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proteanhq/protean
src/protean/core/provider/__init__.py
Providers._initialize_providers
def _initialize_providers(self): """Read config file and initialize providers""" configured_providers = active_config.DATABASES provider_objects = {} if not isinstance(configured_providers, dict) or configured_providers == {}: raise ConfigurationError( "'DATA...
python
def _initialize_providers(self): """Read config file and initialize providers""" configured_providers = active_config.DATABASES provider_objects = {} if not isinstance(configured_providers, dict) or configured_providers == {}: raise ConfigurationError( "'DATA...
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Read config file and initialize providers
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train
https://github.com/proteanhq/protean/blob/0e29873f4aa634aa93cc08ed675dd749c7ed4b0f/src/protean/core/provider/__init__.py#L14-L35
proteanhq/protean
src/protean/core/provider/__init__.py
Providers.get_provider
def get_provider(self, provider_name='default'): """Fetch provider with the name specified in Configuration file""" try: if self._providers is None: self._providers = self._initialize_providers() return self._providers[provider_name] except KeyError: ...
python
def get_provider(self, provider_name='default'): """Fetch provider with the name specified in Configuration file""" try: if self._providers is None: self._providers = self._initialize_providers() return self._providers[provider_name] except KeyError: ...
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train
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proteanhq/protean
src/protean/core/provider/__init__.py
Providers.get_connection
def get_connection(self, provider_name='default'): """Fetch connection from Provider""" try: return self._providers[provider_name].get_connection() except KeyError: raise AssertionError(f'No Provider registered with name {provider_name}')
python
def get_connection(self, provider_name='default'): """Fetch connection from Provider""" try: return self._providers[provider_name].get_connection() except KeyError: raise AssertionError(f'No Provider registered with name {provider_name}')
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Fetch connection from Provider
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train
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proteanhq/protean
src/protean/conf/__init__.py
Config.update_defaults
def update_defaults(self, ext_config): """ Update the default settings for an extension from an object""" for setting in dir(ext_config): if setting.isupper() and not hasattr(self, setting): setattr(self, setting, getattr(ext_config, setting))
python
def update_defaults(self, ext_config): """ Update the default settings for an extension from an object""" for setting in dir(ext_config): if setting.isupper() and not hasattr(self, setting): setattr(self, setting, getattr(ext_config, setting))
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deep-compute/deeputil
deeputil/keep_running.py
keeprunning
def keeprunning(wait_secs=0, exit_on_success=False, on_success=None, on_error=None, on_done=None): ''' Example 1: dosomething needs to run until completion condition without needing to have a loop in its code. Also, when error happens, we should NOT terminate execution >>> from deep...
python
def keeprunning(wait_secs=0, exit_on_success=False, on_success=None, on_error=None, on_done=None): ''' Example 1: dosomething needs to run until completion condition without needing to have a loop in its code. Also, when error happens, we should NOT terminate execution >>> from deep...
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Example 1: dosomething needs to run until completion condition without needing to have a loop in its code. Also, when error happens, we should NOT terminate execution >>> from deeputil import AttrDict >>> @keeprunning(wait_secs=1) ... def dosomething(state): ... state.i += 1 ... pri...
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train
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proteanhq/protean
src/protean/core/field/utils.py
fetch_entity_cls_from_registry
def fetch_entity_cls_from_registry(entity): """Util Method to fetch an Entity class from an entity's name""" # Defensive check to ensure we only process if `to_cls` is a string if isinstance(entity, str): try: return repo_factory.get_entity(entity) except AssertionError: ...
python
def fetch_entity_cls_from_registry(entity): """Util Method to fetch an Entity class from an entity's name""" # Defensive check to ensure we only process if `to_cls` is a string if isinstance(entity, str): try: return repo_factory.get_entity(entity) except AssertionError: ...
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory.register
def register(self, entity_cls, provider_name=None): """ Register the given model with the factory :param entity_cls: Entity class to be registered :param provider: Optional provider to associate with Entity class """ self._validate_entity_cls(entity_cls) # Register the e...
python
def register(self, entity_cls, provider_name=None): """ Register the given model with the factory :param entity_cls: Entity class to be registered :param provider: Optional provider to associate with Entity class """ self._validate_entity_cls(entity_cls) # Register the e...
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train
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory._find_entity_in_records_by_class_name
def _find_entity_in_records_by_class_name(self, entity_name): """Fetch by Entity Name in values""" records = { key: value for (key, value) in self._registry.items() if value.name == entity_name } # If more than one record was found, we are dealing with...
python
def _find_entity_in_records_by_class_name(self, entity_name): """Fetch by Entity Name in values""" records = { key: value for (key, value) in self._registry.items() if value.name == entity_name } # If more than one record was found, we are dealing with...
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train
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory._get_entity_by_class
def _get_entity_by_class(self, entity_cls): """Fetch Entity record with Entity class details""" entity_qualname = fully_qualified_name(entity_cls) if entity_qualname in self._registry: return self._registry[entity_qualname] else: return self._find_entity_in_record...
python
def _get_entity_by_class(self, entity_cls): """Fetch Entity record with Entity class details""" entity_qualname = fully_qualified_name(entity_cls) if entity_qualname in self._registry: return self._registry[entity_qualname] else: return self._find_entity_in_record...
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train
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory._get_entity_by_name
def _get_entity_by_name(self, entity_name): """Fetch Entity record with an Entity name""" if entity_name in self._registry: return self._registry[entity_name] else: return self._find_entity_in_records_by_class_name(entity_name)
python
def _get_entity_by_name(self, entity_name): """Fetch Entity record with an Entity name""" if entity_name in self._registry: return self._registry[entity_name] else: return self._find_entity_in_records_by_class_name(entity_name)
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train
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory._validate_entity_cls
def _validate_entity_cls(self, entity_cls): """Validate that Entity is a valid class""" # Import here to avoid cyclic dependency from protean.core.entity import Entity if not issubclass(entity_cls, Entity): raise AssertionError( f'Entity {entity_cls.__name__}...
python
def _validate_entity_cls(self, entity_cls): """Validate that Entity is a valid class""" # Import here to avoid cyclic dependency from protean.core.entity import Entity if not issubclass(entity_cls, Entity): raise AssertionError( f'Entity {entity_cls.__name__}...
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Validate that Entity is a valid class
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train
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory.get_model
def get_model(self, entity_cls): """Retrieve Model class connected to Entity""" entity_record = self._get_entity_by_class(entity_cls) model_cls = None if entity_record.model_cls: model_cls = entity_record.model_cls else: # We should ask the Provider to gi...
python
def get_model(self, entity_cls): """Retrieve Model class connected to Entity""" entity_record = self._get_entity_by_class(entity_cls) model_cls = None if entity_record.model_cls: model_cls = entity_record.model_cls else: # We should ask the Provider to gi...
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Retrieve Model class connected to Entity
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proteanhq/protean
src/protean/core/repository/factory.py
RepositoryFactory.get_repository
def get_repository(self, entity_cls): """Retrieve a Repository for the Model with a live connection""" entity_record = self._get_entity_by_class(entity_cls) provider = self.get_provider(entity_record.provider_name) return provider.get_repository(entity_record.entity_cls)
python
def get_repository(self, entity_cls): """Retrieve a Repository for the Model with a live connection""" entity_record = self._get_entity_by_class(entity_cls) provider = self.get_provider(entity_record.provider_name) return provider.get_repository(entity_record.entity_cls)
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Danielhiversen/pymill
mill/__init__.py
set_heater_values
async def set_heater_values(heater_data, heater): """Set heater values from heater data""" heater.current_temp = heater_data.get('currentTemp') heater.device_status = heater_data.get('deviceStatus') heater.available = heater.device_status == 0 heater.name = heater_data.get('deviceName') heater.f...
python
async def set_heater_values(heater_data, heater): """Set heater values from heater data""" heater.current_temp = heater_data.get('currentTemp') heater.device_status = heater_data.get('deviceStatus') heater.available = heater.device_status == 0 heater.name = heater_data.get('deviceName') heater.f...
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Set heater values from heater data
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Danielhiversen/pymill
mill/__init__.py
Mill.connect
async def connect(self, retry=2): """Connect to Mill.""" # pylint: disable=too-many-return-statements url = API_ENDPOINT_1 + 'login' headers = { "Content-Type": "application/x-zc-object", "Connection": "Keep-Alive", "X-Zc-Major-Domain": "seanywell", ...
python
async def connect(self, retry=2): """Connect to Mill.""" # pylint: disable=too-many-return-statements url = API_ENDPOINT_1 + 'login' headers = { "Content-Type": "application/x-zc-object", "Connection": "Keep-Alive", "X-Zc-Major-Domain": "seanywell", ...
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Connect to Mill.
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_connect
def sync_connect(self): """Close the Mill connection.""" loop = asyncio.get_event_loop() task = loop.create_task(self.connect()) loop.run_until_complete(task)
python
def sync_connect(self): """Close the Mill connection.""" loop = asyncio.get_event_loop() task = loop.create_task(self.connect()) loop.run_until_complete(task)
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Close the Mill connection.
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_close_connection
def sync_close_connection(self): """Close the Mill connection.""" loop = asyncio.get_event_loop() task = loop.create_task(self.close_connection()) loop.run_until_complete(task)
python
def sync_close_connection(self): """Close the Mill connection.""" loop = asyncio.get_event_loop() task = loop.create_task(self.close_connection()) loop.run_until_complete(task)
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Danielhiversen/pymill
mill/__init__.py
Mill.request
async def request(self, command, payload, retry=3): """Request data.""" # pylint: disable=too-many-return-statements if self._token is None: _LOGGER.error("No token") return None _LOGGER.debug(command, payload) nonce = ''.join(random.choice(string.ascii...
python
async def request(self, command, payload, retry=3): """Request data.""" # pylint: disable=too-many-return-statements if self._token is None: _LOGGER.error("No token") return None _LOGGER.debug(command, payload) nonce = ''.join(random.choice(string.ascii...
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Request data.
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train
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_request
def sync_request(self, command, payload, retry=2): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.request(command, payload, retry)) return loop.run_until_complete(task)
python
def sync_request(self, command, payload, retry=2): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.request(command, payload, retry)) return loop.run_until_complete(task)
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Request data.
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Danielhiversen/pymill
mill/__init__.py
Mill.update_rooms
async def update_rooms(self): """Request data.""" homes = await self.get_home_list() for home in homes: payload = {"homeId": home.get("homeId"), "timeZoneNum": "+01:00"} data = await self.request("selectRoombyHome", payload) rooms = data.get('roomInfo', []) ...
python
async def update_rooms(self): """Request data.""" homes = await self.get_home_list() for home in homes: payload = {"homeId": home.get("homeId"), "timeZoneNum": "+01:00"} data = await self.request("selectRoombyHome", payload) rooms = data.get('roomInfo', []) ...
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_update_rooms
def sync_update_rooms(self): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.update_rooms()) return loop.run_until_complete(task)
python
def sync_update_rooms(self): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.update_rooms()) return loop.run_until_complete(task)
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Danielhiversen/pymill
mill/__init__.py
Mill.set_room_temperatures_by_name
async def set_room_temperatures_by_name(self, room_name, sleep_temp=None, comfort_temp=None, away_temp=None): """Set room temps by name.""" if sleep_temp is None and comfort_temp is None and away_temp is None: return for room_id, _room in s...
python
async def set_room_temperatures_by_name(self, room_name, sleep_temp=None, comfort_temp=None, away_temp=None): """Set room temps by name.""" if sleep_temp is None and comfort_temp is None and away_temp is None: return for room_id, _room in s...
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Set room temps by name.
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Danielhiversen/pymill
mill/__init__.py
Mill.set_room_temperatures
async def set_room_temperatures(self, room_id, sleep_temp=None, comfort_temp=None, away_temp=None): """Set room temps.""" if sleep_temp is None and comfort_temp is None and away_temp is None: return room = self.rooms.get(room_id) if room is...
python
async def set_room_temperatures(self, room_id, sleep_temp=None, comfort_temp=None, away_temp=None): """Set room temps.""" if sleep_temp is None and comfort_temp is None and away_temp is None: return room = self.rooms.get(room_id) if room is...
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Set room temps.
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Danielhiversen/pymill
mill/__init__.py
Mill.update_heaters
async def update_heaters(self): """Request data.""" homes = await self.get_home_list() for home in homes: payload = {"homeId": home.get("homeId")} data = await self.request("getIndependentDevices", payload) if data is None: continue ...
python
async def update_heaters(self): """Request data.""" homes = await self.get_home_list() for home in homes: payload = {"homeId": home.get("homeId")} data = await self.request("getIndependentDevices", payload) if data is None: continue ...
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_update_heaters
def sync_update_heaters(self): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.update_heaters()) loop.run_until_complete(task)
python
def sync_update_heaters(self): """Request data.""" loop = asyncio.get_event_loop() task = loop.create_task(self.update_heaters()) loop.run_until_complete(task)
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Danielhiversen/pymill
mill/__init__.py
Mill.throttle_update_heaters
async def throttle_update_heaters(self): """Throttle update device.""" if (self._throttle_time is not None and dt.datetime.now() - self._throttle_time < MIN_TIME_BETWEEN_UPDATES): return self._throttle_time = dt.datetime.now() await self.update_heaters()
python
async def throttle_update_heaters(self): """Throttle update device.""" if (self._throttle_time is not None and dt.datetime.now() - self._throttle_time < MIN_TIME_BETWEEN_UPDATES): return self._throttle_time = dt.datetime.now() await self.update_heaters()
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Danielhiversen/pymill
mill/__init__.py
Mill.throttle_update_all_heaters
async def throttle_update_all_heaters(self): """Throttle update all devices and rooms.""" if (self._throttle_all_time is not None and dt.datetime.now() - self._throttle_all_time < MIN_TIME_BETWEEN_UPDATES): return self._throttle_all_time = dt.datetime....
python
async def throttle_update_all_heaters(self): """Throttle update all devices and rooms.""" if (self._throttle_all_time is not None and dt.datetime.now() - self._throttle_all_time < MIN_TIME_BETWEEN_UPDATES): return self._throttle_all_time = dt.datetime....
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Danielhiversen/pymill
mill/__init__.py
Mill.heater_control
async def heater_control(self, device_id, fan_status=None, power_status=None): """Set heater temps.""" heater = self.heaters.get(device_id) if heater is None: _LOGGER.error("No such device") return if fan_status is None: fa...
python
async def heater_control(self, device_id, fan_status=None, power_status=None): """Set heater temps.""" heater = self.heaters.get(device_id) if heater is None: _LOGGER.error("No such device") return if fan_status is None: fa...
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_heater_control
def sync_heater_control(self, device_id, fan_status=None, power_status=None): """Set heater temps.""" loop = asyncio.get_event_loop() task = loop.create_task(self.heater_control(device_id, fan_status, ...
python
def sync_heater_control(self, device_id, fan_status=None, power_status=None): """Set heater temps.""" loop = asyncio.get_event_loop() task = loop.create_task(self.heater_control(device_id, fan_status, ...
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Danielhiversen/pymill
mill/__init__.py
Mill.set_heater_temp
async def set_heater_temp(self, device_id, set_temp): """Set heater temp.""" payload = {"homeType": 0, "timeZoneNum": "+02:00", "deviceId": device_id, "value": int(set_temp), "key": "holidayTemp"} await self.request("cha...
python
async def set_heater_temp(self, device_id, set_temp): """Set heater temp.""" payload = {"homeType": 0, "timeZoneNum": "+02:00", "deviceId": device_id, "value": int(set_temp), "key": "holidayTemp"} await self.request("cha...
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Danielhiversen/pymill
mill/__init__.py
Mill.sync_set_heater_temp
def sync_set_heater_temp(self, device_id, set_temp): """Set heater temps.""" loop = asyncio.get_event_loop() task = loop.create_task(self.set_heater_temp(device_id, set_temp)) loop.run_until_complete(task)
python
def sync_set_heater_temp(self, device_id, set_temp): """Set heater temps.""" loop = asyncio.get_event_loop() task = loop.create_task(self.set_heater_temp(device_id, set_temp)) loop.run_until_complete(task)
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tadashi-aikawa/jumeaux
jumeaux/addons/log2reqs/csv.py
Executor.exec
def exec(self, payload: Log2ReqsAddOnPayload) -> TList[Request]: """Transform csv as below. "title1","/path1","a=1&b=2","header1=1&header2=2" "title2","/path2","c=1" "title3","/path3",,"header1=1&header2=2" "title4","/path4" Exception: ValueEr...
python
def exec(self, payload: Log2ReqsAddOnPayload) -> TList[Request]: """Transform csv as below. "title1","/path1","a=1&b=2","header1=1&header2=2" "title2","/path2","c=1" "title3","/path3",,"header1=1&header2=2" "title4","/path4" Exception: ValueEr...
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wasp/waspy
waspy/app.py
Application.handle_request
async def handle_request(self, request: Request) -> Response: """ coroutine: This method is called by Transport implementation to handle the actual request. It returns a webtype.Response object. """ # Get handler try: try: self._set_ctx...
python
async def handle_request(self, request: Request) -> Response: """ coroutine: This method is called by Transport implementation to handle the actual request. It returns a webtype.Response object. """ # Get handler try: try: self._set_ctx...
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coroutine: This method is called by Transport implementation to handle the actual request. It returns a webtype.Response object.
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martinmcbride/pysound
pysound/effects.py
echo
def echo(params, source, delay, strength): ''' Create an echo :param params: :param source: :param delay: :param strength: :return: ''' source = create_buffer(params, source) delay = create_buffer(params, delay) strength = create_buffer(params, strength) output = source[:...
python
def echo(params, source, delay, strength): ''' Create an echo :param params: :param source: :param delay: :param strength: :return: ''' source = create_buffer(params, source) delay = create_buffer(params, delay) strength = create_buffer(params, strength) output = source[:...
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proteanhq/protean
src/protean/core/queryset.py
QuerySet._clone
def _clone(self): """ Return a copy of the current QuerySet. """ clone = self.__class__(self._entity_cls, criteria=self._criteria, offset=self._offset, limit=self._limit, order_by=self._order_by) return clone
python
def _clone(self): """ Return a copy of the current QuerySet. """ clone = self.__class__(self._entity_cls, criteria=self._criteria, offset=self._offset, limit=self._limit, order_by=self._order_by) return clone
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proteanhq/protean
src/protean/core/queryset.py
QuerySet._add_q
def _add_q(self, q_object): """Add a Q-object to the current filter.""" self._criteria = self._criteria._combine(q_object, q_object.connector)
python
def _add_q(self, q_object): """Add a Q-object to the current filter.""" self._criteria = self._criteria._combine(q_object, q_object.connector)
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.limit
def limit(self, limit): """Limit number of records""" clone = self._clone() if isinstance(limit, int): clone._limit = limit return clone
python
def limit(self, limit): """Limit number of records""" clone = self._clone() if isinstance(limit, int): clone._limit = limit return clone
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.offset
def offset(self, offset): """Fetch results after `offset` value""" clone = self._clone() if isinstance(offset, int): clone._offset = offset return clone
python
def offset(self, offset): """Fetch results after `offset` value""" clone = self._clone() if isinstance(offset, int): clone._offset = offset return clone
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.order_by
def order_by(self, order_by: Union[set, str]): """Update order_by setting for filter set""" clone = self._clone() if isinstance(order_by, str): order_by = {order_by} clone._order_by = clone._order_by.union(order_by) return clone
python
def order_by(self, order_by: Union[set, str]): """Update order_by setting for filter set""" clone = self._clone() if isinstance(order_by, str): order_by = {order_by} clone._order_by = clone._order_by.union(order_by) return clone
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.all
def all(self): """Primary method to fetch data based on filters Also trigged when the QuerySet is evaluated by calling one of the following methods: * len() * bool() * list() * Iteration * Slicing """ logger.debug(f'Query `{sel...
python
def all(self): """Primary method to fetch data based on filters Also trigged when the QuerySet is evaluated by calling one of the following methods: * len() * bool() * list() * Iteration * Slicing """ logger.debug(f'Query `{sel...
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.update
def update(self, *data, **kwargs): """Updates all objects with details given if they match a set of conditions supplied. This method updates each object individually, to fire callback methods and ensure validations are run. Returns the number of objects matched (which may not be equal ...
python
def update(self, *data, **kwargs): """Updates all objects with details given if they match a set of conditions supplied. This method updates each object individually, to fire callback methods and ensure validations are run. Returns the number of objects matched (which may not be equal ...
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.raw
def raw(self, query: Any, data: Any = None): """Runs raw query directly on the database and returns Entity objects Note that this method will raise an exception if the returned objects are not of the Entity type. `query` is not checked for correctness or validity, and any errors th...
python
def raw(self, query: Any, data: Any = None): """Runs raw query directly on the database and returns Entity objects Note that this method will raise an exception if the returned objects are not of the Entity type. `query` is not checked for correctness or validity, and any errors th...
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.delete
def delete(self): """Deletes matching objects from the Repository Does not throw error if no objects are matched. Returns the number of objects matched (which may not be equal to the number of objects deleted if objects rows already have the new value). """ # Fetch ...
python
def delete(self): """Deletes matching objects from the Repository Does not throw error if no objects are matched. Returns the number of objects matched (which may not be equal to the number of objects deleted if objects rows already have the new value). """ # Fetch ...
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.update_all
def update_all(self, *args, **kwargs): """Updates all objects with details given if they match a set of conditions supplied. This method forwards filters and updates directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Up...
python
def update_all(self, *args, **kwargs): """Updates all objects with details given if they match a set of conditions supplied. This method forwards filters and updates directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Up...
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Updates all objects with details given if they match a set of conditions supplied. This method forwards filters and updates directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Update values can be specified either as a dict, or ...
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train
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.delete_all
def delete_all(self, *args, **kwargs): """Deletes objects that match a set of conditions supplied. This method forwards filters directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Returns the number of objects matched an...
python
def delete_all(self, *args, **kwargs): """Deletes objects that match a set of conditions supplied. This method forwards filters directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Returns the number of objects matched an...
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Deletes objects that match a set of conditions supplied. This method forwards filters directly to the repository. It does not instantiate entities and it does not trigger Entity callbacks or validations. Returns the number of objects matched and deleted.
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train
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.total
def total(self): """Return the total number of records""" if self._result_cache: return self._result_cache.total return self.all().total
python
def total(self): """Return the total number of records""" if self._result_cache: return self._result_cache.total return self.all().total
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train
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.items
def items(self): """Return result values""" if self._result_cache: return self._result_cache.items return self.all().items
python
def items(self): """Return result values""" if self._result_cache: return self._result_cache.items return self.all().items
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train
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.first
def first(self): """Return the first result""" if self._result_cache: return self._result_cache.first return self.all().first
python
def first(self): """Return the first result""" if self._result_cache: return self._result_cache.first return self.all().first
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train
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.has_next
def has_next(self): """Return True if there are more values present""" if self._result_cache: return self._result_cache.has_next return self.all().has_next
python
def has_next(self): """Return True if there are more values present""" if self._result_cache: return self._result_cache.has_next return self.all().has_next
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Return True if there are more values present
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proteanhq/protean
src/protean/core/queryset.py
QuerySet.has_prev
def has_prev(self): """Return True if there are previous values present""" if self._result_cache: return self._result_cache.has_prev return self.all().has_prev
python
def has_prev(self): """Return True if there are previous values present""" if self._result_cache: return self._result_cache.has_prev return self.all().has_prev
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proteanhq/protean
src/protean/services/email/utils.py
get_connection
def get_connection(backend=None, fail_silently=False, **kwargs): """Load an email backend and return an instance of it. If backend is None (default), use settings.EMAIL_BACKEND. Both fail_silently and other keyword arguments are used in the constructor of the backend. """ klass = perform_import(...
python
def get_connection(backend=None, fail_silently=False, **kwargs): """Load an email backend and return an instance of it. If backend is None (default), use settings.EMAIL_BACKEND. Both fail_silently and other keyword arguments are used in the constructor of the backend. """ klass = perform_import(...
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proteanhq/protean
src/protean/services/email/utils.py
send_mail
def send_mail(subject, message, recipient_list, from_email=None, fail_silently=False, auth_user=None, auth_password=None, connection=None, **kwargs): """ Easy wrapper for sending a single message to a recipient list. All members of the recipient list will see the other recipients...
python
def send_mail(subject, message, recipient_list, from_email=None, fail_silently=False, auth_user=None, auth_password=None, connection=None, **kwargs): """ Easy wrapper for sending a single message to a recipient list. All members of the recipient list will see the other recipients...
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proteanhq/protean
src/protean/services/email/utils.py
send_mass_mail
def send_mass_mail(data_tuple, fail_silently=False, auth_user=None, auth_password=None, connection=None): """ Given a data_tuple of (subject, message, from_email, recipient_list), send each message to each recipient list. Return the number of emails sent. If from_email is None, use th...
python
def send_mass_mail(data_tuple, fail_silently=False, auth_user=None, auth_password=None, connection=None): """ Given a data_tuple of (subject, message, from_email, recipient_list), send each message to each recipient list. Return the number of emails sent. If from_email is None, use th...
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.value
def value(self): """Utility method to retrieve Response Object information""" # Set the code to the status value if isinstance(self.code, Status): code = self.code.value else: code = self.code return {'code': code, 'errors': self.errors}
python
def value(self): """Utility method to retrieve Response Object information""" # Set the code to the status value if isinstance(self.code, Status): code = self.code.value else: code = self.code return {'code': code, 'errors': self.errors}
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_response
def build_response(cls, code=Status.SYSTEM_ERROR, errors=None): """Utility method to build a new Resource Error object. Can be used to build all kinds of error messages. """ errors = [errors] if not isinstance(errors, list) else errors return cls(code, errors)
python
def build_response(cls, code=Status.SYSTEM_ERROR, errors=None): """Utility method to build a new Resource Error object. Can be used to build all kinds of error messages. """ errors = [errors] if not isinstance(errors, list) else errors return cls(code, errors)
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_from_invalid_request
def build_from_invalid_request(cls, invalid_request_object): """Utility method to build a new Error object from parameters. Typically used to build HTTP 422 error response.""" errors = [{err['parameter']: err['message']} for err in invalid_request_object.errors] return cls.build_response...
python
def build_from_invalid_request(cls, invalid_request_object): """Utility method to build a new Error object from parameters. Typically used to build HTTP 422 error response.""" errors = [{err['parameter']: err['message']} for err in invalid_request_object.errors] return cls.build_response...
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_not_found
def build_not_found(cls, errors=None): """Utility method to build a HTTP 404 Resource Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.NOT_FOUND, errors)
python
def build_not_found(cls, errors=None): """Utility method to build a HTTP 404 Resource Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.NOT_FOUND, errors)
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_system_error
def build_system_error(cls, errors=None): """Utility method to build a HTTP 500 System Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.SYSTEM_ERROR, errors)
python
def build_system_error(cls, errors=None): """Utility method to build a HTTP 500 System Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.SYSTEM_ERROR, errors)
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_parameters_error
def build_parameters_error(cls, errors=None): """Utility method to build a HTTP 400 Parameter Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.PARAMETERS_ERROR, errors)
python
def build_parameters_error(cls, errors=None): """Utility method to build a HTTP 400 Parameter Error response""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.PARAMETERS_ERROR, errors)
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proteanhq/protean
src/protean/core/transport/response.py
ResponseFailure.build_unprocessable_error
def build_unprocessable_error(cls, errors=None): """Utility method to build a HTTP 422 Parameter Error object""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.UNPROCESSABLE_ENTITY, errors)
python
def build_unprocessable_error(cls, errors=None): """Utility method to build a HTTP 422 Parameter Error object""" errors = [errors] if not isinstance(errors, list) else errors return cls(Status.UNPROCESSABLE_ENTITY, errors)
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martinmcbride/pysound
pysound/envelopes.py
linseg
def linseg(params, start=0, end=1): ''' Signal starts at start value, ramps linearly up to end value :param params: buffer parameters, controls length of signal created :param start: start value (number) :param end: end value (number) :return: array of resulting signal ''' return np.lins...
python
def linseg(params, start=0, end=1): ''' Signal starts at start value, ramps linearly up to end value :param params: buffer parameters, controls length of signal created :param start: start value (number) :param end: end value (number) :return: array of resulting signal ''' return np.lins...
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martinmcbride/pysound
pysound/envelopes.py
attack_decay
def attack_decay(params, attack, start=0, peak=1): ''' Signal starts at min value, ramps linearly up to max value during the attack time, than ramps back down to min value over remaining time :param params: buffer parameters, controls length of signal created :param attack: attack time, in samples ...
python
def attack_decay(params, attack, start=0, peak=1): ''' Signal starts at min value, ramps linearly up to max value during the attack time, than ramps back down to min value over remaining time :param params: buffer parameters, controls length of signal created :param attack: attack time, in samples ...
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martinmcbride/pysound
pysound/envelopes.py
GenericEnvelope.set
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python
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martinmcbride/pysound
pysound/envelopes.py
GenericEnvelope.linseg
def linseg(self, value, samples): ''' Create a linear section moving from current value to new value over acertain number of samples. :param value: New value :param samples: Length of segment in samples :return: ''' if self.params.length > self.pos and sam...
python
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heroku/salesforce-oauth-request
salesforce_oauth_request/utils.py
oauth_flow
def oauth_flow(s, oauth_url, username=None, password=None, sandbox=False): """s should be a requests session""" r = s.get(oauth_url) if r.status_code >= 300: raise RuntimeError(r.text) params = urlparse.parse_qs(urlparse.urlparse(r.url).query) data = {"un":username, "width":256...
python
def oauth_flow(s, oauth_url, username=None, password=None, sandbox=False): """s should be a requests session""" r = s.get(oauth_url) if r.status_code >= 300: raise RuntimeError(r.text) params = urlparse.parse_qs(urlparse.urlparse(r.url).query) data = {"un":username, "width":256...
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s should be a requests session
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moonso/loqusdb
loqusdb/utils/update.py
update_database
def update_database(adapter, variant_file=None, sv_file=None, family_file=None, family_type='ped', skip_case_id=False, gq_treshold=None, case_id=None, max_window = 3000): """Update a case in the database Args: adapter: Connection to database variant_file(str): Path t...
python
def update_database(adapter, variant_file=None, sv_file=None, family_file=None, family_type='ped', skip_case_id=False, gq_treshold=None, case_id=None, max_window = 3000): """Update a case in the database Args: adapter: Connection to database variant_file(str): Path t...
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Update a case in the database Args: adapter: Connection to database variant_file(str): Path to variant file sv_file(str): Path to sv variant file family_file(str): Path to family file family_type(str): Format of family file skip_case_id(bool):...
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https://github.com/moonso/loqusdb/blob/792dcd0d461aff5adc703c49eebf58964913a513/loqusdb/utils/update.py#L23-L137
MainRo/cyclotron-py
cyclotron/router.py
make_crossroad_router
def make_crossroad_router(source, drain=False): ''' legacy crossroad implementation. deprecated ''' sink_observer = None def on_sink_subscribe(observer): nonlocal sink_observer sink_observer = observer def dispose(): nonlocal sink_observer sink_observer ...
python
def make_crossroad_router(source, drain=False): ''' legacy crossroad implementation. deprecated ''' sink_observer = None def on_sink_subscribe(observer): nonlocal sink_observer sink_observer = observer def dispose(): nonlocal sink_observer sink_observer ...
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legacy crossroad implementation. deprecated
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MainRo/cyclotron-py
cyclotron/router.py
make_error_router
def make_error_router(): """ Creates an error router An error router takes a higher order observable a input and returns two observables: One containing the flattened items of the input observable and another one containing the flattened errors of the input observable. .. image:: ../docs/asset/err...
python
def make_error_router(): """ Creates an error router An error router takes a higher order observable a input and returns two observables: One containing the flattened items of the input observable and another one containing the flattened errors of the input observable. .. image:: ../docs/asset/err...
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moonso/loqusdb
loqusdb/commands/load.py
load
def load(ctx, variant_file, sv_variants, family_file, family_type, skip_case_id, gq_treshold, case_id, ensure_index, max_window, check_profile, hard_threshold, soft_threshold): """Load the variants of a case A variant is loaded if it is observed in any individual of a case If no family file is pro...
python
def load(ctx, variant_file, sv_variants, family_file, family_type, skip_case_id, gq_treshold, case_id, ensure_index, max_window, check_profile, hard_threshold, soft_threshold): """Load the variants of a case A variant is loaded if it is observed in any individual of a case If no family file is pro...
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Load the variants of a case A variant is loaded if it is observed in any individual of a case If no family file is provided all individuals in vcf file will be considered.
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train
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moonso/loqusdb
loqusdb/plugins/mongo/adapter.py
MongoAdapter.wipe_db
def wipe_db(self): """Wipe the whole database""" logger.warning("Wiping the whole database") self.client.drop_database(self.db_name) logger.debug("Database wiped")
python
def wipe_db(self): """Wipe the whole database""" logger.warning("Wiping the whole database") self.client.drop_database(self.db_name) logger.debug("Database wiped")
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moonso/loqusdb
loqusdb/plugins/mongo/adapter.py
MongoAdapter.check_indexes
def check_indexes(self): """Check if the indexes exists""" for collection_name in INDEXES: existing_indexes = self.indexes(collection_name) indexes = INDEXES[collection_name] for index in indexes: index_name = index.document.get('name') ...
python
def check_indexes(self): """Check if the indexes exists""" for collection_name in INDEXES: existing_indexes = self.indexes(collection_name) indexes = INDEXES[collection_name] for index in indexes: index_name = index.document.get('name') ...
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moonso/loqusdb
loqusdb/plugins/mongo/adapter.py
MongoAdapter.ensure_indexes
def ensure_indexes(self): """Update the indexes""" for collection_name in INDEXES: existing_indexes = self.indexes(collection_name) indexes = INDEXES[collection_name] for index in indexes: index_name = index.document.get('name') if inde...
python
def ensure_indexes(self): """Update the indexes""" for collection_name in INDEXES: existing_indexes = self.indexes(collection_name) indexes = INDEXES[collection_name] for index in indexes: index_name = index.document.get('name') if inde...
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Update the indexes
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train
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moonso/loqusdb
loqusdb/utils/variant.py
format_info
def format_info(variant, variant_type='snv'): """Format the info field for SNV variants Args: variant(dict) variant_type(str): snv or sv Returns: vcf_info(str): A VCF formated info field """ observations = variant.get('observations',0) homozygotes = varian...
python
def format_info(variant, variant_type='snv'): """Format the info field for SNV variants Args: variant(dict) variant_type(str): snv or sv Returns: vcf_info(str): A VCF formated info field """ observations = variant.get('observations',0) homozygotes = varian...
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moonso/loqusdb
loqusdb/utils/variant.py
format_variant
def format_variant(variant, variant_type='snv'): """Convert variant information to a VCF formated string Args: variant(dict) variant_type(str) Returns: vcf_variant(str) """ chrom = variant.get('chrom') pos = variant.get('start') ref = variant.get('ref')...
python
def format_variant(variant, variant_type='snv'): """Convert variant information to a VCF formated string Args: variant(dict) variant_type(str) Returns: vcf_variant(str) """ chrom = variant.get('chrom') pos = variant.get('start') ref = variant.get('ref')...
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Convert variant information to a VCF formated string Args: variant(dict) variant_type(str) Returns: vcf_variant(str)
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yjzhang/uncurl_python
uncurl/state_estimation.py
_create_m_objective
def _create_m_objective(w, X): """ Creates an objective function and its derivative for M, given W and X Args: w (array): clusters x cells X (array): genes x cells """ clusters, cells = w.shape genes = X.shape[0] w_sum = w.sum(1) def objective(m): m = m.reshape((...
python
def _create_m_objective(w, X): """ Creates an objective function and its derivative for M, given W and X Args: w (array): clusters x cells X (array): genes x cells """ clusters, cells = w.shape genes = X.shape[0] w_sum = w.sum(1) def objective(m): m = m.reshape((...
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Creates an objective function and its derivative for M, given W and X Args: w (array): clusters x cells X (array): genes x cells
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yjzhang/uncurl_python
uncurl/state_estimation.py
initialize_from_assignments
def initialize_from_assignments(assignments, k, max_assign_weight=0.75): """ Creates a weight initialization matrix from Poisson clustering assignments. Args: assignments (array): 1D array of integers, of length cells k (int): number of states/clusters max_assign_weight (float, opti...
python
def initialize_from_assignments(assignments, k, max_assign_weight=0.75): """ Creates a weight initialization matrix from Poisson clustering assignments. Args: assignments (array): 1D array of integers, of length cells k (int): number of states/clusters max_assign_weight (float, opti...
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Creates a weight initialization matrix from Poisson clustering assignments. Args: assignments (array): 1D array of integers, of length cells k (int): number of states/clusters max_assign_weight (float, optional): between 0 and 1 - how much weight to assign to the highest cluster. Default: 0...
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train
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yjzhang/uncurl_python
uncurl/state_estimation.py
initialize_means
def initialize_means(data, clusters, k): """ Initializes the M matrix given the data and a set of cluster labels. Cluster centers are set to the mean of each cluster. Args: data (array): genes x cells clusters (array): 1d array of ints (0...k-1) k (int): number of clusters "...
python
def initialize_means(data, clusters, k): """ Initializes the M matrix given the data and a set of cluster labels. Cluster centers are set to the mean of each cluster. Args: data (array): genes x cells clusters (array): 1d array of ints (0...k-1) k (int): number of clusters "...
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Initializes the M matrix given the data and a set of cluster labels. Cluster centers are set to the mean of each cluster. Args: data (array): genes x cells clusters (array): 1d array of ints (0...k-1) k (int): number of clusters
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yjzhang/uncurl_python
uncurl/state_estimation.py
initialize_weights_nn
def initialize_weights_nn(data, means, lognorm=True): """ Initializes the weights with a nearest-neighbor approach using the means. """ # TODO genes, cells = data.shape k = means.shape[1] if lognorm: data = log1p(cell_normalize(data)) for i in range(cells): for j in range...
python
def initialize_weights_nn(data, means, lognorm=True): """ Initializes the weights with a nearest-neighbor approach using the means. """ # TODO genes, cells = data.shape k = means.shape[1] if lognorm: data = log1p(cell_normalize(data)) for i in range(cells): for j in range...
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Initializes the weights with a nearest-neighbor approach using the means.
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yjzhang/uncurl_python
uncurl/state_estimation.py
initialize_means_weights
def initialize_means_weights(data, clusters, init_means=None, init_weights=None, initialization='tsvd', max_assign_weight=0.75): """ Generates initial means and weights for state estimation. """ genes, cells = data.shape if init_means is None: if init_weights is not None: if len(...
python
def initialize_means_weights(data, clusters, init_means=None, init_weights=None, initialization='tsvd', max_assign_weight=0.75): """ Generates initial means and weights for state estimation. """ genes, cells = data.shape if init_means is None: if init_weights is not None: if len(...
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Generates initial means and weights for state estimation.
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yjzhang/uncurl_python
uncurl/state_estimation.py
poisson_estimate_state
def poisson_estimate_state(data, clusters, init_means=None, init_weights=None, method='NoLips', max_iters=30, tol=0, disp=False, inner_max_iters=100, normalize=True, initialization='tsvd', parallel=True, threads=4, max_assign_weight=0.75, run_w_first=True, constrain_w=False, regularization=0.0, write_progress_file=None...
python
def poisson_estimate_state(data, clusters, init_means=None, init_weights=None, method='NoLips', max_iters=30, tol=0, disp=False, inner_max_iters=100, normalize=True, initialization='tsvd', parallel=True, threads=4, max_assign_weight=0.75, run_w_first=True, constrain_w=False, regularization=0.0, write_progress_file=None...
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Uses a Poisson Covex Mixture model to estimate cell states and cell state mixing weights. To lower computational costs, use a sparse matrix, set disp to False, and set tol to 0. Args: data (array): genes x cells array or sparse matrix. clusters (int): number of mixture components i...
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yjzhang/uncurl_python
uncurl/state_estimation.py
update_m
def update_m(data, old_M, old_W, selected_genes, disp=False, inner_max_iters=100, parallel=True, threads=4, write_progress_file=None, tol=0.0, regularization=0.0, **kwargs): """ This returns a new M matrix that contains all genes, given an M that was created from running state estimation with a subset of ge...
python
def update_m(data, old_M, old_W, selected_genes, disp=False, inner_max_iters=100, parallel=True, threads=4, write_progress_file=None, tol=0.0, regularization=0.0, **kwargs): """ This returns a new M matrix that contains all genes, given an M that was created from running state estimation with a subset of ge...
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This returns a new M matrix that contains all genes, given an M that was created from running state estimation with a subset of genes. Args: data (sparse matrix or dense array): data matrix of shape (genes, cells), containing all genes old_M (array): shape is (selected_genes, k) old_W (...
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markperdue/pyvesync
home_assistant/custom_components/__init__.py
setup
def setup(hass, config): """Set up the VeSync component.""" from pyvesync.vesync import VeSync conf = config[DOMAIN] manager = VeSync(conf.get(CONF_USERNAME), conf.get(CONF_PASSWORD), time_zone=conf.get(CONF_TIME_ZONE)) if not manager.login(): _LOGGER.error("Unable to...
python
def setup(hass, config): """Set up the VeSync component.""" from pyvesync.vesync import VeSync conf = config[DOMAIN] manager = VeSync(conf.get(CONF_USERNAME), conf.get(CONF_PASSWORD), time_zone=conf.get(CONF_TIME_ZONE)) if not manager.login(): _LOGGER.error("Unable to...
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Set up the VeSync component.
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yjzhang/uncurl_python
uncurl/ensemble.py
state_estimation_ensemble
def state_estimation_ensemble(data, k, n_runs=10, M_list=[], **se_params): """ Runs an ensemble method on the list of M results... Args: data: genes x cells array k: number of classes n_runs (optional): number of random initializations of state estimation M_list (optional): ...
python
def state_estimation_ensemble(data, k, n_runs=10, M_list=[], **se_params): """ Runs an ensemble method on the list of M results... Args: data: genes x cells array k: number of classes n_runs (optional): number of random initializations of state estimation M_list (optional): ...
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Runs an ensemble method on the list of M results... Args: data: genes x cells array k: number of classes n_runs (optional): number of random initializations of state estimation M_list (optional): list of M arrays from state estimation se_params (optional): optional poisson_e...
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L22-L47
yjzhang/uncurl_python
uncurl/ensemble.py
nmf_ensemble
def nmf_ensemble(data, k, n_runs=10, W_list=[], **nmf_params): """ Runs an ensemble method on the list of NMF W matrices... Args: data: genes x cells array (should be log + cell-normalized) k: number of classes n_runs (optional): number of random initializations of state estimation ...
python
def nmf_ensemble(data, k, n_runs=10, W_list=[], **nmf_params): """ Runs an ensemble method on the list of NMF W matrices... Args: data: genes x cells array (should be log + cell-normalized) k: number of classes n_runs (optional): number of random initializations of state estimation ...
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L49-L79
yjzhang/uncurl_python
uncurl/ensemble.py
nmf_kfold
def nmf_kfold(data, k, n_runs=10, **nmf_params): """ Runs K-fold ensemble topic modeling (Belford et al. 2017) """ # TODO nmf = NMF(k) W_list = [] kf = KFold(n_splits=n_runs, shuffle=True) # TODO: randomly divide data into n_runs folds for train_index, test_index in kf.split(data.T):...
python
def nmf_kfold(data, k, n_runs=10, **nmf_params): """ Runs K-fold ensemble topic modeling (Belford et al. 2017) """ # TODO nmf = NMF(k) W_list = [] kf = KFold(n_splits=n_runs, shuffle=True) # TODO: randomly divide data into n_runs folds for train_index, test_index in kf.split(data.T):...
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Runs K-fold ensemble topic modeling (Belford et al. 2017)
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L81-L101
yjzhang/uncurl_python
uncurl/ensemble.py
nmf_init
def nmf_init(data, clusters, k, init='enhanced'): """ runs enhanced NMF initialization from clusterings (Gong 2013) There are 3 options for init: enhanced - uses EIn-NMF from Gong 2013 basic - uses means for W, assigns H such that the chosen cluster for a given cell has value 0.75 and all o...
python
def nmf_init(data, clusters, k, init='enhanced'): """ runs enhanced NMF initialization from clusterings (Gong 2013) There are 3 options for init: enhanced - uses EIn-NMF from Gong 2013 basic - uses means for W, assigns H such that the chosen cluster for a given cell has value 0.75 and all o...
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L110-L148
yjzhang/uncurl_python
uncurl/ensemble.py
nmf_tsne
def nmf_tsne(data, k, n_runs=10, init='enhanced', **params): """ runs tsne-consensus-NMF 1. run a bunch of NMFs, get W and H 2. run tsne + km on all WH matrices 3. run consensus clustering on all km results 4. use consensus clustering as initialization for a new run of NMF 5. return the W a...
python
def nmf_tsne(data, k, n_runs=10, init='enhanced', **params): """ runs tsne-consensus-NMF 1. run a bunch of NMFs, get W and H 2. run tsne + km on all WH matrices 3. run consensus clustering on all km results 4. use consensus clustering as initialization for a new run of NMF 5. return the W a...
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runs tsne-consensus-NMF 1. run a bunch of NMFs, get W and H 2. run tsne + km on all WH matrices 3. run consensus clustering on all km results 4. use consensus clustering as initialization for a new run of NMF 5. return the W and H from the resulting NMF run
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L150-L177
yjzhang/uncurl_python
uncurl/ensemble.py
poisson_se_multiclust
def poisson_se_multiclust(data, k, n_runs=10, **se_params): """ Initializes state estimation using a consensus of several fast clustering/dimensionality reduction algorithms. It does a consensus of 8 truncated SVD - k-means rounds, and uses the basic nmf_init to create starting points. """ ...
python
def poisson_se_multiclust(data, k, n_runs=10, **se_params): """ Initializes state estimation using a consensus of several fast clustering/dimensionality reduction algorithms. It does a consensus of 8 truncated SVD - k-means rounds, and uses the basic nmf_init to create starting points. """ ...
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Initializes state estimation using a consensus of several fast clustering/dimensionality reduction algorithms. It does a consensus of 8 truncated SVD - k-means rounds, and uses the basic nmf_init to create starting points.
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L197-L233
yjzhang/uncurl_python
uncurl/ensemble.py
poisson_consensus_se
def poisson_consensus_se(data, k, n_runs=10, **se_params): """ Initializes Poisson State Estimation using a consensus Poisson clustering. """ clusters = [] for i in range(n_runs): assignments, means = poisson_cluster(data, k) clusters.append(assignments) clusterings = np.vstack(...
python
def poisson_consensus_se(data, k, n_runs=10, **se_params): """ Initializes Poisson State Estimation using a consensus Poisson clustering. """ clusters = [] for i in range(n_runs): assignments, means = poisson_cluster(data, k) clusters.append(assignments) clusterings = np.vstack(...
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Initializes Poisson State Estimation using a consensus Poisson clustering.
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train
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yjzhang/uncurl_python
uncurl/ensemble.py
lensNMF
def lensNMF(data, k, ks=1): """ Runs L-EnsNMF on the data. (Suh et al. 2016) """ # TODO: why is this not working n_rounds = k/ks R_i = data.copy() nmf = NMF(ks) nmf2 = NMF(ks, init='custom') w_is = [] h_is = [] rs = [] w_i = np.zeros((data.shape[0], ks)) h_i = np.zero...
python
def lensNMF(data, k, ks=1): """ Runs L-EnsNMF on the data. (Suh et al. 2016) """ # TODO: why is this not working n_rounds = k/ks R_i = data.copy() nmf = NMF(ks) nmf2 = NMF(ks, init='custom') w_is = [] h_is = [] rs = [] w_i = np.zeros((data.shape[0], ks)) h_i = np.zero...
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Runs L-EnsNMF on the data. (Suh et al. 2016)
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train
https://github.com/yjzhang/uncurl_python/blob/55c58ca5670f87699d3bd5752fdfa4baa07724dd/uncurl/ensemble.py#L274-L315
moonso/loqusdb
loqusdb/utils/case.py
get_case
def get_case(family_lines, family_type='ped', vcf_path=None): """Return ped_parser case from a family file Create a dictionary with case data. If no family file is given create from VCF Args: family_lines (iterator): The family lines family_type (str): The format of the family line...
python
def get_case(family_lines, family_type='ped', vcf_path=None): """Return ped_parser case from a family file Create a dictionary with case data. If no family file is given create from VCF Args: family_lines (iterator): The family lines family_type (str): The format of the family line...
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moonso/loqusdb
loqusdb/utils/case.py
update_case
def update_case(case_obj, existing_case): """Update an existing case This will add paths to VCF files, individuals etc Args: case_obj(models.Case) existing_case(models.Case) Returns: updated_case(models.Case): Updated existing case """ variant_nrs = ['nr_va...
python
def update_case(case_obj, existing_case): """Update an existing case This will add paths to VCF files, individuals etc Args: case_obj(models.Case) existing_case(models.Case) Returns: updated_case(models.Case): Updated existing case """ variant_nrs = ['nr_va...
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fbergmann/libSEDML
examples/python/print_sedml.py
main
def main (args): """Usage: print_sedml input-filename """ if len(args) != 2: print(main.__doc__) sys.exit(1) doc = libsedml.readSedML(args[1]); if ( doc.getErrorLog().getNumFailsWithSeverity(libsedml.LIBSEDML_SEV_ERROR) > 0): print doc.getErrorLog().toString(); sys.exit(2); print 'The...
python
def main (args): """Usage: print_sedml input-filename """ if len(args) != 2: print(main.__doc__) sys.exit(1) doc = libsedml.readSedML(args[1]); if ( doc.getErrorLog().getNumFailsWithSeverity(libsedml.LIBSEDML_SEV_ERROR) > 0): print doc.getErrorLog().toString(); sys.exit(2); print 'The...
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bachya/py17track
py17track/profile.py
Profile.login
async def login(self, email: str, password: str) -> bool: """Login to the profile.""" login_resp = await self._request( 'post', API_URL_USER, json={ 'version': '1.0', 'method': 'Signin', 'param': { 'E...
python
async def login(self, email: str, password: str) -> bool: """Login to the profile.""" login_resp = await self._request( 'post', API_URL_USER, json={ 'version': '1.0', 'method': 'Signin', 'param': { 'E...
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bachya/py17track
py17track/profile.py
Profile.packages
async def packages( self, package_state: Union[int, str] = '', show_archived: bool = False) -> list: """Get the list of packages associated with the account.""" packages_resp = await self._request( 'post', API_URL_BUYER, json={ ...
python
async def packages( self, package_state: Union[int, str] = '', show_archived: bool = False) -> list: """Get the list of packages associated with the account.""" packages_resp = await self._request( 'post', API_URL_BUYER, json={ ...
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bachya/py17track
py17track/profile.py
Profile.summary
async def summary(self, show_archived: bool = False) -> dict: """Get a quick summary of how many packages are in an account.""" summary_resp = await self._request( 'post', API_URL_BUYER, json={ 'version': '1.0', 'method': 'GetIndexData'...
python
async def summary(self, show_archived: bool = False) -> dict: """Get a quick summary of how many packages are in an account.""" summary_resp = await self._request( 'post', API_URL_BUYER, json={ 'version': '1.0', 'method': 'GetIndexData'...
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markperdue/pyvesync
home_assistant/custom_components/switch.py
setup_platform
def setup_platform(hass, config, add_entities, discovery_info=None): """Set up the VeSync switch platform.""" if discovery_info is None: return switches = [] manager = hass.data[DOMAIN]['manager'] if manager.outlets is not None and manager.outlets: if len(manager.outlets) == 1: ...
python
def setup_platform(hass, config, add_entities, discovery_info=None): """Set up the VeSync switch platform.""" if discovery_info is None: return switches = [] manager = hass.data[DOMAIN]['manager'] if manager.outlets is not None and manager.outlets: if len(manager.outlets) == 1: ...
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Set up the VeSync switch platform.
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train
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markperdue/pyvesync
home_assistant/custom_components/switch.py
VeSyncSwitchHA.device_state_attributes
def device_state_attributes(self): """Return the state attributes of the device.""" attr = {} attr['active_time'] = self.smartplug.active_time attr['voltage'] = self.smartplug.voltage attr['active_time'] = self.smartplug.active_time attr['weekly_energy_total'] = self.smar...
python
def device_state_attributes(self): """Return the state attributes of the device.""" attr = {} attr['active_time'] = self.smartplug.active_time attr['voltage'] = self.smartplug.voltage attr['active_time'] = self.smartplug.active_time attr['weekly_energy_total'] = self.smar...
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Return the state attributes of the device.
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moonso/loqusdb
loqusdb/plugins/mongo/variant.py
VariantMixin._get_update
def _get_update(self, variant): """Convert a variant to a proper update Args: variant(dict) Returns: update(dict) """ update = { '$inc': { 'homozygote': variant.get('homozygote', 0), ...
python
def _get_update(self, variant): """Convert a variant to a proper update Args: variant(dict) Returns: update(dict) """ update = { '$inc': { 'homozygote': variant.get('homozygote', 0), ...
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moonso/loqusdb
loqusdb/plugins/mongo/variant.py
VariantMixin.add_variant
def add_variant(self, variant): """Add a variant to the variant collection If the variant exists we update the count else we insert a new variant object. Args: variant (dict): A variant dictionary """ LOG.debug("Upserting variant...
python
def add_variant(self, variant): """Add a variant to the variant collection If the variant exists we update the count else we insert a new variant object. Args: variant (dict): A variant dictionary """ LOG.debug("Upserting variant...
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Add a variant to the variant collection If the variant exists we update the count else we insert a new variant object. Args: variant (dict): A variant dictionary
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