#!/usr/bin/env python3
"""Production preflight checks for the Math Conjecture Trainer Space."""

from __future__ import annotations

import argparse
import importlib
import json
import os
import subprocess
import sys
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Callable, Dict, List

import yaml


ROOT = Path(__file__).resolve().parents[1]
CONFIG_PATH = ROOT / "configs" / "math_conjecture_sota.yaml"
HF_HOME_DIR = ROOT / "workspace" / ".hf_home"
HF_DATASETS_CACHE_DIR = HF_HOME_DIR / "datasets"
HF_HUB_CACHE_DIR = HF_HOME_DIR / "hub"


@dataclass
class CheckResult:
    name: str
    ok: bool
    detail: str


def check_required_files() -> str:
    required = [
        ROOT / "app.py",
        ROOT / "scripts" / "train_sota.py",
        ROOT / "scripts" / "eval_sota.py",
        CONFIG_PATH,
        ROOT / "requirements.txt",
    ]
    missing = [str(path) for path in required if not path.exists()]
    if missing:
        raise FileNotFoundError("Missing required files: " + ", ".join(missing))
    return f"{len(required)} required files present."


def check_config_shape() -> str:
    cfg = yaml.safe_load(CONFIG_PATH.read_text(encoding="utf-8"))
    if not isinstance(cfg, dict):
        raise ValueError("Config root must be a mapping.")
    required_sections = ("model", "data", "stages")
    for section in required_sections:
        if section not in cfg:
            raise ValueError(f"Missing config section: {section}")
    stages = cfg.get("stages")
    if not isinstance(stages, list) or not stages:
        raise ValueError("Config must contain at least one stage.")
    return f"Config valid with {len(stages)} stage(s)."


def check_python_imports() -> str:
    modules = [
        "gradio",
        "torch",
        "yaml",
        "huggingface_hub",
        "datasets",
        "transformers",
        "peft",
    ]
    versions: Dict[str, str] = {}
    for module_name in modules:
        mod = importlib.import_module(module_name)
        versions[module_name] = str(getattr(mod, "__version__", "unknown"))
    return "Imports OK: " + ", ".join(f"{k}={v}" for k, v in versions.items())


def check_module_integrity() -> str:
    root_str = str(ROOT)
    if root_str not in sys.path:
        sys.path.insert(0, root_str)

    app = importlib.import_module("app")
    train_sota = importlib.import_module("scripts.train_sota")
    eval_sota = importlib.import_module("scripts.eval_sota")

    runtime = app.run_runtime_snapshot()
    if not isinstance(runtime, dict):
        raise ValueError("Runtime snapshot is not a dictionary.")
    if "python" not in runtime or "torch" not in runtime:
        raise ValueError("Runtime snapshot missing expected keys.")

    train_cfg = train_sota.load_config(CONFIG_PATH)
    eval_cfg = eval_sota.load_config(CONFIG_PATH)
    if not isinstance(train_cfg, dict) or not isinstance(eval_cfg, dict):
        raise ValueError("Config loaders did not return dictionaries.")
    return "App/train/eval module imports and config loaders are healthy."


def run_optional_training_dry_run(timeout_seconds: int) -> str:
    HF_HOME_DIR.mkdir(parents=True, exist_ok=True)
    HF_DATASETS_CACHE_DIR.mkdir(parents=True, exist_ok=True)
    HF_HUB_CACHE_DIR.mkdir(parents=True, exist_ok=True)
    env = os.environ.copy()
    env.setdefault("HF_HOME", str(HF_HOME_DIR))
    env.setdefault("HF_DATASETS_CACHE", str(HF_DATASETS_CACHE_DIR))
    env.setdefault("HUGGINGFACE_HUB_CACHE", str(HF_HUB_CACHE_DIR))

    cmd = [
        sys.executable,
        str(ROOT / "scripts" / "train_sota.py"),
        "--config",
        str(CONFIG_PATH),
        "--start-stage",
        "1",
        "--max-stages",
        "1",
        "--dry-run",
    ]
    completed = subprocess.run(
        cmd,
        cwd=str(ROOT),
        check=False,
        env=env,
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT,
        text=True,
        timeout=timeout_seconds,
    )
    if completed.returncode != 0:
        tail = "\n".join((completed.stdout or "").splitlines()[-30:])
        raise RuntimeError(f"Dry-run failed with exit code {completed.returncode}.\n{tail}")
    return "Optional training dry-run passed."


def run_checks(checks: List[tuple[str, Callable[[], str]]]) -> List[CheckResult]:
    out: List[CheckResult] = []
    for name, fn in checks:
        try:
            detail = fn()
            out.append(CheckResult(name=name, ok=True, detail=detail))
        except Exception as exc:
            out.append(CheckResult(name=name, ok=False, detail=f"{type(exc).__name__}: {exc}"))
    return out


def parse_args() -> argparse.Namespace:
    parser = argparse.ArgumentParser(description="Run production preflight checks for the Space trainer.")
    parser.add_argument(
        "--run-training-dry-run",
        action="store_true",
        help="Also execute scripts/train_sota.py in --dry-run mode (stage 1 only).",
    )
    parser.add_argument(
        "--dry-run-timeout-seconds",
        type=int,
        default=1800,
        help="Timeout for optional training dry-run step.",
    )
    parser.add_argument(
        "--json",
        action="store_true",
        help="Print machine-readable JSON output.",
    )
    return parser.parse_args()


def main() -> None:
    args = parse_args()
    checks: List[tuple[str, Callable[[], str]]] = [
        ("required_files", check_required_files),
        ("config_shape", check_config_shape),
        ("python_imports", check_python_imports),
        ("module_integrity", check_module_integrity),
    ]
    if args.run_training_dry_run:
        checks.append(
            (
                "training_dry_run",
                lambda: run_optional_training_dry_run(timeout_seconds=max(30, args.dry_run_timeout_seconds)),
            )
        )

    results = run_checks(checks)
    ok = all(item.ok for item in results)
    payload: Dict[str, Any] = {
        "ok": ok,
        "checks": [{"name": item.name, "ok": item.ok, "detail": item.detail} for item in results],
    }

    if args.json:
        print(json.dumps(payload, ensure_ascii=True, indent=2))
    else:
        for item in results:
            status = "PASS" if item.ok else "FAIL"
            print(f"[{status}] {item.name}: {item.detail}")
        print("Overall:", "PASS" if ok else "FAIL")

    if not ok:
        raise SystemExit(1)


if __name__ == "__main__":
    main()