from datetime import UTC, datetime, timedelta

import asyncpg

from utils.read.accounts import self_user_id
from utils.read.models import ResponseStats, VolumeBucket


async def message_volume(
    pool: asyncpg.Pool, account_id: int, chat_id: int, *, days: int = 90
) -> list[VolumeBucket]:
    self_id = await self_user_id(pool, account_id)
    rows = await pool.fetch(
        "SELECT date_trunc('day', date) AS bucket, count(*) AS total, "
        "count(*) FILTER (WHERE sender_id = $3) AS outgoing "
        "FROM messages "
        "WHERE account_id = $1 AND chat_id = $2 AND date >= $4 "
        "GROUP BY bucket ORDER BY bucket",
        account_id,
        chat_id,
        self_id,
        datetime.now(UTC) - timedelta(days=days),
    )
    return [
        VolumeBucket(
            bucket=row["bucket"],
            total=row["total"],
            outgoing=row["outgoing"],
            incoming=row["total"] - row["outgoing"],
        )
        for row in rows
    ]


async def response_stats(
    pool: asyncpg.Pool, account_id: int, chat_id: int, *, days: int = 365
) -> ResponseStats:
    self_id = await self_user_id(pool, account_id)
    rows = await pool.fetch(
        "WITH ordered AS ("
        "SELECT sender_id, date, "
        "lag(sender_id) OVER w AS prev_sender, "
        "lag(date) OVER w AS prev_date "
        "FROM messages "
        "WHERE account_id = $1 AND chat_id = $2 AND sender_id IS NOT NULL "
        "AND date >= $4 "
        "WINDOW w AS (ORDER BY date, message_id)), "
        "resp AS ("
        "SELECT (sender_id = $3) AS is_mine, "
        "EXTRACT(EPOCH FROM (date - prev_date)) AS secs "
        "FROM ordered "
        "WHERE prev_sender IS NOT NULL AND prev_sender <> sender_id) "
        "SELECT is_mine, count(*) AS n, "
        "percentile_cont(0.5) WITHIN GROUP (ORDER BY secs) AS median_secs "
        "FROM resp GROUP BY is_mine",
        account_id,
        chat_id,
        self_id,
        datetime.now(UTC) - timedelta(days=days),
    )
    stats = ResponseStats(
        mine_median_seconds=None, mine_count=0, their_median_seconds=None, their_count=0
    )
    for row in rows:
        if row["is_mine"]:
            stats.mine_median_seconds = row["median_secs"]
            stats.mine_count = row["n"]
        else:
            stats.their_median_seconds = row["median_secs"]
            stats.their_count = row["n"]
    return stats