"""Mesure l'occupation disque et les temps de réponse à l'échelle du festival.

Cible : 1400 bénévoles, 110 groupes, 500 messages par groupe, 5 jours.
Le tier gratuit Hugging Face offre 1 Go persistant : ce script vérifie qu'on
reste très en dessous, et que les écrans les plus sollicités répondent vite
une fois la base pleine.

Usage : python scripts/load_test.py [--users 1400] [--groups 110] [--messages 500]

La base est créée dans un répertoire temporaire dédié et supprimée à la fin.
"""

from __future__ import annotations

import argparse
import random
import shutil
import statistics
import sys
import time
from pathlib import Path

TEST_DIR = Path("/tmp/motoc-load")
if TEST_DIR.exists():
    shutil.rmtree(TEST_DIR)
TEST_DIR.mkdir(parents=True)

import os  # noqa: E402

os.environ["DATA_DIR"] = str(TEST_DIR)
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))

from app import config, db, maintenance  # noqa: E402
from app.auth import CurrentUser  # noqa: E402
from app.services import groups_for_user  # noqa: E402

# Message représentatif : les messages de coordination sont courts, mais on
# prend une longueur généreuse pour ne pas sous-estimer l'occupation.
SAMPLE = (
    "Point de situation : équipe en place au bar 2, il manque deux personnes "
    "pour la relève de 18h, merci de confirmer votre présence."
)


def mb(value: int) -> str:
    return f"{value / 1024 / 1024:.1f} Mo"


def build(users: int, groups: int, messages: int) -> None:
    now = db.now_ms()
    festival_ms = 5 * 86_400_000

    phones = [f"06{i:08d}" for i in range(users)]
    db.execute_many(
        "INSERT INTO users(phone, first_name, last_name, nickname, pin_hash, pin_salt, "
        "status, created_at) VALUES(?, ?, ?, ?, ?, ?, 'active', ?)",
        [
            (
                phone,
                f"Prénom{index}",
                f"NOMDEFAMILLE{index}",
                f"Pseudo{index}",
                "a" * 64,  # longueur d'un hash scrypt hexadécimal
                "b" * 32,
                now,
            )
            for index, phone in enumerate(phones)
        ],
    )

    group_ids = []
    for index in range(groups):
        # Un tiers de sous-groupes, comme dans l'organisation réelle.
        parent = group_ids[index % max(1, len(group_ids))] if index > 2 and index % 3 == 0 else None
        cur = db.execute(
            "INSERT INTO groups(name, parent_id, description, created_at) VALUES(?, ?, ?, ?)",
            (f"Groupe {index}", parent, "Description du groupe", now),
        )
        group_ids.append(cur.lastrowid)

    # Chaque bénévole appartient à 3 groupes en moyenne.
    memberships = []
    for index, phone in enumerate(phones):
        for offset in range(3):
            memberships.append((group_ids[(index * 3 + offset) % groups], phone, "member", now))
    db.execute_many(
        "INSERT OR IGNORE INTO memberships(group_id, phone, role, joined_at) VALUES(?, ?, ?, ?)",
        memberships,
    )

    rows = []
    for gid in group_ids:
        for index in range(messages):
            author = phones[(gid + index) % users]
            rows.append(
                (
                    gid,
                    author,
                    f"Pseudo{(gid + index) % users}",
                    "text",
                    SAMPLE,
                    None,
                    now - festival_ms + int(index / messages * festival_ms),
                )
            )
    db.execute_many(
        "INSERT INTO messages(group_id, author_phone, author_label, kind, body, meta, created_at) "
        "VALUES(?, ?, ?, ?, ?, ?, ?)",
        rows,
    )

    # État de lecture : un enregistrement par couple (bénévole, groupe).
    db.execute_many(
        "INSERT OR IGNORE INTO read_state(phone, group_id, last_read_id) VALUES(?, ?, ?)",
        [(phone, gid, 0) for gid, phone, _, _ in memberships],
    )


def timed(label: str, function, repeats: int = 5) -> float:
    samples = []
    for _ in range(repeats):
        start = time.perf_counter()
        function()
        samples.append((time.perf_counter() - start) * 1000)
    median = statistics.median(samples)
    flag = "\033[32m✓\033[0m" if median < 400 else "\033[33m!\033[0m"
    print(f"  {flag} {label:<46} {median:7.1f} ms")
    return median


def main() -> int:
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--users", type=int, default=1400)
    parser.add_argument("--groups", type=int, default=110)
    parser.add_argument("--messages", type=int, default=500)
    args = parser.parse_args()

    total_messages = args.groups * args.messages
    print(
        f"\n\033[1mCharge simulée : {args.users} bénévoles, {args.groups} groupes, "
        f"{total_messages} messages\033[0m\n"
    )

    db.connect()
    start = time.perf_counter()
    build(args.users, args.groups, args.messages)
    print(f"  base construite en {time.perf_counter() - start:.1f} s")

    size = db.db_size_bytes()
    quota = 1024 * 1024 * 1024
    print(f"\n\033[1mOccupation disque\033[0m")
    print(f"  base complète                                  {mb(size)}")
    print(f"  part du quota de 1 Go                          {size / quota * 100:.1f} %")
    print(f"  par message                                    {size / total_messages:.0f} o")

    print(f"\n\033[1mTemps de réponse, base pleine\033[0m")
    phones = [r["phone"] for r in db.query("SELECT phone FROM users LIMIT 50")]
    member = CurrentUser(
        phone=phones[0], first_name="A", last_name="B", nickname="P",
        is_superadmin=False, status="active",
    )
    admin = CurrentUser(
        phone=phones[1], first_name="A", last_name="B", nickname="P",
        is_superadmin=True, status="active",
    )
    gid = db.query_one("SELECT id FROM groups LIMIT 1")["id"]

    worst = 0.0
    worst = max(worst, timed("liste des groupes (bénévole, 3 groupes)", lambda: groups_for_user(member)))
    worst = max(worst, timed(f"liste des groupes (superadmin, {args.groups} groupes)", lambda: groups_for_user(admin)))
    worst = max(
        worst,
        timed(
            "historique d'un groupe (50 messages)",
            lambda: db.query(
                "SELECT * FROM messages WHERE group_id = ? ORDER BY id DESC LIMIT 50", (gid,)
            ),
        ),
    )
    worst = max(
        worst,
        timed(
            "annuaire, recherche par nom (200 résultats)",
            lambda: db.query(
                "SELECT * FROM users WHERE nickname LIKE ? ORDER BY flagged DESC, status, "
                "nickname COLLATE NOCASE LIMIT 200",
                ("%Pseudo1%",),
            ),
        ),
    )
    worst = max(
        worst,
        timed(
            "compteurs d'adhésions (annuaire complet)",
            lambda: db.query("SELECT phone, COUNT(*) AS n FROM memberships GROUP BY phone"),
        ),
    )

    print(f"\n\033[1mPurge de rétention\033[0m")
    print(f"  quota configuré : {config.KEEP_MESSAGES_PER_GROUP} messages/groupe, "
          f"{config.RETENTION_DAYS} jours")
    start = time.perf_counter()
    result = maintenance.purge(aggressive=False)
    elapsed = time.perf_counter() - start
    print(f"  purge exécutée en {elapsed:.1f} s")
    print(f"  supprimés : {result['deleted_age']} par âge, {result['deleted_overflow']} par quota")
    print(f"  taille après purge et VACUUM : {mb(result['size_after'])}")

    db.close()
    shutil.rmtree(TEST_DIR, ignore_errors=True)

    ok = size < quota * 0.25 and worst < 400
    print(
        f"\n\033[1m{'✓ Marge confortable' if ok else '! À surveiller'} — "
        f"{mb(size)} sur 1 Go, requête la plus lente {worst:.0f} ms\033[0m\n"
    )
    return 0 if ok else 1


if __name__ == "__main__":
    sys.exit(main())