Add support for calculating daily and monthly fossil energy consumption (#59588)
Erik Montnemery
GitHub
parent
49a27e12ad
commit
4a5238efa5
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@ -2,18 +2,22 @@
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from __future__ import annotations
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import asyncio
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from collections import defaultdict
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from datetime import datetime, timedelta
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import functools
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from itertools import chain
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from types import ModuleType
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from typing import Any, Awaitable, Callable, cast
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import voluptuous as vol
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from homeassistant.components import websocket_api
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from homeassistant.components import recorder, websocket_api
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from homeassistant.core import HomeAssistant, callback
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from homeassistant.helpers.integration_platform import (
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async_process_integration_platforms,
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)
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from homeassistant.helpers.singleton import singleton
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from homeassistant.util import dt as dt_util
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from .const import DOMAIN
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from .data import (
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@ -44,6 +48,7 @@ def async_setup(hass: HomeAssistant) -> None:
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websocket_api.async_register_command(hass, ws_info)
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websocket_api.async_register_command(hass, ws_validate)
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websocket_api.async_register_command(hass, ws_solar_forecast)
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websocket_api.async_register_command(hass, ws_get_fossil_energy_consumption)
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@singleton("energy_platforms")
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@ -218,3 +223,143 @@ async def ws_solar_forecast(
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forecasts[config_entry_id] = forecast
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connection.send_result(msg["id"], forecasts)
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@websocket_api.websocket_command(
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{
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vol.Required("type"): "energy/fossil_energy_consumption",
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vol.Required("start_time"): str,
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vol.Required("end_time"): str,
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vol.Required("energy_statistic_ids"): [str],
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vol.Required("co2_statistic_id"): str,
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vol.Required("period"): vol.Any("5minute", "hour", "day", "month"),
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}
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)
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@websocket_api.async_response
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async def ws_get_fossil_energy_consumption(
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hass: HomeAssistant, connection: websocket_api.ActiveConnection, msg: dict
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) -> None:
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"""Calculate amount of fossil based energy."""
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start_time_str = msg["start_time"]
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end_time_str = msg["end_time"]
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if start_time := dt_util.parse_datetime(start_time_str):
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start_time = dt_util.as_utc(start_time)
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else:
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connection.send_error(msg["id"], "invalid_start_time", "Invalid start_time")
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return
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if end_time := dt_util.parse_datetime(end_time_str):
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end_time = dt_util.as_utc(end_time)
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else:
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connection.send_error(msg["id"], "invalid_end_time", "Invalid end_time")
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return
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statistic_ids = list(msg["energy_statistic_ids"])
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statistic_ids.append(msg["co2_statistic_id"])
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# Fetch energy + CO2 statistics
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statistics = await hass.async_add_executor_job(
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recorder.statistics.statistics_during_period,
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hass,
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start_time,
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end_time,
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statistic_ids,
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"hour",
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True,
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)
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def _combine_sum_statistics(
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stats: dict[str, list[dict[str, Any]]], statistic_ids: list[str]
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) -> dict[datetime, float]:
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"""Combine multiple statistics, returns a dict indexed by start time."""
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result: defaultdict[datetime, float] = defaultdict(float)
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for statistics_id, stat in stats.items():
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if statistics_id not in statistic_ids:
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continue
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for period in stat:
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if period["sum"] is None:
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continue
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result[period["start"]] += period["sum"]
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return {key: result[key] for key in sorted(result)}
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def _calculate_deltas(sums: dict[datetime, float]) -> dict[datetime, float]:
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prev: float | None = None
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result: dict[datetime, float] = {}
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for period, sum_ in sums.items():
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if prev is not None:
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result[period] = sum_ - prev
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prev = sum_
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return result
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def _reduce_deltas(
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stat_list: list[dict[str, Any]],
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same_period: Callable[[datetime, datetime], bool],
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period_start_end: Callable[[datetime], tuple[datetime, datetime]],
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period: timedelta,
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) -> list[dict[str, Any]]:
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"""Reduce hourly deltas to daily or monthly deltas."""
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result: list[dict[str, Any]] = []
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deltas: list[float] = []
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prev_stat: dict[str, Any] = stat_list[0]
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# Loop over the hourly deltas + a fake entry to end the period
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for statistic in chain(
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stat_list, ({"start": stat_list[-1]["start"] + period},)
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):
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if not same_period(prev_stat["start"], statistic["start"]):
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start, _ = period_start_end(prev_stat["start"])
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# The previous statistic was the last entry of the period
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result.append(
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{
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"start": start.isoformat(),
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"delta": sum(deltas),
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}
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)
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deltas = []
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if statistic.get("delta") is not None:
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deltas.append(statistic["delta"])
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prev_stat = statistic
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return result
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merged_energy_statistics = _combine_sum_statistics(
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statistics, msg["energy_statistic_ids"]
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)
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energy_deltas = _calculate_deltas(merged_energy_statistics)
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indexed_co2_statistics = {
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period["start"]: period["mean"]
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for period in statistics.get(msg["co2_statistic_id"], {})
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}
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# Calculate amount of fossil based energy, assume 100% fossil if missing
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fossil_energy = [
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{"start": start, "delta": delta * indexed_co2_statistics.get(start, 100) / 100}
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for start, delta in energy_deltas.items()
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]
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if msg["period"] == "hour":
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reduced_fossil_energy = [
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{"start": period["start"].isoformat(), "delta": period["delta"]}
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for period in fossil_energy
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]
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elif msg["period"] == "day":
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reduced_fossil_energy = _reduce_deltas(
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fossil_energy,
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recorder.statistics.same_day,
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recorder.statistics.day_start_end,
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timedelta(days=1),
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)
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else:
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reduced_fossil_energy = _reduce_deltas(
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fossil_energy,
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recorder.statistics.same_month,
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recorder.statistics.month_start_end,
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timedelta(days=1),
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)
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result = {period["start"]: period["delta"] for period in reduced_fossil_energy}
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connection.send_result(msg["id"], result)
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@ -697,8 +697,8 @@ def _reduce_statistics(
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"mean": mean(mean_values) if mean_values else None,
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"min": min(min_values) if min_values else None,
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"max": max(max_values) if max_values else None,
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"last_reset": prev_stat["last_reset"],
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"state": prev_stat["state"],
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"last_reset": prev_stat.get("last_reset"),
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"state": prev_stat.get("state"),
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"sum": prev_stat["sum"],
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}
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)
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@ -716,50 +716,54 @@ def _reduce_statistics(
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return result
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def same_day(time1: datetime, time2: datetime) -> bool:
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"""Return True if time1 and time2 are in the same date."""
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date1 = dt_util.as_local(time1).date()
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date2 = dt_util.as_local(time2).date()
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return date1 == date2
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def day_start_end(time: datetime) -> tuple[datetime, datetime]:
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"""Return the start and end of the period (day) time is within."""
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start = dt_util.as_utc(
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dt_util.as_local(time).replace(hour=0, minute=0, second=0, microsecond=0)
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)
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end = start + timedelta(days=1)
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return (start, end)
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def _reduce_statistics_per_day(
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stats: dict[str, list[dict[str, Any]]]
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) -> dict[str, list[dict[str, Any]]]:
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"""Reduce hourly statistics to daily statistics."""
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def same_period(time1: datetime, time2: datetime) -> bool:
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"""Return True if time1 and time2 are in the same date."""
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date1 = dt_util.as_local(time1).date()
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date2 = dt_util.as_local(time2).date()
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return date1 == date2
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return _reduce_statistics(stats, same_day, day_start_end, timedelta(days=1))
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def period_start_end(time: datetime) -> tuple[datetime, datetime]:
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"""Return the start and end of the period (day) time is within."""
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start = dt_util.as_utc(
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dt_util.as_local(time).replace(hour=0, minute=0, second=0, microsecond=0)
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)
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end = start + timedelta(days=1)
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return (start, end)
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return _reduce_statistics(stats, same_period, period_start_end, timedelta(days=1))
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def same_month(time1: datetime, time2: datetime) -> bool:
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"""Return True if time1 and time2 are in the same year and month."""
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date1 = dt_util.as_local(time1).date()
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date2 = dt_util.as_local(time2).date()
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return (date1.year, date1.month) == (date2.year, date2.month)
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def month_start_end(time: datetime) -> tuple[datetime, datetime]:
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"""Return the start and end of the period (month) time is within."""
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start_local = dt_util.as_local(time).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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start = dt_util.as_utc(start_local)
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end_local = (start_local + timedelta(days=31)).replace(day=1)
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end = dt_util.as_utc(end_local)
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return (start, end)
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def _reduce_statistics_per_month(
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stats: dict[str, list[dict[str, Any]]]
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stats: dict[str, list[dict[str, Any]]],
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) -> dict[str, list[dict[str, Any]]]:
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"""Reduce hourly statistics to monthly statistics."""
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def same_period(time1: datetime, time2: datetime) -> bool:
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"""Return True if time1 and time2 are in the same year and month."""
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date1 = dt_util.as_local(time1).date()
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date2 = dt_util.as_local(time2).date()
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return (date1.year, date1.month) == (date2.year, date2.month)
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def period_start_end(time: datetime) -> tuple[datetime, datetime]:
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"""Return the start and end of the period (month) time is within."""
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start_local = dt_util.as_local(time).replace(
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day=1, hour=0, minute=0, second=0, microsecond=0
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)
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start = dt_util.as_utc(start_local)
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end_local = (start_local + timedelta(days=31)).replace(day=1)
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end = dt_util.as_utc(end_local)
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return (start, end)
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return _reduce_statistics(stats, same_period, period_start_end, timedelta(days=31))
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return _reduce_statistics(stats, same_month, month_start_end, timedelta(days=31))
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def statistics_during_period(
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@ -768,6 +772,7 @@ def statistics_during_period(
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end_time: datetime | None = None,
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statistic_ids: list[str] | None = None,
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period: Literal["5minute", "day", "hour", "month"] = "hour",
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start_time_as_datetime: bool = False,
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) -> dict[str, list[dict[str, Any]]]:
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"""Return statistics during UTC period start_time - end_time for the statistic_ids.
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@ -808,7 +813,15 @@ def statistics_during_period(
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# Return statistics combined with metadata
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if period not in ("day", "month"):
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return _sorted_statistics_to_dict(
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hass, session, stats, statistic_ids, metadata, True, table, start_time
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hass,
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session,
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stats,
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statistic_ids,
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metadata,
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True,
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table,
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start_time,
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start_time_as_datetime,
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)
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result = _sorted_statistics_to_dict(
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@ -4,9 +4,17 @@ from unittest.mock import AsyncMock, Mock
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import pytest
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from homeassistant.components.energy import data, is_configured
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from homeassistant.components.recorder.statistics import async_add_external_statistics
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from homeassistant.setup import async_setup_component
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from homeassistant.util import dt as dt_util
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from tests.common import MockConfigEntry, flush_store, mock_platform
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from tests.common import (
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MockConfigEntry,
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flush_store,
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init_recorder_component,
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mock_platform,
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)
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from tests.components.recorder.common import async_wait_recording_done_without_instance
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@pytest.fixture(autouse=True)
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@ -289,3 +297,525 @@ async def test_get_solar_forecast(hass, hass_ws_client, mock_energy_platform) ->
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}
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}
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}
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@pytest.mark.freeze_time("2021-08-01 00:00:00+00:00")
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async def test_fossil_energy_consumption_no_co2(hass, hass_ws_client):
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"""Test fossil_energy_consumption when co2 data is missing."""
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now = dt_util.utcnow()
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later = dt_util.as_utc(dt_util.parse_datetime("2022-09-01 00:00:00"))
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await hass.async_add_executor_job(init_recorder_component, hass)
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await async_setup_component(hass, "history", {})
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await async_setup_component(hass, "sensor", {})
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period1 = dt_util.as_utc(dt_util.parse_datetime("2021-09-01 00:00:00"))
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period2 = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 23:00:00"))
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period2_day_start = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 00:00:00"))
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period3 = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
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period4 = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 23:00:00"))
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period4_day_start = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 00:00:00"))
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external_energy_statistics_1 = (
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{
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"start": period1,
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"last_reset": None,
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"state": 0,
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"sum": 2,
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},
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{
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"start": period2,
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"last_reset": None,
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"state": 1,
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"sum": 3,
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},
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{
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"start": period3,
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"last_reset": None,
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"state": 2,
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"sum": 5,
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},
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{
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"start": period4,
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"last_reset": None,
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"state": 3,
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"sum": 8,
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},
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)
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external_energy_metadata_1 = {
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"has_mean": False,
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"has_sum": True,
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"name": "Total imported energy",
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"source": "test",
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"statistic_id": "test:total_energy_import_tariff_1",
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"unit_of_measurement": "kWh",
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}
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external_energy_statistics_2 = (
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{
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"start": period1,
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"last_reset": None,
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"state": 0,
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"sum": 20,
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},
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{
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"start": period2,
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"last_reset": None,
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"state": 1,
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"sum": 30,
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},
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{
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"start": period3,
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"last_reset": None,
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"state": 2,
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"sum": 50,
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},
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{
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"start": period4,
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"last_reset": None,
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"state": 3,
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"sum": 80,
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},
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)
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external_energy_metadata_2 = {
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"has_mean": False,
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"has_sum": True,
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"name": "Total imported energy",
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"source": "test",
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"statistic_id": "test:total_energy_import_tariff_2",
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"unit_of_measurement": "kWh",
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}
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async_add_external_statistics(
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hass, external_energy_metadata_1, external_energy_statistics_1
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)
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async_add_external_statistics(
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hass, external_energy_metadata_2, external_energy_statistics_2
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)
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await async_wait_recording_done_without_instance(hass)
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client = await hass_ws_client()
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await client.send_json(
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{
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"id": 1,
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"type": "energy/fossil_energy_consumption",
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"start_time": now.isoformat(),
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"end_time": later.isoformat(),
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"energy_statistic_ids": [
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"test:total_energy_import_tariff_1",
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"test:total_energy_import_tariff_2",
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],
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"co2_statistic_id": "test:co2_ratio_missing",
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"period": "hour",
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}
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)
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response = await client.receive_json()
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assert response["success"]
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assert response["result"] == {
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period2.isoformat(): pytest.approx(33.0 - 22.0),
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period3.isoformat(): pytest.approx(55.0 - 33.0),
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period4.isoformat(): pytest.approx(88.0 - 55.0),
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}
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await client.send_json(
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{
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"id": 2,
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"type": "energy/fossil_energy_consumption",
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"start_time": now.isoformat(),
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"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:co2_ratio_missing",
|
||||
"period": "day",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period2_day_start.isoformat(): pytest.approx(33.0 - 22.0),
|
||||
period3.isoformat(): pytest.approx(55.0 - 33.0),
|
||||
period4_day_start.isoformat(): pytest.approx(88.0 - 55.0),
|
||||
}
|
||||
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 3,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:co2_ratio_missing",
|
||||
"period": "month",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period1.isoformat(): pytest.approx(33.0 - 22.0),
|
||||
period3.isoformat(): pytest.approx((55.0 - 33.0) + (88.0 - 55.0)),
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.freeze_time("2021-08-01 00:00:00+00:00")
|
||||
async def test_fossil_energy_consumption_hole(hass, hass_ws_client):
|
||||
"""Test fossil_energy_consumption when some data points lack sum."""
|
||||
now = dt_util.utcnow()
|
||||
later = dt_util.as_utc(dt_util.parse_datetime("2022-09-01 00:00:00"))
|
||||
|
||||
await hass.async_add_executor_job(init_recorder_component, hass)
|
||||
await async_setup_component(hass, "history", {})
|
||||
await async_setup_component(hass, "sensor", {})
|
||||
|
||||
period1 = dt_util.as_utc(dt_util.parse_datetime("2021-09-01 00:00:00"))
|
||||
period2 = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 23:00:00"))
|
||||
period3 = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
|
||||
period4 = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 23:00:00"))
|
||||
|
||||
external_energy_statistics_1 = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"state": 0,
|
||||
"sum": None,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"state": 1,
|
||||
"sum": 3,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"state": 2,
|
||||
"sum": 5,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"state": 3,
|
||||
"sum": 8,
|
||||
},
|
||||
)
|
||||
external_energy_metadata_1 = {
|
||||
"has_mean": False,
|
||||
"has_sum": True,
|
||||
"name": "Total imported energy",
|
||||
"source": "test",
|
||||
"statistic_id": "test:total_energy_import_tariff_1",
|
||||
"unit_of_measurement": "kWh",
|
||||
}
|
||||
external_energy_statistics_2 = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"state": 0,
|
||||
"sum": 20,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"state": 1,
|
||||
"sum": None,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"state": 2,
|
||||
"sum": 50,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"state": 3,
|
||||
"sum": 80,
|
||||
},
|
||||
)
|
||||
external_energy_metadata_2 = {
|
||||
"has_mean": False,
|
||||
"has_sum": True,
|
||||
"name": "Total imported energy",
|
||||
"source": "test",
|
||||
"statistic_id": "test:total_energy_import_tariff_2",
|
||||
"unit_of_measurement": "kWh",
|
||||
}
|
||||
|
||||
async_add_external_statistics(
|
||||
hass, external_energy_metadata_1, external_energy_statistics_1
|
||||
)
|
||||
async_add_external_statistics(
|
||||
hass, external_energy_metadata_2, external_energy_statistics_2
|
||||
)
|
||||
await async_wait_recording_done_without_instance(hass)
|
||||
|
||||
client = await hass_ws_client()
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 1,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:co2_ratio_missing",
|
||||
"period": "hour",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period2.isoformat(): pytest.approx(3.0 - 20.0),
|
||||
period3.isoformat(): pytest.approx(55.0 - 3.0),
|
||||
period4.isoformat(): pytest.approx(88.0 - 55.0),
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.freeze_time("2021-08-01 00:00:00+00:00")
|
||||
async def test_fossil_energy_consumption(hass, hass_ws_client):
|
||||
"""Test fossil_energy_consumption with co2 sensor data."""
|
||||
now = dt_util.utcnow()
|
||||
later = dt_util.as_utc(dt_util.parse_datetime("2022-09-01 00:00:00"))
|
||||
|
||||
await hass.async_add_executor_job(init_recorder_component, hass)
|
||||
await async_setup_component(hass, "history", {})
|
||||
await async_setup_component(hass, "sensor", {})
|
||||
|
||||
period1 = dt_util.as_utc(dt_util.parse_datetime("2021-09-01 00:00:00"))
|
||||
period2 = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 23:00:00"))
|
||||
period2_day_start = dt_util.as_utc(dt_util.parse_datetime("2021-09-30 00:00:00"))
|
||||
period3 = dt_util.as_utc(dt_util.parse_datetime("2021-10-01 00:00:00"))
|
||||
period4 = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 23:00:00"))
|
||||
period4_day_start = dt_util.as_utc(dt_util.parse_datetime("2021-10-31 00:00:00"))
|
||||
|
||||
external_energy_statistics_1 = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"state": 0,
|
||||
"sum": 2,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"state": 1,
|
||||
"sum": 3,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"state": 2,
|
||||
"sum": 4,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"state": 3,
|
||||
"sum": 5,
|
||||
},
|
||||
)
|
||||
external_energy_metadata_1 = {
|
||||
"has_mean": False,
|
||||
"has_sum": True,
|
||||
"name": "Total imported energy",
|
||||
"source": "test",
|
||||
"statistic_id": "test:total_energy_import_tariff_1",
|
||||
"unit_of_measurement": "kWh",
|
||||
}
|
||||
external_energy_statistics_2 = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"state": 0,
|
||||
"sum": 20,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"state": 1,
|
||||
"sum": 30,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"state": 2,
|
||||
"sum": 40,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"state": 3,
|
||||
"sum": 50,
|
||||
},
|
||||
)
|
||||
external_energy_metadata_2 = {
|
||||
"has_mean": False,
|
||||
"has_sum": True,
|
||||
"name": "Total imported energy",
|
||||
"source": "test",
|
||||
"statistic_id": "test:total_energy_import_tariff_2",
|
||||
"unit_of_measurement": "kWh",
|
||||
}
|
||||
external_co2_statistics = (
|
||||
{
|
||||
"start": period1,
|
||||
"last_reset": None,
|
||||
"mean": 10,
|
||||
},
|
||||
{
|
||||
"start": period2,
|
||||
"last_reset": None,
|
||||
"mean": 30,
|
||||
},
|
||||
{
|
||||
"start": period3,
|
||||
"last_reset": None,
|
||||
"mean": 60,
|
||||
},
|
||||
{
|
||||
"start": period4,
|
||||
"last_reset": None,
|
||||
"mean": 90,
|
||||
},
|
||||
)
|
||||
external_co2_metadata = {
|
||||
"has_mean": True,
|
||||
"has_sum": False,
|
||||
"name": "Fossil percentage",
|
||||
"source": "test",
|
||||
"statistic_id": "test:fossil_percentage",
|
||||
"unit_of_measurement": "%",
|
||||
}
|
||||
|
||||
async_add_external_statistics(
|
||||
hass, external_energy_metadata_1, external_energy_statistics_1
|
||||
)
|
||||
async_add_external_statistics(
|
||||
hass, external_energy_metadata_2, external_energy_statistics_2
|
||||
)
|
||||
async_add_external_statistics(hass, external_co2_metadata, external_co2_statistics)
|
||||
await async_wait_recording_done_without_instance(hass)
|
||||
|
||||
client = await hass_ws_client()
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 1,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:fossil_percentage",
|
||||
"period": "hour",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period2.isoformat(): pytest.approx((33.0 - 22.0) * 0.3),
|
||||
period3.isoformat(): pytest.approx((44.0 - 33.0) * 0.6),
|
||||
period4.isoformat(): pytest.approx((55.0 - 44.0) * 0.9),
|
||||
}
|
||||
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 2,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:fossil_percentage",
|
||||
"period": "day",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period2_day_start.isoformat(): pytest.approx((33.0 - 22.0) * 0.3),
|
||||
period3.isoformat(): pytest.approx((44.0 - 33.0) * 0.6),
|
||||
period4_day_start.isoformat(): pytest.approx((55.0 - 44.0) * 0.9),
|
||||
}
|
||||
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 3,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": later.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:fossil_percentage",
|
||||
"period": "month",
|
||||
}
|
||||
)
|
||||
response = await client.receive_json()
|
||||
assert response["success"]
|
||||
assert response["result"] == {
|
||||
period1.isoformat(): pytest.approx((33.0 - 22.0) * 0.3),
|
||||
period3.isoformat(): pytest.approx(
|
||||
((44.0 - 33.0) * 0.6) + ((55.0 - 44.0) * 0.9)
|
||||
),
|
||||
}
|
||||
|
||||
|
||||
async def test_fossil_energy_consumption_checks(hass, hass_ws_client):
|
||||
"""Test fossil_energy_consumption parameter validation."""
|
||||
client = await hass_ws_client(hass)
|
||||
now = dt_util.utcnow()
|
||||
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 1,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": "donald_duck",
|
||||
"end_time": now.isoformat(),
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:fossil_percentage",
|
||||
"period": "hour",
|
||||
}
|
||||
)
|
||||
|
||||
msg = await client.receive_json()
|
||||
|
||||
assert msg["id"] == 1
|
||||
assert not msg["success"]
|
||||
assert msg["error"] == {
|
||||
"code": "invalid_start_time",
|
||||
"message": "Invalid start_time",
|
||||
}
|
||||
|
||||
await client.send_json(
|
||||
{
|
||||
"id": 2,
|
||||
"type": "energy/fossil_energy_consumption",
|
||||
"start_time": now.isoformat(),
|
||||
"end_time": "donald_duck",
|
||||
"energy_statistic_ids": [
|
||||
"test:total_energy_import_tariff_1",
|
||||
"test:total_energy_import_tariff_2",
|
||||
],
|
||||
"co2_statistic_id": "test:fossil_percentage",
|
||||
"period": "hour",
|
||||
}
|
||||
)
|
||||
|
||||
msg = await client.receive_json()
|
||||
|
||||
assert msg["id"] == 2
|
||||
assert not msg["success"]
|
||||
assert msg["error"] == {"code": "invalid_end_time", "message": "Invalid end_time"}
|
||||
|
|
|
|||
Loading…
Reference in New Issue