mirror of
https://github.com/basnijholt/adaptive-lighting.git
synced 2026-09-11 22:34:04 +02:00
19fcb1d6b9* Automatically sync more data * Automatically generate apply table * Generate manual control * Add manual control docs * Update README.md * Move docs functions to separate file * Update code * simple * no path * link paths * Fix link * missed * cd core * Update README.md * Allow alternative docs * update readme * More special * Fx * Update README.md * Remove common descriptions * Update README.md * Update README.md * Rephrase * Update README.md --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
116 lines
3.3 KiB
Python
116 lines
3.3 KiB
Python
from typing import Any
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from homeassistant.helpers import selector
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import homeassistant.helpers.config_validation as cv
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import pandas as pd
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import voluptuous as vol
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from .const import (
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DOCS,
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DOCS_APPLY,
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DOCS_MANUAL_CONTROL,
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SET_MANUAL_CONTROL_SCHEMA,
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VALIDATION_TUPLES,
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apply_service_schema,
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)
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def _format_voluptuous_instance(instance):
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coerce_type = None
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min_val = None
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max_val = None
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for validator in instance.validators:
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if isinstance(validator, vol.Coerce):
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coerce_type = validator.type.__name__
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elif isinstance(validator, (vol.Clamp, vol.Range)):
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min_val = validator.min
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max_val = validator.max
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if min_val is not None and max_val is not None:
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return f"`{coerce_type}` {min_val}-{max_val}"
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elif min_val is not None:
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return f"`{coerce_type} > {min_val}`"
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elif max_val is not None:
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return f"`{coerce_type} < {max_val}`"
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else:
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return f"`{coerce_type}`"
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def _type_to_str(type_: Any) -> str:
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"""Convert a (voluptuous) type to a string."""
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if type_ == cv.entity_ids:
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return "list of `entity_id`s"
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elif type_ in (bool, int, float, str):
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return f"`{type_.__name__}`"
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elif type_ == cv.boolean:
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return "bool"
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elif isinstance(type_, vol.All):
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return _format_voluptuous_instance(type_)
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elif isinstance(type_, vol.In):
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return f"one of `{type_.container}`"
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elif isinstance(type_, selector.SelectSelector):
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return f"one of `{type_.config['options']}`"
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elif isinstance(type_, selector.ColorRGBSelector):
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return "RGB color"
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else:
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raise ValueError(f"Unknown type: {type_}")
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def generate_config_markdown_table():
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import pandas as pd
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rows = []
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for k, default, type_ in VALIDATION_TUPLES:
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description = DOCS[k]
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row = {
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"Variable name": f"`{k}`",
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"Description": description,
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"Default": f"`{default}`",
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"Type": _type_to_str(type_),
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}
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rows.append(row)
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df = pd.DataFrame(rows)
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return df.to_markdown(index=False)
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def _schema_to_dict(schema: vol.Schema) -> dict[str, tuple[Any, Any]]:
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result = {}
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for key, value in schema.schema.items():
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if isinstance(key, vol.Optional):
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default_value = key.default
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result[key.schema] = (default_value, value)
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return result
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def _generate_service_markdown_table(
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schema: dict[str, tuple[Any, Any]], alternative_docs: dict[str, str] = None
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):
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schema = _schema_to_dict(schema)
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rows = []
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for k, (default, type_) in schema.items():
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if alternative_docs is not None and k in alternative_docs:
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description = alternative_docs[k]
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else:
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description = DOCS[k]
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row = {
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"Service data attribute": f"`{k}`",
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"Description": description,
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"Required": "✅" if default == vol.UNDEFINED else "❌",
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"Type": _type_to_str(type_),
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}
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rows.append(row)
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df = pd.DataFrame(rows)
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return df.to_markdown(index=False)
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def generate_apply_markdown_table():
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return _generate_service_markdown_table(apply_service_schema(), DOCS_APPLY)
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def generate_set_manual_control_markdown_table():
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return _generate_service_markdown_table(
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SET_MANUAL_CONTROL_SCHEMA, DOCS_MANUAL_CONTROL
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)
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