"""File-coverage validation for a reporting month: wrong month, overlaps, gaps, coverage.

Multi-marketplace aware: overlap/gap checks compare only files of the SAME marketplace
(each market ships its own full-month file), and a few days of boundary spillover is
tolerated (Amazon exports use UTC/PST cuts, so a January file legitimately starts with
Dec-31 evening rows).
"""
from __future__ import annotations

from datetime import date, timedelta

from .xlsx_reader import FileMeta

# Rows this close to the month boundary are normal timezone spillover, not a wrong month.
BOUNDARY_GRACE_DAYS = 3


def validate_coverage(metas: list[FileMeta], month_end: date | None) -> list[dict]:
    exc: list[dict] = []
    if not month_end:
        return exc
    first = month_end.replace(day=1)
    lo = first - timedelta(days=BOUNDARY_GRACE_DAYS)
    hi = month_end + timedelta(days=BOUNDARY_GRACE_DAYS)

    dated = [(m.filename, m.min_date, m.max_date, m.marketplace or "")
             for m in metas if m.min_date and m.max_date]

    # (1) files clearly outside the reporting month — prevents mixing months.
    for fn, mn, mx, _mkt in dated:
        if mx < lo or mn > hi:
            exc.append({"category": "wrong_month", "severity": "error",
                        "detail": f"{fn} covers {mn}..{mx}, outside reporting month "
                                  f"{first:%Y-%m}", "source": fn})
        elif mn < lo or mx > hi:
            exc.append({"category": "wrong_month", "severity": "warning",
                        "detail": f"{fn} extends well beyond the reporting month "
                                  f"({mn}..{mx} vs {first}..{month_end})", "source": fn})

    # (2)+(3) overlaps and gaps — only within the SAME marketplace.
    by_mkt: dict[str, list[tuple[str, date, date]]] = {}
    for fn, mn, mx, mkt in dated:
        by_mkt.setdefault(mkt, []).append((fn, mn, mx))
    for mkt, entries in by_mkt.items():
        if len(entries) < 2:
            continue
        ds = sorted(entries, key=lambda x: x[1])
        for i in range(1, len(ds)):
            prev, cur = ds[i - 1], ds[i]
            if cur[1] <= prev[2]:
                exc.append({"category": "overlapping_files", "severity": "warning",
                            "detail": f"{cur[0]} ({cur[1]}..{cur[2]}) overlaps "
                                      f"{prev[0]} ({prev[1]}..{prev[2]})", "source": cur[0]})
            else:
                gs, ge = prev[2] + timedelta(days=1), cur[1] - timedelta(days=1)
                if gs <= ge:
                    exc.append({"category": "missing_dates", "severity": "warning",
                                "detail": f"Missing transactions {gs}..{ge} between "
                                          f"{prev[0]} and {cur[0]}", "source": ""})

    # (4) whole-month coverage across all files.
    if dated:
        allmin = min(x[1] for x in dated)
        allmax = max(x[2] for x in dated)
        if allmin > first:
            exc.append({"category": "missing_dates", "severity": "warning",
                        "detail": f"No transactions before {allmin}; month starts {first}",
                        "source": ""})
        if allmax < month_end:
            exc.append({"category": "missing_dates", "severity": "warning",
                        "detail": f"No transactions after {allmax}; month ends {month_end}",
                        "source": ""})
    return exc