"""Before/after per-pattern effectiveness (PRD §6.5 FR-M1/FR-M2; T02).

Given a change/pattern with an ``applied_at`` date, split sessions into *before*
and *after* by their start time, aggregate each side, and diff the headline
metrics — so we can say whether a distributed pattern (e.g. the Read-before-Edit
reflex, or the State Hub skill) actually moved the numbers, and retire it if not.
"""

from __future__ import annotations

from .metrics import aggregate

# Metrics where a *lower* value after the change means improvement.
_LOWER_IS_BETTER = {
    "infra_overhead_share_median", "infra_overhead_share_p90", "error_rate",
    "recurring_error_occurrences", "schema_thrash_sessions", "tokens_p50", "tokens_p90",
}
# Metrics where a *higher* value is improvement.
_HIGHER_IS_BETTER = {"success_rate"}


def split_by_date(digests: list[dict], applied_at: str) -> tuple[list[dict], list[dict]]:
    """Partition digests into (before, after) by ``started_at`` vs ``applied_at``."""
    before, after = [], []
    for d in digests:
        ts = d.get("started_at") or ""
        (after if ts and ts >= applied_at else before).append(d)
    return before, after


def _delta(metric: str, before: float, after: float) -> dict:
    change = round(after - before, 3)
    if metric in _LOWER_IS_BETTER:
        improved = change < 0
    elif metric in _HIGHER_IS_BETTER:
        improved = change > 0
    else:
        improved = None
    return {"before": before, "after": after, "change": change, "improved": improved}


def effectiveness(digests: list[dict], applied_at: str, *, label: str = "") -> dict:
    """Compare fleet metrics after ``applied_at`` against the prior period."""
    before, after = split_by_date(digests, applied_at)
    b_agg, a_agg = aggregate(before), aggregate(after)
    metrics = (_LOWER_IS_BETTER | _HIGHER_IS_BETTER)
    deltas = {}
    if before and after:
        for m in metrics:
            deltas[m] = _delta(m, b_agg.get(m, 0.0), a_agg.get(m, 0.0))
    return {
        "label": label,
        "applied_at": applied_at,
        "n_before": len(before),
        "n_after": len(after),
        "before": b_agg,
        "after": a_agg,
        "deltas": deltas,
        "insufficient_data": not (before and after),
    }