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6616d68d42
Starts structuring the documentation library usage into Tutorials, Guides, Explanations and Reference. Continues migrating new docs from rst to markdown. Extends the test framework discovery mocks to allow easy writing and testing of code examples.
203 lines
7.2 KiB
Python
203 lines
7.2 KiB
Python
"""Generic interface for defining device features."""
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from __future__ import annotations
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import logging
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from dataclasses import dataclass
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from enum import Enum, auto
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from typing import TYPE_CHECKING, Any, Callable
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if TYPE_CHECKING:
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from .device import Device
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_LOGGER = logging.getLogger(__name__)
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@dataclass
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class Feature:
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"""Feature defines a generic interface for device features."""
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class Type(Enum):
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"""Type to help decide how to present the feature."""
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#: Sensor is an informative read-only value
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Sensor = auto()
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#: BinarySensor is a read-only boolean
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BinarySensor = auto()
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#: Switch is a boolean setting
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Switch = auto()
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#: Action triggers some action on device
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Action = auto()
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#: Number defines a numeric setting
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#: See :attr:`range_getter`, :attr:`Feature.minimum_value`,
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#: and :attr:`maximum_value`
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Number = auto()
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#: Choice defines a setting with pre-defined values
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Choice = auto()
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Unknown = -1
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# TODO: unsure if this is a great idea..
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Sensor = Type.Sensor
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BinarySensor = Type.BinarySensor
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Switch = Type.Switch
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Action = Type.Action
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Number = Type.Number
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Choice = Type.Choice
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class Category(Enum):
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"""Category hint to allow feature grouping."""
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#: Primary features control the device state directly.
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#: Examples include turning the device on/off, or adjusting its brightness.
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Primary = auto()
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#: Config features change device behavior without immediate state changes.
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Config = auto()
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#: Informative/sensor features deliver some potentially interesting information.
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Info = auto()
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#: Debug features deliver more verbose information then informative features.
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#: You may want to hide these per default to avoid cluttering your UI.
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Debug = auto()
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#: The default category if none is specified.
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Unset = -1
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#: Device instance required for getting and setting values
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device: Device
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#: Identifier
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id: str
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#: User-friendly short description
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name: str
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#: Name of the property that allows accessing the value
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attribute_getter: str | Callable | None = None
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#: Name of the method that allows changing the value
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attribute_setter: str | None = None
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#: Container storing the data, this overrides 'device' for getters
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container: Any = None
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#: Icon suggestion
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icon: str | None = None
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#: Unit, if applicable
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unit: str | None = None
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#: Category hint for downstreams
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category: Feature.Category = Category.Unset
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#: Type of the feature
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type: Feature.Type = Type.Sensor
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# Display hints offer a way suggest how the value should be shown to users
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#: Hint to help rounding the sensor values to given after-comma digits
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precision_hint: int | None = None
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# Number-specific attributes
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#: Minimum value
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minimum_value: int = 0
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#: Maximum value
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maximum_value: int = 2**16 # Arbitrary max
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#: Attribute containing the name of the range getter property.
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#: If set, this property will be used to set *minimum_value* and *maximum_value*.
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range_getter: str | None = None
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# Choice-specific attributes
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#: List of choices as enum
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choices: list[str] | None = None
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#: Attribute name of the choices getter property.
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#: If set, this property will be used to set *choices*.
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choices_getter: str | None = None
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def __post_init__(self):
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"""Handle late-binding of members."""
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# Populate minimum & maximum values, if range_getter is given
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container = self.container if self.container is not None else self.device
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if self.range_getter is not None:
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self.minimum_value, self.maximum_value = getattr(
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container, self.range_getter
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)
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# Populate choices, if choices_getter is given
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if self.choices_getter is not None:
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self.choices = getattr(container, self.choices_getter)
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# Set the category, if unset
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if self.category is Feature.Category.Unset:
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if self.attribute_setter:
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self.category = Feature.Category.Config
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else:
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self.category = Feature.Category.Info
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if self.category == Feature.Category.Config and self.type in [
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Feature.Type.Sensor,
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Feature.Type.BinarySensor,
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]:
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raise ValueError(
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f"Invalid type for configurable feature: {self.name} ({self.id}):"
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f" {self.type}"
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)
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@property
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def value(self):
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"""Return the current value."""
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if self.type == Feature.Type.Action:
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return "<Action>"
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if self.attribute_getter is None:
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raise ValueError("Not an action and no attribute_getter set")
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container = self.container if self.container is not None else self.device
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if isinstance(self.attribute_getter, Callable):
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return self.attribute_getter(container)
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return getattr(container, self.attribute_getter)
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async def set_value(self, value):
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"""Set the value."""
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if self.attribute_setter is None:
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raise ValueError("Tried to set read-only feature.")
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if self.type == Feature.Type.Number: # noqa: SIM102
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if value < self.minimum_value or value > self.maximum_value:
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raise ValueError(
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f"Value {value} out of range "
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f"[{self.minimum_value}, {self.maximum_value}]"
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)
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elif self.type == Feature.Type.Choice: # noqa: SIM102
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if value not in self.choices:
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raise ValueError(
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f"Unexpected value for {self.name}: {value}"
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f" - allowed: {self.choices}"
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)
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container = self.container if self.container is not None else self.device
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if self.type == Feature.Type.Action:
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return await getattr(container, self.attribute_setter)()
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return await getattr(container, self.attribute_setter)(value)
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def __repr__(self):
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try:
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value = self.value
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choices = self.choices
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except Exception as ex:
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return f"Unable to read value ({self.id}): {ex}"
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if self.type == Feature.Type.Choice:
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if not isinstance(choices, list) or value not in choices:
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_LOGGER.warning(
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"Invalid value for for choice %s (%s): %s not in %s",
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self.name,
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self.id,
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value,
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choices,
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)
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return (
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f"{self.name} ({self.id}): invalid value '{value}' not in {choices}"
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)
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value = " ".join(
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[f"*{choice}*" if choice == value else choice for choice in choices]
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)
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if self.precision_hint is not None and value is not None:
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value = round(self.value, self.precision_hint)
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s = f"{self.name} ({self.id}): {value}"
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if self.unit is not None:
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s += f" {self.unit}"
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if self.type == Feature.Type.Number:
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s += f" (range: {self.minimum_value}-{self.maximum_value})"
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return s
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