python-kasa/kasa/feature.py
Teemu R b860c32d5f
Implement feature categories (#846)
Initial implementation for feature categories to help downstreams and
our cli tool to categorize the data for more user-friendly manner. As
more and more information is being exposed through the generic features
interface, it is necessary to give some hints to downstreams about how
might want to present the information to users.

This is not a 1:1 mapping to the homeassistant's mental model, and it
will be necessary to fine-tune homeassistant-specific parameters by
other means to polish the presentation.
2024-04-23 19:20:12 +02:00

126 lines
4.3 KiB
Python

"""Generic interface for defining device features."""
from __future__ import annotations
from dataclasses import dataclass
from enum import Enum, auto
from typing import TYPE_CHECKING, Any, Callable
if TYPE_CHECKING:
from .device import Device
# TODO: This is only useful for Feature, so maybe move to Feature.Type?
class FeatureType(Enum):
"""Type to help decide how to present the feature."""
Sensor = auto()
BinarySensor = auto()
Switch = auto()
Button = auto()
Number = auto()
@dataclass
class Feature:
"""Feature defines a generic interface for device features."""
class Category(Enum):
"""Category hint for downstreams."""
#: Primary features control the device state directly.
#: Examples including turning the device on, or adjust its brightness.
Primary = auto()
#: Config features change device behavior without immediate state changes.
Config = auto()
#: Informative/sensor features deliver some potentially interesting information.
Info = auto()
#: Debug features deliver more verbose information then informative features.
#: You may want to hide these per default to avoid cluttering your UI.
Debug = auto()
#: The default category if none is specified.
Unset = -1
#: Device instance required for getting and setting values
device: Device
#: User-friendly short description
name: str
#: Name of the property that allows accessing the value
attribute_getter: str | Callable
#: Name of the method that allows changing the value
attribute_setter: str | None = None
#: Container storing the data, this overrides 'device' for getters
container: Any = None
#: Icon suggestion
icon: str | None = None
#: Unit, if applicable
unit: str | None = None
#: Category hint for downstreams
category: Feature.Category = Category.Unset
#: Type of the feature
type: FeatureType = FeatureType.Sensor
# Number-specific attributes
#: Minimum value
minimum_value: int = 0
#: Maximum value
maximum_value: int = 2**16 # Arbitrary max
#: Attribute containing the name of the range getter property.
#: If set, this property will be used to set *minimum_value* and *maximum_value*.
range_getter: str | None = None
#: Identifier
id: str | None = None
def __post_init__(self):
"""Handle late-binding of members."""
# Set id, if unset
if self.id is None:
self.id = self.name.lower().replace(" ", "_")
# Populate minimum & maximum values, if range_getter is given
container = self.container if self.container is not None else self.device
if self.range_getter is not None:
self.minimum_value, self.maximum_value = getattr(
container, self.range_getter
)
# Set the category, if unset
if self.category is Feature.Category.Unset:
if self.attribute_setter:
self.category = Feature.Category.Config
else:
self.category = Feature.Category.Info
@property
def value(self):
"""Return the current value."""
container = self.container if self.container is not None else self.device
if isinstance(self.attribute_getter, Callable):
return self.attribute_getter(container)
return getattr(container, self.attribute_getter)
async def set_value(self, value):
"""Set the value."""
if self.attribute_setter is None:
raise ValueError("Tried to set read-only feature.")
if self.type == FeatureType.Number: # noqa: SIM102
if value < self.minimum_value or value > self.maximum_value:
raise ValueError(
f"Value {value} out of range "
f"[{self.minimum_value}, {self.maximum_value}]"
)
container = self.container if self.container is not None else self.device
return await getattr(container, self.attribute_setter)(value)
def __repr__(self):
s = f"{self.name} ({self.id}): {self.value}"
if self.unit is not None:
s += f" {self.unit}"
if self.type == FeatureType.Number:
s += f" (range: {self.minimum_value}-{self.maximum_value})"
return s