Search is not available for this dataset
identifier stringlengths 1 155 | parameters stringlengths 2 6.09k | docstring stringlengths 11 63.4k | docstring_summary stringlengths 0 63.4k | function stringlengths 29 99.8k | function_tokens list | start_point list | end_point list | language stringclasses 1
value | docstring_language stringlengths 2 7 | docstring_language_predictions stringlengths 18 23 | is_langid_reliable stringclasses 2
values |
|---|---|---|---|---|---|---|---|---|---|---|---|
MockDysonState.__init__ | (self) | Create new Mock Dyson State. | Create new Mock Dyson State. | def __init__(self):
"""Create new Mock Dyson State.""" | [
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71,
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72,
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MockDysonState.__repr__ | (self) | Mock repr because original one fails since constructor not called. | Mock repr because original one fails since constructor not called. | def __repr__(self):
"""Mock repr because original one fails since constructor not called."""
return "<MockDysonState>" | [
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config_entry | () | Create a mock GeoNet NZ Quakes config entry. | Create a mock GeoNet NZ Quakes config entry. | def config_entry():
"""Create a mock GeoNet NZ Quakes config entry."""
return MockConfigEntry(
domain=DOMAIN,
data={
CONF_LATITUDE: -41.2,
CONF_LONGITUDE: 174.7,
CONF_RADIUS: 25,
CONF_UNIT_SYSTEM: "metric",
CONF_SCAN_INTERVAL: 300.0,
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async_init_integration | (
hass: HomeAssistant, ups_fixture: str, resources: list
) | Set up the nexia integration in Home Assistant. | Set up the nexia integration in Home Assistant. | async def async_init_integration(
hass: HomeAssistant, ups_fixture: str, resources: list
) -> MockConfigEntry:
"""Set up the nexia integration in Home Assistant."""
ups_fixture = f"nut/{ups_fixture}.json"
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async_setup_entry | (hass, config, async_add_entities) | Initialize a Spider thermostat. | Initialize a Spider thermostat. | async def async_setup_entry(hass, config, async_add_entities):
"""Initialize a Spider thermostat."""
api = hass.data[DOMAIN][config.entry_id]
async_add_entities(
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SpiderThermostat.__init__ | (self, api, thermostat) | Initialize the thermostat. | Initialize the thermostat. | def __init__(self, api, thermostat):
"""Initialize the thermostat."""
self.api = api
self.thermostat = thermostat | [
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SpiderThermostat.supported_features | (self) | Return the list of supported features. | Return the list of supported features. | def supported_features(self):
"""Return the list of supported features."""
if self.thermostat.has_fan_mode:
return SUPPORT_TARGET_TEMPERATURE | SUPPORT_FAN_MODE
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SpiderThermostat.unique_id | (self) | Return the id of the thermostat, if any. | Return the id of the thermostat, if any. | def unique_id(self):
"""Return the id of the thermostat, if any."""
return self.thermostat.id | [
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SpiderThermostat.name | (self) | Return the name of the thermostat, if any. | Return the name of the thermostat, if any. | def name(self):
"""Return the name of the thermostat, if any."""
return self.thermostat.name | [
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SpiderThermostat.temperature_unit | (self) | Return the unit of measurement. | Return the unit of measurement. | def temperature_unit(self):
"""Return the unit of measurement."""
return TEMP_CELSIUS | [
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SpiderThermostat.current_temperature | (self) | Return the current temperature. | Return the current temperature. | def current_temperature(self):
"""Return the current temperature."""
return self.thermostat.current_temperature | [
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SpiderThermostat.target_temperature | (self) | Return the temperature we try to reach. | Return the temperature we try to reach. | def target_temperature(self):
"""Return the temperature we try to reach."""
return self.thermostat.target_temperature | [
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SpiderThermostat.target_temperature_step | (self) | Return the supported step of target temperature. | Return the supported step of target temperature. | def target_temperature_step(self):
"""Return the supported step of target temperature."""
return self.thermostat.temperature_steps | [
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SpiderThermostat.min_temp | (self) | Return the minimum temperature. | Return the minimum temperature. | def min_temp(self):
"""Return the minimum temperature."""
return self.thermostat.minimum_temperature | [
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SpiderThermostat.max_temp | (self) | Return the maximum temperature. | Return the maximum temperature. | def max_temp(self):
"""Return the maximum temperature."""
return self.thermostat.maximum_temperature | [
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SpiderThermostat.hvac_mode | (self) | Return current operation ie. heat, cool, idle. | Return current operation ie. heat, cool, idle. | def hvac_mode(self):
"""Return current operation ie. heat, cool, idle."""
return SPIDER_STATE_TO_HA[self.thermostat.operation_mode] | [
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SpiderThermostat.hvac_modes | (self) | Return the list of available operation modes. | Return the list of available operation modes. | def hvac_modes(self):
"""Return the list of available operation modes."""
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SpiderThermostat.set_temperature | (self, **kwargs) | Set new target temperature. | Set new target temperature. | def set_temperature(self, **kwargs):
"""Set new target temperature."""
temperature = kwargs.get(ATTR_TEMPERATURE)
if temperature is None:
return
self.thermostat.set_temperature(temperature) | [
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SpiderThermostat.set_hvac_mode | (self, hvac_mode) | Set new target operation mode. | Set new target operation mode. | def set_hvac_mode(self, hvac_mode):
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SpiderThermostat.fan_mode | (self) | Return the fan setting. | Return the fan setting. | def fan_mode(self):
"""Return the fan setting."""
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SpiderThermostat.set_fan_mode | (self, fan_mode) | Set fan mode. | Set fan mode. | def set_fan_mode(self, fan_mode):
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SpiderThermostat.fan_modes | (self) | List of available fan modes. | List of available fan modes. | def fan_modes(self):
"""List of available fan modes."""
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SpiderThermostat.update | (self) | Get the latest data. | Get the latest data. | def update(self):
"""Get the latest data."""
self.thermostat = self.api.get_thermostat(self.unique_id) | [
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async_setup_entry | (hass, config_entry, async_add_entities) | Set up the Tesla binary_sensors by config_entry. | Set up the Tesla binary_sensors by config_entry. | async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up the Tesla binary_sensors by config_entry."""
async_add_entities(
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TeslaBinarySensor(
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TeslaBinarySensor.device_class | (self) | Return the class of this binary sensor. | Return the class of this binary sensor. | def device_class(self):
"""Return the class of this binary sensor."""
return (
self.tesla_device.sensor_type
if self.tesla_device.sensor_type in DEVICE_CLASSES
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TeslaBinarySensor.is_on | (self) | Return the state of the binary sensor. | Return the state of the binary sensor. | def is_on(self):
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setup | (hass, base_config) | Set up the gc100 component. | Set up the gc100 component. | def setup(hass, base_config):
"""Set up the gc100 component."""
config = base_config[DOMAIN]
host = config[CONF_HOST]
port = config[CONF_PORT]
gc_device = gc100.GC100SocketClient(host, port)
def cleanup_gc100(event):
"""Stuff to do before stopping."""
gc_device.quit()
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GC100Device.__init__ | (self, hass, gc_device) | Init a gc100 device. | Init a gc100 device. | def __init__(self, hass, gc_device):
"""Init a gc100 device."""
self.hass = hass
self.gc_device = gc_device | [
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GC100Device.read_sensor | (self, port_addr, callback) | Read a value from a digital input. | Read a value from a digital input. | def read_sensor(self, port_addr, callback):
"""Read a value from a digital input."""
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GC100Device.write_switch | (self, port_addr, state, callback) | Write a value to a relay. | Write a value to a relay. | def write_switch(self, port_addr, state, callback):
"""Write a value to a relay."""
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GC100Device.subscribe | (self, port_addr, callback) | Add detection for RISING and FALLING events. | Add detection for RISING and FALLING events. | def subscribe(self, port_addr, callback):
"""Add detection for RISING and FALLING events."""
self.gc_device.subscribe_notify(port_addr, callback) | [
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async_discover_and_construct | (
hass: HomeAssistantType, udn: str = None, st: str = None
) | Discovery devices and construct a Device for one. | Discovery devices and construct a Device for one. | async def async_discover_and_construct(
hass: HomeAssistantType, udn: str = None, st: str = None
) -> Device:
"""Discovery devices and construct a Device for one."""
# pylint: disable=invalid-name
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async_setup | (hass: HomeAssistantType, config: ConfigType) | Set up UPnP component. | Set up UPnP component. | async def async_setup(hass: HomeAssistantType, config: ConfigType):
"""Set up UPnP component."""
_LOGGER.debug("async_setup, config: %s", config)
conf_default = CONFIG_SCHEMA({DOMAIN: {}})[DOMAIN]
conf = config.get(DOMAIN, conf_default)
local_ip = await hass.async_add_executor_job(get_local_ip)
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async_setup_entry | (hass: HomeAssistantType, config_entry: ConfigEntry) | Set up UPnP/IGD device from a config entry. | Set up UPnP/IGD device from a config entry. | async def async_setup_entry(hass: HomeAssistantType, config_entry: ConfigEntry) -> bool:
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async_unload_entry | (
hass: HomeAssistantType, config_entry: ConfigEntry
) | Unload a UPnP/IGD device from a config entry. | Unload a UPnP/IGD device from a config entry. | async def async_unload_entry(
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"""Unload a UPnP/IGD device from a config entry."""
udn = config_entry.data.get(CONFIG_ENTRY_UDN)
if udn in hass.data[DOMAIN][DOMAIN_DEVICES]:
del hass.data[DOMAIN][DOMAIN_DEVICES][udn]
if udn in hass... | [
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LocalCorrelatedJitter.initialize_model | (self, mc, **kwargs) | A special kind of initialization is required for this module, since it has to take a second dataset
and check the correspondence with the points
| A special kind of initialization is required for this module, since it has to take a second dataset
and check the correspondence with the points | def initialize_model(self, mc, **kwargs):
""" A special kind of initialization is required for this module, since it has to take a second dataset
and check the correspondence with the points
"""
dataset_ref = mc.dataset_dict[kwargs['reference']]
dataset_asc = mc.dataset_dict[kwa... | [
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LocalCorrelatedJitter.compute | (self, variable_value, dataset, x0_input=None) | In our array, coefficient are sorted from the lowest degree to the higher
This is the order accepted by NumPy.polynomial.polynomial.polyval ,
which is reversed with respect to from NumPy.polyval
| In our array, coefficient are sorted from the lowest degree to the higher
This is the order accepted by NumPy.polynomial.polynomial.polyval ,
which is reversed with respect to from NumPy.polyval
| def compute(self, variable_value, dataset, x0_input=None):
coeff = np.zeros(self.order+1)
for i_order in range(1, self.order+1):
var = 'c'+repr(i_order)
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x_zero = variable_value['x_zero']
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async_setup_entry | (hass, config_entry, async_add_entities) | Set up the ecobee weather platform. | Set up the ecobee weather platform. | async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up the ecobee weather platform."""
data = hass.data[DOMAIN]
dev = []
for index in range(len(data.ecobee.thermostats)):
thermostat = data.ecobee.get_thermostat(index)
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dev.ap... | [
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"ecobee... | [
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_process_forecast | (json) | Process a single ecobee API forecast to return expected values. | Process a single ecobee API forecast to return expected values. | def _process_forecast(json):
"""Process a single ecobee API forecast to return expected values."""
forecast = {}
try:
forecast[ATTR_FORECAST_CONDITION] = ECOBEE_WEATHER_SYMBOL_TO_HASS[
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foreca... | [
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EcobeeWeather.__init__ | (self, data, name, index) | Initialize the Ecobee weather platform. | Initialize the Ecobee weather platform. | def __init__(self, data, name, index):
"""Initialize the Ecobee weather platform."""
self.data = data
self._name = name
self._index = index
self.weather = None | [
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EcobeeWeather.get_forecast | (self, index, param) | Retrieve forecast parameter. | Retrieve forecast parameter. | def get_forecast(self, index, param):
"""Retrieve forecast parameter."""
try:
forecast = self.weather["forecasts"][index]
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EcobeeWeather.name | (self) | Return the name of the sensor. | Return the name of the sensor. | def name(self):
"""Return the name of the sensor."""
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EcobeeWeather.unique_id | (self) | Return a unique identifier for the weather platform. | Return a unique identifier for the weather platform. | def unique_id(self):
"""Return a unique identifier for the weather platform."""
return self.data.ecobee.get_thermostat(self._index)["identifier"] | [
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EcobeeWeather.device_info | (self) | Return device information for the ecobee weather platform. | Return device information for the ecobee weather platform. | def device_info(self):
"""Return device information for the ecobee weather platform."""
thermostat = self.data.ecobee.get_thermostat(self._index)
try:
model = f"{ECOBEE_MODEL_TO_NAME[thermostat['modelNumber']]} Thermostat"
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EcobeeWeather.condition | (self) | Return the current condition. | Return the current condition. | def condition(self):
"""Return the current condition."""
try:
return ECOBEE_WEATHER_SYMBOL_TO_HASS[self.get_forecast(0, "weatherSymbol")]
except ValueError:
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EcobeeWeather.temperature | (self) | Return the temperature. | Return the temperature. | def temperature(self):
"""Return the temperature."""
try:
return float(self.get_forecast(0, "temperature")) / 10
except ValueError:
return None | [
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EcobeeWeather.temperature_unit | (self) | Return the unit of measurement. | Return the unit of measurement. | def temperature_unit(self):
"""Return the unit of measurement."""
return TEMP_FAHRENHEIT | [
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EcobeeWeather.pressure | (self) | Return the pressure. | Return the pressure. | def pressure(self):
"""Return the pressure."""
try:
return int(self.get_forecast(0, "pressure"))
except ValueError:
return None | [
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EcobeeWeather.humidity | (self) | Return the humidity. | Return the humidity. | def humidity(self):
"""Return the humidity."""
try:
return int(self.get_forecast(0, "relativeHumidity"))
except ValueError:
return None | [
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EcobeeWeather.visibility | (self) | Return the visibility. | Return the visibility. | def visibility(self):
"""Return the visibility."""
try:
return int(self.get_forecast(0, "visibility")) / 1000
except ValueError:
return None | [
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EcobeeWeather.wind_speed | (self) | Return the wind speed. | Return the wind speed. | def wind_speed(self):
"""Return the wind speed."""
try:
return int(self.get_forecast(0, "windSpeed"))
except ValueError:
return None | [
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EcobeeWeather.wind_bearing | (self) | Return the wind direction. | Return the wind direction. | def wind_bearing(self):
"""Return the wind direction."""
try:
return int(self.get_forecast(0, "windBearing"))
except ValueError:
return None | [
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EcobeeWeather.attribution | (self) | Return the attribution. | Return the attribution. | def attribution(self):
"""Return the attribution."""
if not self.weather:
return None
station = self.weather.get("weatherStation", "UNKNOWN")
time = self.weather.get("timestamp", "UNKNOWN")
return f"Ecobee weather provided by {station} at {time} UTC" | [
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EcobeeWeather.forecast | (self) | Return the forecast array. | Return the forecast array. | def forecast(self):
"""Return the forecast array."""
if "forecasts" not in self.weather:
return None
forecasts = []
date = dt_util.utcnow()
for day in range(0, 5):
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EcobeeWeather.async_update | (self) | Get the latest weather data. | Get the latest weather data. | async def async_update(self):
"""Get the latest weather data."""
await self.data.update()
thermostat = self.data.ecobee.get_thermostat(self._index)
self.weather = thermostat.get("weather") | [
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async_setup_entry | (
hass: HomeAssistant,
entry: ConfigEntry,
async_add_entities: Callable[[List[Entity], bool], None],
) | Set up Bond light devices. | Set up Bond light devices. | async def async_setup_entry(
hass: HomeAssistant,
entry: ConfigEntry,
async_add_entities: Callable[[List[Entity], bool], None],
) -> None:
"""Set up Bond light devices."""
hub: BondHub = hass.data[DOMAIN][entry.entry_id]
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BondLight.__init__ | (
self, hub: BondHub, device: BondDevice, sub_device: Optional[str] = None
) | Create HA entity representing Bond fan. | Create HA entity representing Bond fan. | def __init__(
self, hub: BondHub, device: BondDevice, sub_device: Optional[str] = None
):
"""Create HA entity representing Bond fan."""
super().__init__(hub, device, sub_device)
self._brightness: Optional[int] = None
self._light: Optional[int] = None | [
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BondLight.supported_features | (self) | Flag supported features. | Flag supported features. | def supported_features(self) -> Optional[int]:
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if self._device.supports_set_brightness():
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BondLight.is_on | (self) | Return if light is currently on. | Return if light is currently on. | def is_on(self) -> bool:
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BondLight.brightness | (self) | Return the brightness of this light between 1..255. | Return the brightness of this light between 1..255. | def brightness(self) -> int:
"""Return the brightness of this light between 1..255."""
brightness_value = (
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BondLight.async_turn_on | (self, **kwargs: Any) | Turn on the light. | Turn on the light. | async def async_turn_on(self, **kwargs: Any) -> None:
"""Turn on the light."""
brightness = kwargs.get(ATTR_BRIGHTNESS)
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await self._hub.bond.action(
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BondLight.async_turn_off | (self, **kwargs: Any) | Turn off the light. | Turn off the light. | async def async_turn_off(self, **kwargs: Any) -> None:
"""Turn off the light."""
await self._hub.bond.action(self._device.device_id, Action.turn_light_off()) | [
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BondFireplace.__init__ | (self, hub: BondHub, device: BondDevice) | Create HA entity representing Bond fireplace. | Create HA entity representing Bond fireplace. | def __init__(self, hub: BondHub, device: BondDevice):
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super().__init__(hub, device)
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# Bond flame level, 0-100
self._flame: Optional[int] = None | [
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BondFireplace.supported_features | (self) | Flag brightness as supported feature to represent flame level. | Flag brightness as supported feature to represent flame level. | def supported_features(self) -> Optional[int]:
"""Flag brightness as supported feature to represent flame level."""
return SUPPORT_BRIGHTNESS | [
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BondFireplace.is_on | (self) | Return True if power is on. | Return True if power is on. | def is_on(self) -> bool:
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BondFireplace.async_turn_on | (self, **kwargs: Any) | Turn the fireplace on. | Turn the fireplace on. | async def async_turn_on(self, **kwargs: Any) -> None:
"""Turn the fireplace on."""
_LOGGER.debug("Fireplace async_turn_on called with: %s", kwargs)
brightness = kwargs.get(ATTR_BRIGHTNESS)
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BondFireplace.async_turn_off | (self, **kwargs: Any) | Turn the fireplace off. | Turn the fireplace off. | async def async_turn_off(self, **kwargs: Any) -> None:
"""Turn the fireplace off."""
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BondFireplace.brightness | (self) | Return the flame of this fireplace converted to HA brightness between 0..255. | Return the flame of this fireplace converted to HA brightness between 0..255. | def brightness(self):
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BondFireplace.icon | (self) | Show fireplace icon for the entity. | Show fireplace icon for the entity. | def icon(self) -> Optional[str]:
"""Show fireplace icon for the entity."""
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prepare_inputs_for_generation | (self, input_ids: torch.LongTensor, **kwargs) |
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to prepare inputs in the
generate method.
|
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to prepare inputs in the
generate method.
| def prepare_inputs_for_generation(self, input_ids: torch.LongTensor, **kwargs) -> Dict[str, Any]:
"""
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to prepare inputs in the
generate method.
"""
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adjust_logits_during_generation | (self, logits: torch.FloatTensor, **kwargs) |
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to adjust the logits in
the generate method.
|
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to adjust the logits in
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| def adjust_logits_during_generation(self, logits: torch.FloatTensor, **kwargs) -> torch.FloatTensor:
"""
Implement in subclasses of :class:`~transformers.PreTrainedModel` for custom behavior to adjust the logits in
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"""
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_get_logits_warper | (
self, top_k: int = None, top_p: float = None, temperature: float = None, num_beams: int = None
) |
This class returns a :obj:`~transformers.LogitsProcessorList` list object that contains all relevant
:obj:`~transformers.LogitsWarper` instances used for multinomial sampling.
|
This class returns a :obj:`~transformers.LogitsProcessorList` list object that contains all relevant
:obj:`~transformers.LogitsWarper` instances used for multinomial sampling.
| def _get_logits_warper(
self, top_k: int = None, top_p: float = None, temperature: float = None, num_beams: int = None
) -> LogitsProcessorList:
"""
This class returns a :obj:`~transformers.LogitsProcessorList` list object that contains all relevant
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_get_logits_processor | (
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repetition_penalty: float,
no_repeat_ngram_size: int,
encoder_no_repeat_ngram_size: int,
encoder_input_ids: torch.LongTensor,
bad_words_ids: List[List[int]],
min_length: int,
max_length: int,
eos_token_id: int,
forced_bos_token_id: ... |
This class returns a :obj:`~transformers.LogitsProcessorList` list object that contains all relevant
:obj:`~transformers.LogitsProcessor` instances used to modify the scores of the language model head.
|
This class returns a :obj:`~transformers.LogitsProcessorList` list object that contains all relevant
:obj:`~transformers.LogitsProcessor` instances used to modify the scores of the language model head.
| def _get_logits_processor(
self,
repetition_penalty: float,
no_repeat_ngram_size: int,
encoder_no_repeat_ngram_size: int,
encoder_input_ids: torch.LongTensor,
bad_words_ids: List[List[int]],
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max_length: int,
eos_token_id: int,
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generate | (
self,
input_ids: Optional[torch.LongTensor] = None,
max_length: Optional[int] = None,
min_length: Optional[int] = None,
do_sample: Optional[bool] = None,
early_stopping: Optional[bool] = None,
num_beams: Optional[int] = None,
temperature: Optional[float]... | r"""
Generates sequences for models with a language modeling head. The method currently supports greedy decoding,
multinomial sampling, beam-search decoding, and beam-search multinomial sampling.
Apart from :obj:`input_ids` and :obj:`attention_mask`, all the arguments below will default to the ... | r"""
Generates sequences for models with a language modeling head. The method currently supports greedy decoding,
multinomial sampling, beam-search decoding, and beam-search multinomial sampling. | def generate(
self,
input_ids: Optional[torch.LongTensor] = None,
max_length: Optional[int] = None,
min_length: Optional[int] = None,
do_sample: Optional[bool] = None,
early_stopping: Optional[bool] = None,
num_beams: Optional[int] = None,
temperature: Opt... | [
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greedy_search | (
self,
input_ids: torch.LongTensor,
logits_processor: Optional[LogitsProcessorList] = None,
stopping_criteria: Optional[StoppingCriteriaList] = None,
max_length: Optional[int] = None,
pad_token_id: Optional[int] = None,
eos_token_id: Optional[int] = None,
... | r"""
Generates sequences for models with a language modeling head using greedy decoding.
Parameters:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`):
The sequence used as a prompt for the generation. If :obj:`None` the method ... | r"""
Generates sequences for models with a language modeling head using greedy decoding. | def greedy_search(
self,
input_ids: torch.LongTensor,
logits_processor: Optional[LogitsProcessorList] = None,
stopping_criteria: Optional[StoppingCriteriaList] = None,
max_length: Optional[int] = None,
pad_token_id: Optional[int] = None,
eos_token_id: Optional[int... | [
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sample | (
self,
input_ids: torch.LongTensor,
logits_processor: Optional[LogitsProcessorList] = None,
stopping_criteria: Optional[StoppingCriteriaList] = None,
logits_warper: Optional[LogitsProcessorList] = None,
max_length: Optional[int] = None,
pad_token_id: Optional[int... | r"""
Generates sequences for models with a language modeling head using multinomial sampling.
Parameters:
input_ids (:obj:`torch.LongTensor` of shape :obj:`(batch_size, sequence_length)`, `optional`):
The sequence used as a prompt for the generation. If :obj:`None` the meth... | r"""
Generates sequences for models with a language modeling head using multinomial sampling. | def sample(
self,
input_ids: torch.LongTensor,
logits_processor: Optional[LogitsProcessorList] = None,
stopping_criteria: Optional[StoppingCriteriaList] = None,
logits_warper: Optional[LogitsProcessorList] = None,
max_length: Optional[int] = None,
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async_attach_trigger | (hass, config, action, automation_info) | Listen for events based on configuration. | Listen for events based on configuration. | async def async_attach_trigger(hass, config, action, automation_info):
"""Listen for events based on configuration."""
event = config.get(CONF_EVENT)
offset = config.get(CONF_OFFSET)
description = event
if offset:
description = f"{description} with offset"
job = HassJob(action)
@cal... | [
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_async_reproduce_state | (
hass: HomeAssistantType,
state: State,
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) | Reproduce a single state. | Reproduce a single state. | async def _async_reproduce_state(
hass: HomeAssistantType,
state: State,
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) -> None:
"""Reproduce a single state."""
cur_state = hass.states.get(state.entity_id)
if cur_state is None:
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async_reproduce_states | (
hass: HomeAssistantType,
states: Iterable[State],
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) | Reproduce Water heater states. | Reproduce Water heater states. | async def async_reproduce_states(
hass: HomeAssistantType,
states: Iterable[State],
*,
context: Optional[Context] = None,
reproduce_options: Optional[Dict[str, Any]] = None,
) -> None:
"""Reproduce Water heater states."""
await asyncio.gather(
*(
_async_reproduce_state(
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config_entry_fixture | () | Create a mock config entry. | Create a mock config entry. | def config_entry_fixture():
"""Create a mock config entry."""
return MockConfigEntry(domain=DOMAIN, title="Sentry") | [
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config_fixture | () | Create hass config fixture. | Create hass config fixture. | def config_fixture():
"""Create hass config fixture."""
return {DOMAIN: {"dsn": "http://public@sentry.local/1"}} | [
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get_service | (hass, config, discovery_info=None) | Get the Hangouts notification service. | Get the Hangouts notification service. | def get_service(hass, config, discovery_info=None):
"""Get the Hangouts notification service."""
return HangoutsNotificationService(config.get(CONF_DEFAULT_CONVERSATIONS)) | [
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HangoutsNotificationService.__init__ | (self, default_conversations) | Set up the notification service. | Set up the notification service. | def __init__(self, default_conversations):
"""Set up the notification service."""
self._default_conversations = default_conversations | [
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HangoutsNotificationService.send_message | (self, message="", **kwargs) | Send the message to the Google Hangouts server. | Send the message to the Google Hangouts server. | def send_message(self, message="", **kwargs):
"""Send the message to the Google Hangouts server."""
target_conversations = None
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devices_from_config | (domain_config) | Parse configuration and add Rflink switch devices. | Parse configuration and add Rflink switch devices. | def devices_from_config(domain_config):
"""Parse configuration and add Rflink switch devices."""
devices = []
for device_id, config in domain_config[CONF_DEVICES].items():
device_config = dict(domain_config[CONF_DEVICE_DEFAULTS], **config)
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async_setup_platform | (hass, config, async_add_entities, discovery_info=None) | Set up the Rflink platform. | Set up the Rflink platform. | async def async_setup_platform(hass, config, async_add_entities, discovery_info=None):
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asana_tasks | () | Show all unassigned and user-assigned tasks. | Show all unassigned and user-assigned tasks. | def asana_tasks():
"""Show all unassigned and user-assigned tasks."""
color_dict = projects[['name', 'hex_color']]\
.set_index('name')['hex_color'].to_dict()
_logger.info("color_dict: %s", color_dict)
email = request.args.get('email', '')
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setup | (hass, config) | Set up Modbus component. | Set up Modbus component. | def setup(hass, config):
"""Set up Modbus component."""
hass.data[DOMAIN] = hub_collect = {}
for conf_hub in config[DOMAIN]:
hub_collect[conf_hub[CONF_NAME]] = ModbusHub(conf_hub)
# load platforms
for component, conf_key in (
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... | [
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ModbusHub.__init__ | (self, client_config) | Initialize the Modbus hub. | Initialize the Modbus hub. | def __init__(self, client_config):
"""Initialize the Modbus hub."""
# generic configuration
self._client = None
self._lock = threading.Lock()
self._config_name = client_config[CONF_NAME]
self._config_type = client_config[CONF_TYPE]
self._config_port = client_conf... | [
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ModbusHub.name | (self) | Return the name of this hub. | Return the name of this hub. | def name(self):
"""Return the name of this hub."""
return self._config_name | [
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ModbusHub.setup | (self) | Set up pymodbus client. | Set up pymodbus client. | def setup(self):
"""Set up pymodbus client."""
if self._config_type == "serial":
self._client = ModbusSerialClient(
method=self._config_method,
port=self._config_port,
baudrate=self._config_baudrate,
stopbits=self._config_stopbi... | [
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ModbusHub.close | (self) | Disconnect client. | Disconnect client. | def close(self):
"""Disconnect client."""
with self._lock:
self._client.close() | [
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ModbusHub.connect | (self) | Connect client. | Connect client. | def connect(self):
"""Connect client."""
with self._lock:
self._client.connect() | [
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ModbusHub.read_coils | (self, unit, address, count) | Read coils. | Read coils. | def read_coils(self, unit, address, count):
"""Read coils."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
return self._client.read_coils(address, count, **kwargs) | [
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ModbusHub.read_discrete_inputs | (self, unit, address, count) | Read discrete inputs. | Read discrete inputs. | def read_discrete_inputs(self, unit, address, count):
"""Read discrete inputs."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
return self._client.read_discrete_inputs(address, count, **kwargs) | [
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ModbusHub.read_input_registers | (self, unit, address, count) | Read input registers. | Read input registers. | def read_input_registers(self, unit, address, count):
"""Read input registers."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
return self._client.read_input_registers(address, count, **kwargs) | [
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ModbusHub.read_holding_registers | (self, unit, address, count) | Read holding registers. | Read holding registers. | def read_holding_registers(self, unit, address, count):
"""Read holding registers."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
return self._client.read_holding_registers(address, count, **kwargs) | [
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ModbusHub.write_coil | (self, unit, address, value) | Write coil. | Write coil. | def write_coil(self, unit, address, value):
"""Write coil."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
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ModbusHub.write_register | (self, unit, address, value) | Write register. | Write register. | def write_register(self, unit, address, value):
"""Write register."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
self._client.write_register(address, value, **kwargs) | [
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"write_regist... | [
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ModbusHub.write_registers | (self, unit, address, values) | Write registers. | Write registers. | def write_registers(self, unit, address, values):
"""Write registers."""
with self._lock:
kwargs = {"unit": unit} if unit else {}
self._client.write_registers(address, values, **kwargs) | [
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"write_regi... | [
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