] = __ if eval(cond, globals(), locals()): yield __ else: for __ in range(start, stop, -1): locals()[var] = __ if eval(cond, globals(), locals()): yield __

python

def __experimental_range(start, stop, var, cond, loc={}): '''Utility function made to reproduce range() with unit integer step but with the added possibility of specifying a condition on the looping variable (e.g. var % 2 == 0) ''' locals().update(loc) if start < stop: for __ in range(start, stop): locals()[var] = __ if eval(cond, globals(), locals()): yield __ else: for __ in range(start, stop, -1): locals()[var] = __ if eval(cond, globals(), locals()): yield __

Utility function made to reproduce range() with unit integer step but with the added possibility of specifying a condition on the looping variable (e.g. var % 2 == 0)

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/transformers/int_seq.py#L51-L66

aroberge/experimental

experimental/transformers/int_seq.py

create_for

def create_for(line, search_result): '''Create a new "for loop" line as a replacement for the original code. ''' try: return line.format(search_result.group("indented_for"), search_result.group("var"), search_result.group("start"), search_result.group("stop"), search_result.group("cond")) except IndexError: return line.format(search_result.group("indented_for"), search_result.group("var"), search_result.group("start"), search_result.group("stop"))

python

def create_for(line, search_result): '''Create a new "for loop" line as a replacement for the original code. ''' try: return line.format(search_result.group("indented_for"), search_result.group("var"), search_result.group("start"), search_result.group("stop"), search_result.group("cond")) except IndexError: return line.format(search_result.group("indented_for"), search_result.group("var"), search_result.group("start"), search_result.group("stop"))

Create a new "for loop" line as a replacement for the original code.

train

https://github.com/aroberge/experimental/blob/031a9be10698b429998436da748b8fdb86f18b47/experimental/transformers/int_seq.py#L180-L193

davidblaisonneau-orange/foreman

foreman/itemSmartClassParameter.py

ItemSmartClassParameter.setOverrideValue

def setOverrideValue(self, attributes, hostName): """ Function __setitem__ Set a parameter of a foreman object as a dict @param key: The key to modify @param attribute: The data @return RETURN: The API result """ self['override'] = True attrType = type(attributes) if attrType is dict: self['parameter_type'] = 'hash' elif attrType is list: self['parameter_type'] = 'array' else: self['parameter_type'] = 'string' orv = self.getOverrideValueForHost(hostName) if orv: orv['value'] = attributes return True else: return self.api.create('{}/{}/{}'.format(self.objName, self.key, 'override_values'), {"override_value": {"match": "fqdn={}".format(hostName), "value": attributes}})

python

def setOverrideValue(self, attributes, hostName): """ Function __setitem__ Set a parameter of a foreman object as a dict @param key: The key to modify @param attribute: The data @return RETURN: The API result """ self['override'] = True attrType = type(attributes) if attrType is dict: self['parameter_type'] = 'hash' elif attrType is list: self['parameter_type'] = 'array' else: self['parameter_type'] = 'string' orv = self.getOverrideValueForHost(hostName) if orv: orv['value'] = attributes return True else: return self.api.create('{}/{}/{}'.format(self.objName, self.key, 'override_values'), {"override_value": {"match": "fqdn={}".format(hostName), "value": attributes}})

Function __setitem__ Set a parameter of a foreman object as a dict @param key: The key to modify @param attribute: The data @return RETURN: The API result

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/itemSmartClassParameter.py#L87-L113

developersociety/django-glitter

glitter/reminders/models.py

Reminder.get_interval_timedelta

def get_interval_timedelta(self): """ Spits out the timedelta in days. """ now_datetime = timezone.now() current_month_days = monthrange(now_datetime.year, now_datetime.month)[1] # Two weeks if self.interval == reminders_choices.INTERVAL_2_WEEKS: interval_timedelta = datetime.timedelta(days=14) # One month elif self.interval == reminders_choices.INTERVAL_ONE_MONTH: interval_timedelta = datetime.timedelta(days=current_month_days) # Three months elif self.interval == reminders_choices.INTERVAL_THREE_MONTHS: three_months = now_datetime + relativedelta(months=+3) interval_timedelta = three_months - now_datetime # Six months elif self.interval == reminders_choices.INTERVAL_SIX_MONTHS: six_months = now_datetime + relativedelta(months=+6) interval_timedelta = six_months - now_datetime # One year elif self.interval == reminders_choices.INTERVAL_ONE_YEAR: one_year = now_datetime + relativedelta(years=+1) interval_timedelta = one_year - now_datetime return interval_timedelta

python

def get_interval_timedelta(self): """ Spits out the timedelta in days. """ now_datetime = timezone.now() current_month_days = monthrange(now_datetime.year, now_datetime.month)[1] # Two weeks if self.interval == reminders_choices.INTERVAL_2_WEEKS: interval_timedelta = datetime.timedelta(days=14) # One month elif self.interval == reminders_choices.INTERVAL_ONE_MONTH: interval_timedelta = datetime.timedelta(days=current_month_days) # Three months elif self.interval == reminders_choices.INTERVAL_THREE_MONTHS: three_months = now_datetime + relativedelta(months=+3) interval_timedelta = three_months - now_datetime # Six months elif self.interval == reminders_choices.INTERVAL_SIX_MONTHS: six_months = now_datetime + relativedelta(months=+6) interval_timedelta = six_months - now_datetime # One year elif self.interval == reminders_choices.INTERVAL_ONE_YEAR: one_year = now_datetime + relativedelta(years=+1) interval_timedelta = one_year - now_datetime return interval_timedelta

Spits out the timedelta in days.

train

https://github.com/developersociety/django-glitter/blob/2c0280ec83afee80deee94ee3934fc54239c2e87/glitter/reminders/models.py#L34-L63

MatterMiners/cobald

cobald/daemon/runners/asyncio_watcher.py

awaitable_runner

async def awaitable_runner(runner: BaseRunner): """Execute a runner without blocking the event loop""" runner_thread = CapturingThread(target=runner.run) runner_thread.start() delay = 0.0 while not runner_thread.join(timeout=0): await asyncio.sleep(delay) delay = min(delay + 0.1, 1.0)

python

async def awaitable_runner(runner: BaseRunner): """Execute a runner without blocking the event loop""" runner_thread = CapturingThread(target=runner.run) runner_thread.start() delay = 0.0 while not runner_thread.join(timeout=0): await asyncio.sleep(delay) delay = min(delay + 0.1, 1.0)

Execute a runner without blocking the event loop

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_watcher.py#L9-L16

MatterMiners/cobald

cobald/daemon/runners/asyncio_watcher.py

asyncio_main_run

def asyncio_main_run(root_runner: BaseRunner): """ Create an ``asyncio`` event loop running in the main thread and watching runners Using ``asyncio`` to handle suprocesses requires a specific loop type to run in the main thread. This function sets up and runs the correct loop in a portable way. In addition, it runs a single :py:class:`~.BaseRunner` until completion or failure. .. seealso:: The `issue #8 <https://github.com/MatterMiners/cobald/issues/8>`_ for details. """ assert threading.current_thread() == threading.main_thread(), 'only main thread can accept asyncio subprocesses' if sys.platform == 'win32': event_loop = asyncio.ProactorEventLoop() asyncio.set_event_loop(event_loop) else: event_loop = asyncio.get_event_loop() asyncio.get_child_watcher().attach_loop(event_loop) event_loop.run_until_complete(awaitable_runner(root_runner))

python

def asyncio_main_run(root_runner: BaseRunner): """ Create an ``asyncio`` event loop running in the main thread and watching runners Using ``asyncio`` to handle suprocesses requires a specific loop type to run in the main thread. This function sets up and runs the correct loop in a portable way. In addition, it runs a single :py:class:`~.BaseRunner` until completion or failure. .. seealso:: The `issue #8 <https://github.com/MatterMiners/cobald/issues/8>`_ for details. """ assert threading.current_thread() == threading.main_thread(), 'only main thread can accept asyncio subprocesses' if sys.platform == 'win32': event_loop = asyncio.ProactorEventLoop() asyncio.set_event_loop(event_loop) else: event_loop = asyncio.get_event_loop() asyncio.get_child_watcher().attach_loop(event_loop) event_loop.run_until_complete(awaitable_runner(root_runner))

Create an ``asyncio`` event loop running in the main thread and watching runners Using ``asyncio`` to handle suprocesses requires a specific loop type to run in the main thread. This function sets up and runs the correct loop in a portable way. In addition, it runs a single :py:class:`~.BaseRunner` until completion or failure. .. seealso:: The `issue #8 <https://github.com/MatterMiners/cobald/issues/8>`_ for details.

train

https://github.com/MatterMiners/cobald/blob/264138de4382d1c9b53fabcbc6660e10b33a914d/cobald/daemon/runners/asyncio_watcher.py#L19-L36

davidblaisonneau-orange/foreman

foreman/itemConfigTemplate.py

ItemConfigTemplate.enhance

def enhance(self): """ Function enhance Enhance the object with new item or enhanced items """ self.update({'os_default_templates': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemOsDefaultTemplate)}) self.update({'operatingsystems': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemOperatingSystem)})

python

def enhance(self): """ Function enhance Enhance the object with new item or enhanced items """ self.update({'os_default_templates': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemOsDefaultTemplate)}) self.update({'operatingsystems': SubDict(self.api, self.objName, self.payloadObj, self.key, SubItemOperatingSystem)})

Function enhance Enhance the object with new item or enhanced items

train

https://github.com/davidblaisonneau-orange/foreman/blob/acb8fd8d74657cfac3b25c82e9c6028b93eb6c92/foreman/itemConfigTemplate.py#L37-L48

qubell/contrib-python-qubell-client

qubell/api/tools/__init__.py

retry

def retry(tries=10, delay=1, backoff=2, retry_exception=None): """ Retry "tries" times, with initial "delay", increasing delay "delay*backoff" each time. Without exception success means when function returns valid object. With exception success when no exceptions """ assert tries > 0, "tries must be 1 or greater" catching_mode = bool(retry_exception) def deco_retry(f): @functools.wraps(f) def f_retry(*args, **kwargs): mtries, mdelay = tries, delay while mtries > 0: time.sleep(mdelay) mdelay *= backoff try: rv = f(*args, **kwargs) if not catching_mode and rv: return rv except retry_exception: pass else: if catching_mode: return rv mtries -= 1 if mtries is 0 and not catching_mode: return False if mtries is 0 and catching_mode: return f(*args, **kwargs) # extra try, to avoid except-raise syntax log.debug("{0} try, sleeping for {1} sec".format(tries-mtries, mdelay)) raise Exception("unreachable code") return f_retry return deco_retry

python

def retry(tries=10, delay=1, backoff=2, retry_exception=None): """ Retry "tries" times, with initial "delay", increasing delay "delay*backoff" each time. Without exception success means when function returns valid object. With exception success when no exceptions """ assert tries > 0, "tries must be 1 or greater" catching_mode = bool(retry_exception) def deco_retry(f): @functools.wraps(f) def f_retry(*args, **kwargs): mtries, mdelay = tries, delay while mtries > 0: time.sleep(mdelay) mdelay *= backoff try: rv = f(*args, **kwargs) if not catching_mode and rv: return rv except retry_exception: pass else: if catching_mode: return rv mtries -= 1 if mtries is 0 and not catching_mode: return False if mtries is 0 and catching_mode: return f(*args, **kwargs) # extra try, to avoid except-raise syntax log.debug("{0} try, sleeping for {1} sec".format(tries-mtries, mdelay)) raise Exception("unreachable code") return f_retry return deco_retry

Retry "tries" times, with initial "delay", increasing delay "delay*backoff" each time. Without exception success means when function returns valid object. With exception success when no exceptions

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/tools/__init__.py#L37-L71

qubell/contrib-python-qubell-client

qubell/api/tools/__init__.py

dump

def dump(node): """ Dump initialized object structure to yaml """ from qubell.api.private.platform import Auth, QubellPlatform from qubell.api.private.organization import Organization from qubell.api.private.application import Application from qubell.api.private.instance import Instance from qubell.api.private.revision import Revision from qubell.api.private.environment import Environment from qubell.api.private.zone import Zone from qubell.api.private.manifest import Manifest # Exclude keys from dump # Format: { 'ClassName': ['fields', 'to', 'exclude']} exclusion_list = { Auth: ['cookies'], QubellPlatform:['auth', ], Organization: ['auth', 'organizationId', 'zone'], Application: ['auth', 'applicationId', 'organization'], Instance: ['auth', 'instanceId', 'application'], Manifest: ['name', 'content'], Revision: ['auth', 'revisionId'], Environment: ['auth', 'environmentId', 'organization'], Zone: ['auth', 'zoneId', 'organization'], } def obj_presenter(dumper, obj): for x in exclusion_list.keys(): if isinstance(obj, x): # Find class fields = obj.__dict__.copy() for excl_item in exclusion_list[x]: try: fields.pop(excl_item) except: log.warn('No item %s in object %s' % (excl_item, x)) return dumper.represent_mapping('tag:yaml.org,2002:map', fields) return dumper.represent_mapping('tag:yaml.org,2002:map', obj.__dict__) noalias_dumper = yaml.dumper.Dumper noalias_dumper.ignore_aliases = lambda self, data: True yaml.add_representer(unicode, lambda dumper, value: dumper.represent_scalar(u'tag:yaml.org,2002:str', value)) yaml.add_multi_representer(object, obj_presenter) serialized = yaml.dump(node, default_flow_style=False, Dumper=noalias_dumper) return serialized

python

def dump(node): """ Dump initialized object structure to yaml """ from qubell.api.private.platform import Auth, QubellPlatform from qubell.api.private.organization import Organization from qubell.api.private.application import Application from qubell.api.private.instance import Instance from qubell.api.private.revision import Revision from qubell.api.private.environment import Environment from qubell.api.private.zone import Zone from qubell.api.private.manifest import Manifest # Exclude keys from dump # Format: { 'ClassName': ['fields', 'to', 'exclude']} exclusion_list = { Auth: ['cookies'], QubellPlatform:['auth', ], Organization: ['auth', 'organizationId', 'zone'], Application: ['auth', 'applicationId', 'organization'], Instance: ['auth', 'instanceId', 'application'], Manifest: ['name', 'content'], Revision: ['auth', 'revisionId'], Environment: ['auth', 'environmentId', 'organization'], Zone: ['auth', 'zoneId', 'organization'], } def obj_presenter(dumper, obj): for x in exclusion_list.keys(): if isinstance(obj, x): # Find class fields = obj.__dict__.copy() for excl_item in exclusion_list[x]: try: fields.pop(excl_item) except: log.warn('No item %s in object %s' % (excl_item, x)) return dumper.represent_mapping('tag:yaml.org,2002:map', fields) return dumper.represent_mapping('tag:yaml.org,2002:map', obj.__dict__) noalias_dumper = yaml.dumper.Dumper noalias_dumper.ignore_aliases = lambda self, data: True yaml.add_representer(unicode, lambda dumper, value: dumper.represent_scalar(u'tag:yaml.org,2002:str', value)) yaml.add_multi_representer(object, obj_presenter) serialized = yaml.dump(node, default_flow_style=False, Dumper=noalias_dumper) return serialized

Dump initialized object structure to yaml

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/tools/__init__.py#L145-L191

qubell/contrib-python-qubell-client

qubell/api/tools/__init__.py

load_env

def load_env(file): """ Generate environment used for 'org.restore' method :param file: env file :return: env """ env = yaml.load(open(file)) for org in env.get('organizations', []): if not org.get('applications'): org['applications'] = [] if org.get('starter-kit'): kit_meta = get_starter_kit_meta(org.get('starter-kit')) for meta_app in get_applications_from_metadata(kit_meta): org['applications'].append(meta_app) if org.get('meta'): for meta_app in get_applications_from_metadata(org.get('meta')): org['applications'].append(meta_app) for app in org.get('applications', []): if app.get('file'): app['file'] = os.path.realpath(os.path.join(os.path.dirname(file), app['file'])) return env

python

def load_env(file): """ Generate environment used for 'org.restore' method :param file: env file :return: env """ env = yaml.load(open(file)) for org in env.get('organizations', []): if not org.get('applications'): org['applications'] = [] if org.get('starter-kit'): kit_meta = get_starter_kit_meta(org.get('starter-kit')) for meta_app in get_applications_from_metadata(kit_meta): org['applications'].append(meta_app) if org.get('meta'): for meta_app in get_applications_from_metadata(org.get('meta')): org['applications'].append(meta_app) for app in org.get('applications', []): if app.get('file'): app['file'] = os.path.realpath(os.path.join(os.path.dirname(file), app['file'])) return env

Generate environment used for 'org.restore' method :param file: env file :return: env

train

https://github.com/qubell/contrib-python-qubell-client/blob/4586ea11d5103c2ff9607d3ed922b5a0991b8845/qubell/api/tools/__init__.py#L198-L223