"""Statistics helper for sensor."""
from __future__ import annotations

from collections import defaultdict
from collections.abc import Callable, Iterable, MutableMapping
import datetime
import itertools
import logging
import math
from typing import Any

from sqlalchemy.orm.session import Session

from homeassistant.components.recorder import (
    DOMAIN as RECORDER_DOMAIN,
    get_instance,
    history,
    statistics,
    util as recorder_util,
)
from homeassistant.components.recorder.models import (
    StatisticData,
    StatisticMetaData,
    StatisticResult,
)
from homeassistant.const import (
    ATTR_UNIT_OF_MEASUREMENT,
    REVOLUTIONS_PER_MINUTE,
    UnitOfIrradiance,
    UnitOfSoundPressure,
    UnitOfVolume,
)
from homeassistant.core import HomeAssistant, State, callback, split_entity_id
from homeassistant.exceptions import HomeAssistantError
from homeassistant.helpers.entity import entity_sources
from homeassistant.util import dt as dt_util
from homeassistant.util.enum import try_parse_enum

from .const import (
    ATTR_LAST_RESET,
    ATTR_OPTIONS,
    ATTR_STATE_CLASS,
    DOMAIN,
    SensorStateClass,
)

_LOGGER = logging.getLogger(__name__)

DEFAULT_STATISTICS = {
    SensorStateClass.MEASUREMENT: {"mean", "min", "max"},
    SensorStateClass.TOTAL: {"sum"},
    SensorStateClass.TOTAL_INCREASING: {"sum"},
}

EQUIVALENT_UNITS = {
    "BTU/(h×ft²)": UnitOfIrradiance.BTUS_PER_HOUR_SQUARE_FOOT,
    "dBa": UnitOfSoundPressure.WEIGHTED_DECIBEL_A,
    "RPM": REVOLUTIONS_PER_MINUTE,
    "ft3": UnitOfVolume.CUBIC_FEET,
    "m3": UnitOfVolume.CUBIC_METERS,
}

# Keep track of entities for which a warning about decreasing value has been logged
SEEN_DIP = "sensor_seen_total_increasing_dip"
WARN_DIP = "sensor_warn_total_increasing_dip"
# Keep track of entities for which a warning about negative value has been logged
WARN_NEGATIVE = "sensor_warn_total_increasing_negative"
# Keep track of entities for which a warning about unsupported unit has been logged
WARN_UNSUPPORTED_UNIT = "sensor_warn_unsupported_unit"
WARN_UNSTABLE_UNIT = "sensor_warn_unstable_unit"
# Link to dev statistics where issues around LTS can be fixed
LINK_DEV_STATISTICS = "https://my.home-assistant.io/redirect/developer_statistics"


def _get_sensor_states(hass: HomeAssistant) -> list[State]:
    """Get the current state of all sensors for which to compile statistics."""
    all_sensors = hass.states.all(DOMAIN)
    instance = get_instance(hass)
    return [
        state
        for state in all_sensors
        if instance.entity_filter(state.entity_id)
        and try_parse_enum(SensorStateClass, state.attributes.get(ATTR_STATE_CLASS))
    ]


def _time_weighted_average(
    fstates: list[tuple[float, State]], start: datetime.datetime, end: datetime.datetime
) -> float:
    """Calculate a time weighted average.

    The average is calculated by weighting the states by duration in seconds between
    state changes.
    Note: there's no interpolation of values between state changes.
    """
    old_fstate: float | None = None
    old_start_time: datetime.datetime | None = None
    accumulated = 0.0

    for fstate, state in fstates:
        # The recorder will give us the last known state, which may be well
        # before the requested start time for the statistics
        start_time = start if state.last_updated < start else state.last_updated
        if old_start_time is None:
            # Adjust start time, if there was no last known state
            start = start_time
        else:
            duration = start_time - old_start_time
            # Accumulate the value, weighted by duration until next state change
            assert old_fstate is not None
            accumulated += old_fstate * duration.total_seconds()

        old_fstate = fstate
        old_start_time = start_time

    if old_fstate is not None:
        # Accumulate the value, weighted by duration until end of the period
        assert old_start_time is not None
        duration = end - old_start_time
        accumulated += old_fstate * duration.total_seconds()

    period_seconds = (end - start).total_seconds()
    if period_seconds == 0:
        # If the only state changed that happened was at the exact moment
        # at the end of the period, we can't calculate a meaningful average
        # so we return 0.0 since it represents a time duration smaller than
        # we can measure. This probably means the precision of statistics
        # column schema in the database is incorrect but it is actually possible
        # to happen if the state change event fired at the exact microsecond
        return 0.0
    return accumulated / period_seconds


def _get_units(fstates: list[tuple[float, State]]) -> set[str | None]:
    """Return a set of all units."""
    return {item[1].attributes.get(ATTR_UNIT_OF_MEASUREMENT) for item in fstates}


def _equivalent_units(units: set[str | None]) -> bool:
    """Return True if the units are equivalent."""
    if len(units) == 1:
        return True
    units = {
        EQUIVALENT_UNITS[unit] if unit in EQUIVALENT_UNITS else unit for unit in units
    }
    return len(units) == 1


def _parse_float(state: str) -> float:
    """Parse a float string, throw on inf or nan."""
    fstate = float(state)
    if not math.isfinite(fstate):
        raise ValueError
    return fstate


def _float_or_none(state: str) -> float | None:
    """Return a float or None."""
    try:
        return _parse_float(state)
    except (ValueError, TypeError):
        return None


def _entity_history_to_float_and_state(
    entity_history: Iterable[State],
) -> list[tuple[float, State]]:
    """Return a list of (float, state) tuples for the given entity."""
    return [
        (fstate, state)
        for state in entity_history
        if (fstate := _float_or_none(state.state)) is not None
    ]


def _normalize_states(
    hass: HomeAssistant,
    old_metadatas: dict[str, tuple[int, StatisticMetaData]],
    fstates: list[tuple[float, State]],
    entity_id: str,
) -> tuple[str | None, list[tuple[float, State]]]:
    """Normalize units."""
    state_unit: str | None = None
    statistics_unit: str | None
    state_unit = fstates[0][1].attributes.get(ATTR_UNIT_OF_MEASUREMENT)
    old_metadata = old_metadatas[entity_id][1] if entity_id in old_metadatas else None
    if not old_metadata:
        # We've not seen this sensor before, the first valid state determines the unit
        # used for statistics
        statistics_unit = state_unit
    else:
        # We have seen this sensor before, use the unit from metadata
        statistics_unit = old_metadata["unit_of_measurement"]

    if statistics_unit not in statistics.STATISTIC_UNIT_TO_UNIT_CONVERTER:
        # The unit used by this sensor doesn't support unit conversion

        all_units = _get_units(fstates)
        if not _equivalent_units(all_units):
            if WARN_UNSTABLE_UNIT not in hass.data:
                hass.data[WARN_UNSTABLE_UNIT] = set()
            if entity_id not in hass.data[WARN_UNSTABLE_UNIT]:
                hass.data[WARN_UNSTABLE_UNIT].add(entity_id)
                extra = ""
                if old_metadata:
                    extra = (
                        " and matches the unit of already compiled statistics "
                        f"({old_metadata['unit_of_measurement']})"
                    )
                _LOGGER.warning(
                    (
                        "The unit of %s is changing, got multiple %s, generation of"
                        " long term statistics will be suppressed unless the unit is"
                        " stable%s. Go to %s to fix this"
                    ),
                    entity_id,
                    all_units,
                    extra,
                    LINK_DEV_STATISTICS,
                )
            return None, []
        state_unit = fstates[0][1].attributes.get(ATTR_UNIT_OF_MEASUREMENT)
        return state_unit, fstates

    converter = statistics.STATISTIC_UNIT_TO_UNIT_CONVERTER[statistics_unit]
    valid_fstates: list[tuple[float, State]] = []
    convert: Callable[[float], float]
    last_unit: str | None | object = object()

    for fstate, state in fstates:
        state_unit = state.attributes.get(ATTR_UNIT_OF_MEASUREMENT)
        # Exclude states with unsupported unit from statistics
        if state_unit not in converter.VALID_UNITS:
            if WARN_UNSUPPORTED_UNIT not in hass.data:
                hass.data[WARN_UNSUPPORTED_UNIT] = set()
            if entity_id not in hass.data[WARN_UNSUPPORTED_UNIT]:
                hass.data[WARN_UNSUPPORTED_UNIT].add(entity_id)
                _LOGGER.warning(
                    (
                        "The unit of %s (%s) cannot be converted to the unit of"
                        " previously compiled statistics (%s). Generation of long term"
                        " statistics will be suppressed unless the unit changes back to"
                        " %s or a compatible unit. Go to %s to fix this"
                    ),
                    entity_id,
                    state_unit,
                    statistics_unit,
                    statistics_unit,
                    LINK_DEV_STATISTICS,
                )
            continue
        if state_unit != last_unit:
            # The unit of measurement has changed since the last state change
            # recreate the converter factory
            convert = converter.converter_factory(state_unit, statistics_unit)
            last_unit = state_unit

        valid_fstates.append((convert(fstate), state))

    return statistics_unit, valid_fstates


def _suggest_report_issue(hass: HomeAssistant, entity_id: str) -> str:
    """Suggest to report an issue."""
    domain = entity_sources(hass).get(entity_id, {}).get("domain")
    custom_component = entity_sources(hass).get(entity_id, {}).get("custom_component")
    report_issue = ""
    if custom_component:
        report_issue = "report it to the custom integration author."
    else:
        report_issue = (
            "create a bug report at "
            "https://github.com/home-assistant/core/issues?q=is%3Aopen+is%3Aissue"
        )
        if domain:
            report_issue += f"+label%3A%22integration%3A+{domain}%22"

    return report_issue


def warn_dip(
    hass: HomeAssistant, entity_id: str, state: State, previous_fstate: float
) -> None:
    """Log a warning once if a sensor with state_class_total has a decreasing value.

    The log will be suppressed until two dips have been seen to prevent warning due to
    rounding issues with databases storing the state as a single precision float, which
    was fixed in recorder DB version 20.
    """
    if SEEN_DIP not in hass.data:
        hass.data[SEEN_DIP] = set()
    if entity_id not in hass.data[SEEN_DIP]:
        hass.data[SEEN_DIP].add(entity_id)
        return
    if WARN_DIP not in hass.data:
        hass.data[WARN_DIP] = set()
    if entity_id not in hass.data[WARN_DIP]:
        hass.data[WARN_DIP].add(entity_id)
        domain = entity_sources(hass).get(entity_id, {}).get("domain")
        if domain in ["energy", "growatt_server", "solaredge"]:
            return
        _LOGGER.warning(
            (
                "Entity %s %shas state class total_increasing, but its state is not"
                " strictly increasing. Triggered by state %s (%s) with last_updated set"
                " to %s. Please %s"
            ),
            entity_id,
            f"from integration {domain} " if domain else "",
            state.state,
            previous_fstate,
            state.last_updated.isoformat(),
            _suggest_report_issue(hass, entity_id),
        )


def warn_negative(hass: HomeAssistant, entity_id: str, state: State) -> None:
    """Log a warning once if a sensor with state_class_total has a negative value."""
    if WARN_NEGATIVE not in hass.data:
        hass.data[WARN_NEGATIVE] = set()
    if entity_id not in hass.data[WARN_NEGATIVE]:
        hass.data[WARN_NEGATIVE].add(entity_id)
        domain = entity_sources(hass).get(entity_id, {}).get("domain")
        _LOGGER.warning(
            (
                "Entity %s %shas state class total_increasing, but its state is "
                "negative. Triggered by state %s with last_updated set to %s. Please %s"
            ),
            entity_id,
            f"from integration {domain} " if domain else "",
            state.state,
            state.last_updated.isoformat(),
            _suggest_report_issue(hass, entity_id),
        )


def reset_detected(
    hass: HomeAssistant,
    entity_id: str,
    fstate: float,
    previous_fstate: float | None,
    state: State,
) -> bool:
    """Test if a total_increasing sensor has been reset."""
    if previous_fstate is None:
        return False

    if 0.9 * previous_fstate <= fstate < previous_fstate:
        warn_dip(hass, entity_id, state, previous_fstate)

    if fstate < 0:
        warn_negative(hass, entity_id, state)
        raise HomeAssistantError

    return fstate < 0.9 * previous_fstate


def _wanted_statistics(sensor_states: list[State]) -> dict[str, set[str]]:
    """Prepare a dict with wanted statistics for entities."""
    return {
        state.entity_id: DEFAULT_STATISTICS[state.attributes[ATTR_STATE_CLASS]]
        for state in sensor_states
    }


def _last_reset_as_utc_isoformat(last_reset_s: Any, entity_id: str) -> str | None:
    """Parse last_reset and convert it to UTC."""
    if last_reset_s is None:
        return None
    if isinstance(last_reset_s, str):
        last_reset = dt_util.parse_datetime(last_reset_s)
    else:
        last_reset = None
    if last_reset is None:
        _LOGGER.warning(
            "Ignoring invalid last reset '%s' for %s", last_reset_s, entity_id
        )
        return None
    return dt_util.as_utc(last_reset).isoformat()


def _timestamp_to_isoformat_or_none(timestamp: float | None) -> str | None:
    """Convert a timestamp to ISO format or return None."""
    if timestamp is None:
        return None
    return dt_util.utc_from_timestamp(timestamp).isoformat()


def compile_statistics(
    hass: HomeAssistant, start: datetime.datetime, end: datetime.datetime
) -> statistics.PlatformCompiledStatistics:
    """Compile statistics for all entities during start-end.

    Note: This will query the database and must not be run in the event loop
    """
    # There is already an active session when this code is called since
    # it is called from the recorder statistics. We need to make sure
    # this session never gets committed since it would be out of sync
    # with the recorder statistics session so we mark it as read only.
    #
    # If we ever need to write to the database from this function we
    # will need to refactor the recorder statistics to use a single
    # session.
    with recorder_util.session_scope(hass=hass, read_only=True) as session:
        compiled = _compile_statistics(hass, session, start, end)
    return compiled


def _compile_statistics(  # noqa: C901
    hass: HomeAssistant,
    session: Session,
    start: datetime.datetime,
    end: datetime.datetime,
) -> statistics.PlatformCompiledStatistics:
    """Compile statistics for all entities during start-end."""
    result: list[StatisticResult] = []

    sensor_states = _get_sensor_states(hass)
    wanted_statistics = _wanted_statistics(sensor_states)
    # Get history between start and end
    entities_full_history = [
        i.entity_id for i in sensor_states if "sum" in wanted_statistics[i.entity_id]
    ]
    history_list: MutableMapping[str, list[State]] = {}
    if entities_full_history:
        history_list = history.get_full_significant_states_with_session(
            hass,
            session,
            start - datetime.timedelta.resolution,
            end,
            entity_ids=entities_full_history,
            significant_changes_only=False,
        )
    entities_significant_history = [
        i.entity_id
        for i in sensor_states
        if "sum" not in wanted_statistics[i.entity_id]
    ]
    if entities_significant_history:
        _history_list = history.get_full_significant_states_with_session(
            hass,
            session,
            start - datetime.timedelta.resolution,
            end,
            entity_ids=entities_significant_history,
        )
        history_list = {**history_list, **_history_list}

    entities_with_float_states: dict[str, list[tuple[float, State]]] = {}
    for _state in sensor_states:
        entity_id = _state.entity_id
        # If there are no recent state changes, the sensor's state may already be pruned
        # from the recorder. Get the state from the state machine instead.
        if not (entity_history := history_list.get(entity_id, [_state])):
            continue
        if not (float_states := _entity_history_to_float_and_state(entity_history)):
            continue
        entities_with_float_states[entity_id] = float_states

    # Only lookup metadata for entities that have valid float states
    # since it will result in cache misses for statistic_ids
    # that are not in the metadata table and we are not working
    # with them anyway.
    old_metadatas = statistics.get_metadata_with_session(
        get_instance(hass), session, statistic_ids=set(entities_with_float_states)
    )
    to_process: list[tuple[str, str | None, str, list[tuple[float, State]]]] = []
    to_query: set[str] = set()
    for _state in sensor_states:
        entity_id = _state.entity_id
        if not (maybe_float_states := entities_with_float_states.get(entity_id)):
            continue
        statistics_unit, valid_float_states = _normalize_states(
            hass,
            old_metadatas,
            maybe_float_states,
            entity_id,
        )
        if not valid_float_states:
            continue
        state_class: str = _state.attributes[ATTR_STATE_CLASS]
        to_process.append((entity_id, statistics_unit, state_class, valid_float_states))
        if "sum" in wanted_statistics[entity_id]:
            to_query.add(entity_id)

    last_stats = statistics.get_latest_short_term_statistics(
        hass, to_query, {"last_reset", "state", "sum"}, metadata=old_metadatas
    )
    for (  # pylint: disable=too-many-nested-blocks
        entity_id,
        statistics_unit,
        state_class,
        valid_float_states,
    ) in to_process:
        # Check metadata
        if old_metadata := old_metadatas.get(entity_id):
            if not _equivalent_units(
                {old_metadata[1]["unit_of_measurement"], statistics_unit}
            ):
                if WARN_UNSTABLE_UNIT not in hass.data:
                    hass.data[WARN_UNSTABLE_UNIT] = set()
                if entity_id not in hass.data[WARN_UNSTABLE_UNIT]:
                    hass.data[WARN_UNSTABLE_UNIT].add(entity_id)
                    _LOGGER.warning(
                        (
                            "The unit of %s (%s) cannot be converted to the unit of"
                            " previously compiled statistics (%s). Generation of long"
                            " term statistics will be suppressed unless the unit"
                            " changes back to %s or a compatible unit. Go to %s to fix"
                            " this"
                        ),
                        entity_id,
                        statistics_unit,
                        old_metadata[1]["unit_of_measurement"],
                        old_metadata[1]["unit_of_measurement"],
                        LINK_DEV_STATISTICS,
                    )
                continue

        # Set meta data
        meta: StatisticMetaData = {
            "has_mean": "mean" in wanted_statistics[entity_id],
            "has_sum": "sum" in wanted_statistics[entity_id],
            "name": None,
            "source": RECORDER_DOMAIN,
            "statistic_id": entity_id,
            "unit_of_measurement": statistics_unit,
        }

        # Make calculations
        stat: StatisticData = {"start": start}
        if "max" in wanted_statistics[entity_id]:
            stat["max"] = max(
                *itertools.islice(
                    zip(*valid_float_states),  # type: ignore[typeddict-item]
                    1,
                )
            )
        if "min" in wanted_statistics[entity_id]:
            stat["min"] = min(
                *itertools.islice(
                    zip(*valid_float_states),  # type: ignore[typeddict-item]
                    1,
                )
            )

        if "mean" in wanted_statistics[entity_id]:
            stat["mean"] = _time_weighted_average(valid_float_states, start, end)

        if "sum" in wanted_statistics[entity_id]:
            last_reset = old_last_reset = None
            new_state = old_state = None
            _sum = 0.0
            if entity_id in last_stats:
                # We have compiled history for this sensor before,
                # use that as a starting point.
                last_stat = last_stats[entity_id][0]
                last_reset = _timestamp_to_isoformat_or_none(last_stat["last_reset"])
                old_last_reset = last_reset
                # If there are no previous values and has_sum
                # was previously false there will be no last_stat
                # for state or sum
                new_state = old_state = last_stat.get("state")
                _sum = last_stat.get("sum") or 0.0

            for fstate, state in valid_float_states:
                reset = False
                if (
                    state_class != SensorStateClass.TOTAL_INCREASING
                    and (
                        last_reset := _last_reset_as_utc_isoformat(
                            state.attributes.get("last_reset"), entity_id
                        )
                    )
                    != old_last_reset
                    and last_reset is not None
                ):
                    if old_state is None:
                        _LOGGER.info(
                            (
                                "Compiling initial sum statistics for %s, zero point"
                                " set to %s"
                            ),
                            entity_id,
                            fstate,
                        )
                    else:
                        _LOGGER.info(
                            (
                                "Detected new cycle for %s, last_reset set to %s (old"
                                " last_reset %s)"
                            ),
                            entity_id,
                            last_reset,
                            old_last_reset,
                        )
                    reset = True
                elif old_state is None and last_reset is None:
                    reset = True
                    _LOGGER.info(
                        "Compiling initial sum statistics for %s, zero point set to %s",
                        entity_id,
                        fstate,
                    )
                elif state_class == SensorStateClass.TOTAL_INCREASING:
                    try:
                        if old_state is None or reset_detected(
                            hass, entity_id, fstate, new_state, state
                        ):
                            reset = True
                            _LOGGER.info(
                                (
                                    "Detected new cycle for %s, value dropped from %s"
                                    " to %s, triggered by state with last_updated set"
                                    " to %s"
                                ),
                                entity_id,
                                new_state,
                                fstate,
                                state.last_updated.isoformat(),
                            )
                    except HomeAssistantError:
                        continue

                if reset:
                    # The sensor has been reset, update the sum
                    if old_state is not None and new_state is not None:
                        _sum += new_state - old_state
                    # ..and update the starting point
                    new_state = fstate
                    old_last_reset = last_reset
                    # Force a new cycle for an existing sensor to start at 0
                    if old_state is not None:
                        old_state = 0.0
                    else:
                        old_state = new_state
                else:
                    new_state = fstate

            if new_state is None or old_state is None:
                # No valid updates
                continue

            # Update the sum with the last state
            _sum += new_state - old_state
            if last_reset is not None:
                stat["last_reset"] = dt_util.parse_datetime(last_reset)
            stat["sum"] = _sum
            stat["state"] = new_state

        result.append({"meta": meta, "stat": stat})

    return statistics.PlatformCompiledStatistics(result, old_metadatas)


def list_statistic_ids(
    hass: HomeAssistant,
    statistic_ids: list[str] | tuple[str] | None = None,
    statistic_type: str | None = None,
) -> dict:
    """Return all or filtered statistic_ids and meta data."""
    entities = _get_sensor_states(hass)

    result: dict[str, StatisticMetaData] = {}

    for state in entities:
        state_class = state.attributes[ATTR_STATE_CLASS]
        state_unit = state.attributes.get(ATTR_UNIT_OF_MEASUREMENT)

        provided_statistics = DEFAULT_STATISTICS[state_class]
        if statistic_type is not None and statistic_type not in provided_statistics:
            continue

        if statistic_ids is not None and state.entity_id not in statistic_ids:
            continue

        if (
            "sum" in provided_statistics
            and ATTR_LAST_RESET not in state.attributes
            and state.attributes.get(ATTR_STATE_CLASS) == SensorStateClass.MEASUREMENT
        ):
            continue

        result[state.entity_id] = {
            "has_mean": "mean" in provided_statistics,
            "has_sum": "sum" in provided_statistics,
            "name": None,
            "source": RECORDER_DOMAIN,
            "statistic_id": state.entity_id,
            "unit_of_measurement": state_unit,
        }
        continue

    return result


def validate_statistics(
    hass: HomeAssistant,
) -> dict[str, list[statistics.ValidationIssue]]:
    """Validate statistics."""
    validation_result = defaultdict(list)

    sensor_states = hass.states.all(DOMAIN)
    metadatas = statistics.get_metadata(hass, statistic_source=RECORDER_DOMAIN)
    sensor_entity_ids = {i.entity_id for i in sensor_states}
    sensor_statistic_ids = set(metadatas)
    instance = get_instance(hass)

    for state in sensor_states:
        entity_id = state.entity_id
        state_class = try_parse_enum(
            SensorStateClass, state.attributes.get(ATTR_STATE_CLASS)
        )
        state_unit = state.attributes.get(ATTR_UNIT_OF_MEASUREMENT)

        if metadata := metadatas.get(entity_id):
            if not instance.entity_filter(state.entity_id):
                # Sensor was previously recorded, but no longer is
                validation_result[entity_id].append(
                    statistics.ValidationIssue(
                        "entity_no_longer_recorded",
                        {"statistic_id": entity_id},
                    )
                )

            if state_class is None:
                # Sensor no longer has a valid state class
                validation_result[entity_id].append(
                    statistics.ValidationIssue(
                        "unsupported_state_class",
                        {"statistic_id": entity_id, "state_class": state_class},
                    )
                )

            metadata_unit = metadata[1]["unit_of_measurement"]
            converter = statistics.STATISTIC_UNIT_TO_UNIT_CONVERTER.get(metadata_unit)
            if not converter:
                if not _equivalent_units({state_unit, metadata_unit}):
                    # The unit has changed, and it's not possible to convert
                    validation_result[entity_id].append(
                        statistics.ValidationIssue(
                            "units_changed",
                            {
                                "statistic_id": entity_id,
                                "state_unit": state_unit,
                                "metadata_unit": metadata_unit,
                                "supported_unit": metadata_unit,
                            },
                        )
                    )
            elif state_unit not in converter.VALID_UNITS:
                # The state unit can't be converted to the unit in metadata
                valid_units = (unit or "<None>" for unit in converter.VALID_UNITS)
                valid_units_str = ", ".join(sorted(valid_units))
                validation_result[entity_id].append(
                    statistics.ValidationIssue(
                        "units_changed",
                        {
                            "statistic_id": entity_id,
                            "state_unit": state_unit,
                            "metadata_unit": metadata_unit,
                            "supported_unit": valid_units_str,
                        },
                    )
                )
        elif state_class is not None:
            if not instance.entity_filter(state.entity_id):
                # Sensor is not recorded
                validation_result[entity_id].append(
                    statistics.ValidationIssue(
                        "entity_not_recorded",
                        {"statistic_id": entity_id},
                    )
                )

    for statistic_id in sensor_statistic_ids - sensor_entity_ids:
        if split_entity_id(statistic_id)[0] != DOMAIN:
            continue
        # There is no sensor matching the statistics_id
        validation_result[statistic_id].append(
            statistics.ValidationIssue(
                "no_state",
                {
                    "statistic_id": statistic_id,
                },
            )
        )

    return validation_result


@callback
def exclude_attributes(hass: HomeAssistant) -> set[str]:
    """Exclude attributes from being recorded in the database."""
    return {ATTR_OPTIONS}
