from datetime import datetime
from decimal import Decimal
from typing import Iterable

from app.domain.enums import NormalizationStatus
from app.domain.models import AttributeStatement


def statement_is_usable(statement: AttributeStatement | None, minimum_confidence: Decimal) -> bool:
    if statement is None:
        return False
    if statement.normalization_status != NormalizationStatus.NORMALIZED:
        return False
    if statement.normalized_value is None:
        return False
    return statement.confidence >= minimum_confidence


def select_attribute_snapshot(
    statements: Iterable[AttributeStatement],
    *,
    as_of: datetime,
    snapshot_cutoff: datetime,
) -> dict[str, AttributeStatement]:
    """Pick the newest statement per key at or before the evaluation cutoff."""
    chosen: dict[str, AttributeStatement] = {}
    for statement in statements:
        if statement.observed_at > as_of or statement.ingested_at > snapshot_cutoff:
            continue
        current = chosen.get(statement.attribute)
        if current is None or _is_newer(statement, current):
            chosen[statement.attribute] = statement
    return chosen


def _is_newer(candidate: AttributeStatement, current: AttributeStatement) -> bool:
    return (
        candidate.observed_at,
        candidate.ingested_at,
        candidate.id,
    ) > (
        current.observed_at,
        current.ingested_at,
        current.id,
    )