from __future__ import annotations

from collections import defaultdict
from datetime import datetime, timedelta, timezone
from zoneinfo import ZoneInfo

from fastapi import APIRouter, HTTPException, Query

from app.db.repositories import get_earliest_reading_ts, get_usage_series
from app.db.session import get_session

router = APIRouter(prefix="/api/usage", tags=["usage"])

BNE = ZoneInfo("Australia/Brisbane")


def _resolve_start(session, days: str, end: datetime) -> datetime:
    if days == "all":
        return get_earliest_reading_ts(session) or end
    try:
        n = int(days)
    except ValueError:
        raise HTTPException(400, "days must be an integer or 'all'")
    if n < 1:
        raise HTTPException(400, "days must be >= 1")
    return end - timedelta(days=n)


def _bucket_key(local_date, granularity: str) -> str:
    if granularity == "month":
        return local_date.replace(day=1).isoformat()
    if granularity == "week":
        return (local_date - timedelta(days=local_date.weekday())).isoformat()
    return local_date.isoformat()


@router.get("/daily")
def daily_usage(days: str = Query("30")) -> list[dict]:
    end = datetime.now(timezone.utc)
    with get_session() as session:
        start = _resolve_start(session, days, end)
        rows = get_usage_series(session, start, end)

    # Plotting one bar per day is unreadable (and slow) once the range
    # stretches into years, so roll up to weekly/monthly buckets for long
    # ranges -- this is a display concern only, the underlying stored data
    # stays at full 5-minute resolution.
    span_days = (end - start).days
    granularity = "month" if span_days > 550 else "week" if span_days > 120 else "day"

    by_bucket: dict[str, dict[str, float]] = defaultdict(lambda: {"generation_kwh": 0.0, "load_kwh": 0.0, "import_kwh": 0.0, "export_kwh": 0.0})
    for row in rows:
        key = _bucket_key(row.ts.astimezone(BNE).date(), granularity)
        bucket = by_bucket[key]
        bucket["generation_kwh"] += row.generation_kwh
        bucket["load_kwh"] += row.load_kwh
        bucket["import_kwh"] += row.import_kwh
        bucket["export_kwh"] += row.export_kwh

    return [{"date": day, **{k: round(v, 3) for k, v in totals.items()}} for day, totals in sorted(by_bucket.items())]


@router.get("/summary")
def usage_summary(days: str = Query("30")) -> dict:
    end = datetime.now(timezone.utc)
    with get_session() as session:
        start = _resolve_start(session, days, end)
        rows = get_usage_series(session, start, end)
    if not rows:
        return {"days_with_data": 0}

    dates_seen: set[str] = set()
    totals = {"generation_kwh": 0.0, "load_kwh": 0.0, "import_kwh": 0.0, "export_kwh": 0.0}
    for row in rows:
        dates_seen.add(row.ts.astimezone(BNE).date().isoformat())
        totals["generation_kwh"] += row.generation_kwh
        totals["load_kwh"] += row.load_kwh
        totals["import_kwh"] += row.import_kwh
        totals["export_kwh"] += row.export_kwh

    return {
        "days_with_data": len(dates_seen),
        "first_day": min(dates_seen),
        "last_day": max(dates_seen),
        **{k: round(v, 2) for k, v in totals.items()},
    }