"""Unified training launcher for one or more models."""
import argparse
import json
import os
import subprocess
import sys
import time
from datetime import datetime

from training.registry import DEFAULT_MODELS, normalize_model_list
from utils.run_dirs import resolve_run_root


PLOT_REFRESH_INTERVAL = 30
PROCESS_POLL_INTERVAL = 5


def parse_args():
    parser = argparse.ArgumentParser(
        description="Launch unified training for one or more models.",
    )
    parser.add_argument(
        "--models",
        nargs="*",
        default=None,
        help=(
            "Model names to train. "
            f"Defaults to: {', '.join(DEFAULT_MODELS)}"
        ),
    )
    parser.add_argument(
        "--run-timestamp",
        type=str,
        default=None,
        help="Run timestamp tag. Defaults to the current time.",
    )
    parser.add_argument(
        "--interval",
        type=int,
        default=PLOT_REFRESH_INTERVAL,
        help="Live plot refresh interval in seconds.",
    )
    parser.add_argument(
        "--no-plotter",
        action="store_true",
        help="Disable the live plotter process.",
    )
    return parser.parse_args()


def launch_model_process(model_name, run_timestamp, run_log_root, run_ckpt_root):
    log_dir = os.path.join(run_log_root, model_name)
    checkpoint_dir = os.path.join(run_ckpt_root, model_name)
    os.makedirs(log_dir, exist_ok=True)
    os.makedirs(checkpoint_dir, exist_ok=True)

    stdout_path = os.path.join(log_dir, "stdout.txt")
    stdout_handle = open(stdout_path, "w", encoding="utf-8")
    process = subprocess.Popen(
        [
            sys.executable,
            "-m",
            "training.run_model",
            "--model",
            model_name,
            "--log-dir",
            log_dir,
            "--checkpoint-dir",
            checkpoint_dir,
            "--run-timestamp",
            run_timestamp,
        ],
        stdout=stdout_handle,
        stderr=subprocess.STDOUT,
    )
    return process, stdout_handle, stdout_path


def launch_plotter(run_timestamp, run_log_root, interval):
    stdout_path = os.path.join(run_log_root, "plotter_stdout.txt")
    stdout_handle = open(stdout_path, "w", encoding="utf-8")
    process = subprocess.Popen(
        [
            sys.executable,
            "-m",
            "scripts.plot_live_training",
            "--all-models",
            "--run",
            run_timestamp,
            "--watch",
            "--interval",
            str(interval),
        ],
        stdout=stdout_handle,
        stderr=subprocess.STDOUT,
    )
    return process, stdout_handle, stdout_path


def now_str():
    return datetime.now().strftime("%H:%M:%S")


def read_log_tail(log_path, max_lines=40):
    if not log_path or not os.path.isfile(log_path):
        return []
    with open(log_path, "r", encoding="utf-8", errors="replace") as f:
        lines = f.readlines()
    return [line.rstrip("\n") for line in lines[-max_lines:]]


def write_run_status(run_root, run_timestamp, model_states, plotter_state=None):
    payload = {
        "run_timestamp": run_timestamp,
        "updated_at": datetime.now().isoformat(timespec="seconds"),
        "models": model_states,
    }
    if plotter_state is not None:
        payload["plotter"] = plotter_state

    status_path = os.path.join(run_root, "run_status.json")
    with open(status_path, "w", encoding="utf-8") as f:
        json.dump(payload, f, ensure_ascii=False, indent=2)


def print_failure_excerpt(name, log_path, returncode):
    print(f"[{now_str()}] {name} failed with code={returncode}")
    print(f"  Log: {log_path}")
    tail_lines = read_log_tail(log_path)
    if tail_lines:
        print("  Last log lines:")
        for line in tail_lines:
            encoding = sys.stdout.encoding or "utf-8"
            safe_line = line.encode(encoding, errors="replace").decode(encoding, errors="replace")
            print(f"    {safe_line}")
    else:
        print("  No readable log content found.")


def terminate_process(process):
    if process is None or process.poll() is not None:
        return
    process.terminate()
    try:
        process.wait(timeout=10)
    except subprocess.TimeoutExpired:
        process.kill()


def monitor_processes(processes, run_root, run_timestamp, plotter_info=None):
    pending = set(processes.keys())
    model_states = {}
    for model_name, info in processes.items():
        model_states[model_name] = {
            "status": "running",
            "pid": info["process"].pid,
            "log_dir": info["log_dir"],
            "stdout_path": info["stdout_path"],
            "checkpoint_dir": info["checkpoint_dir"],
            "started_at": info["started_at"],
        }

    plotter_state = None
    if plotter_info is not None:
        plotter_state = {
            "status": "running",
            "pid": plotter_info["process"].pid,
            "stdout_path": plotter_info["stdout_path"],
            "started_at": plotter_info["started_at"],
        }

    write_run_status(run_root, run_timestamp, model_states, plotter_state)

    while pending:
        for model_name in list(pending):
            info = processes[model_name]
            process = info["process"]
            returncode = process.poll()
            if returncode is None:
                continue

            pending.remove(model_name)
            status = "completed" if returncode == 0 else "failed"
            model_states[model_name]["status"] = status
            model_states[model_name]["returncode"] = returncode
            model_states[model_name]["finished_at"] = datetime.now().isoformat(timespec="seconds")
            write_run_status(run_root, run_timestamp, model_states, plotter_state)

            if returncode == 0:
                print(f"[{now_str()}] [{model_name.upper()}] completed")
            else:
                print_failure_excerpt(model_name.upper(), info["stdout_path"], returncode)

        if plotter_info is not None and plotter_state is not None and plotter_state["status"] == "running":
            plotter_returncode = plotter_info["process"].poll()
            if plotter_returncode is not None:
                plotter_state["status"] = "completed" if plotter_returncode == 0 else "failed"
                plotter_state["returncode"] = plotter_returncode
                plotter_state["finished_at"] = datetime.now().isoformat(timespec="seconds")
                write_run_status(run_root, run_timestamp, model_states, plotter_state)
                if plotter_returncode != 0:
                    print_failure_excerpt("PLOTTER", plotter_info["stdout_path"], plotter_returncode)

        if pending:
            time.sleep(PROCESS_POLL_INTERVAL)

    return model_states, plotter_state


def main():
    args = parse_args()
    models = normalize_model_list(args.models)
    run_timestamp, run_root = resolve_run_root(args.run_timestamp or datetime.now().strftime("%Y%m%d_%H%M%S"))
    run_log_root = os.path.join(run_root, "logs")
    run_ckpt_root = os.path.join(run_root, "checkpoints")
    os.makedirs(run_log_root, exist_ok=True)
    os.makedirs(run_ckpt_root, exist_ok=True)

    processes = {}
    handles = []
    model_states = None
    plotter_state = None

    try:
        for model_name in models:
            print(f"[{datetime.now().strftime('%H:%M:%S')}] Launching {model_name.upper()} training...")
            process, stdout_handle, stdout_path = launch_model_process(
                model_name,
                run_timestamp,
                run_log_root,
                run_ckpt_root,
            )
            processes[model_name] = {
                "process": process,
                "stdout_path": stdout_path,
                "stdout_handle": stdout_handle,
                "log_dir": os.path.join(run_log_root, model_name),
                "checkpoint_dir": os.path.join(run_ckpt_root, model_name),
                "started_at": datetime.now().isoformat(timespec="seconds"),
            }
            handles.append(stdout_handle)
            print(f"  PID: {process.pid}")

        plotter_process = None
        plotter_info = None
        if not args.no_plotter:
            plotter_process, plotter_stdout, plotter_stdout_path = launch_plotter(
                run_timestamp,
                run_log_root,
                args.interval,
            )
            handles.append(plotter_stdout)
            plotter_info = {
                "process": plotter_process,
                "stdout_path": plotter_stdout_path,
                "stdout_handle": plotter_stdout,
                "started_at": datetime.now().isoformat(timespec="seconds"),
            }
            print(f"[{datetime.now().strftime('%H:%M:%S')}] Launching live plotter...")
            print(f"  PID: {plotter_process.pid}")

        print()
        print(f"Started {len(models)} training job(s).")
        print(f"Run timestamp: {run_timestamp}")
        print(f"Models: {', '.join(models)}")
        print()

        model_states, plotter_state = monitor_processes(
            processes,
            run_root,
            run_timestamp,
            plotter_info=plotter_info,
        )
        failed_models = [
            model_name for model_name, state in model_states.items()
            if state["status"] != "completed"
        ]
        if failed_models:
            print()
            print(f"[{now_str()}] Failed models: {', '.join(failed_models)}")
            print(f"[{now_str()}] See run status: {os.path.join(run_root, 'run_status.json')}")
            sys.exit(1)
    finally:
        if "plotter_process" in locals():
            terminate_process(plotter_process)
            if plotter_state is not None and plotter_state.get("status") == "running":
                plotter_state["status"] = "terminated"
                plotter_state["finished_at"] = datetime.now().isoformat(timespec="seconds")

        for info in processes.values():
            terminate_process(info["process"])

        if model_states is not None:
            write_run_status(run_root, run_timestamp, model_states, plotter_state)

        for handle in handles:
            handle.close()


if __name__ == "__main__":
    main()