import asyncio
import logging
from dotenv import load_dotenv

from mathema.core.population_monitor import init_population
from mathema.genotype.neo4j.genotype import neo4j
from mathema.utils.logging_config import setup_logging

setup_logging()
log = logging.getLogger(__name__)

N_RUNS = 20


async def run_single_car_experiment(run_idx: int):
    pop_id = f"car_pop_run{run_idx:02d}"

    log.info(f"=== START RUN {run_idx + 1}/{N_RUNS} ({pop_id}) ===")

    monitor = await init_population((
        pop_id,
        [{"morphology": "car_racing_features", "neural_afs": ["tanh"]}],
        "gt",
        "competition",
    ))

    try:
        # ⏱️ max. 35 Minuten warten (30 min Training + Puffer)
        await asyncio.wait_for(
            monitor._stopped_evt.wait(),
            timeout=35 * 60
        )

    except asyncio.TimeoutError:
        log.error(
            f"[RUN {run_idx:02d}] TIMEOUT after 35min – forcing shutdown"
        )

        try:
            await monitor.stop("shutdown")
        except Exception as e:
            log.exception(
                f"[RUN {run_idx:02d}] failed to stop monitor cleanly: {e}"
            )

    # --- Post-run logging ---
    s = monitor.state
    try:
        best = await monitor._best_fitness_in_population(s.population_id)
    except Exception:
        best = float("nan")

    log.info(
        f"=== END RUN {run_idx + 1}/{N_RUNS} "
        f"gens={s.pop_gen} best_fitness={best:.6f} evals={s.eval_acc} ==="
    )


async def main():
    load_dotenv()
    try:
        for i in range(N_RUNS):
            await run_single_car_experiment(i)
        log.info("=== ALL RUNS FINISHED ===")
    finally:
        try:
            await neo4j.close()
        except Exception:
            pass


if __name__ == "__main__":
    asyncio.run(main())