import os
import random
import json
from pathlib import Path

import numpy as np
import pandas as pd
import yaml



def set_seed(seed: int = 17) -> None:
    """Set global seeds for Python, NumPy, and PyTorch."""
    os.environ["PYTHONHASHSEED"] = str(seed)
    random.seed(seed)
    np.random.seed(seed)
    try:
        import torch
        torch.manual_seed(seed)
        torch.cuda.manual_seed_all(seed)
        torch.backends.cudnn.deterministic = True
        torch.backends.cudnn.benchmark = False
    except ImportError:
        pass



def load_cfg(path: str = "env/config.yaml") -> dict:
    """Load a YAML config file and return as a dict."""
    with open(path, "r") as f:
        return yaml.safe_load(f)



def must_read_csv(p) -> pd.DataFrame:
    """Read a CSV, raising FileNotFoundError if missing."""
    p = Path(p)
    if not p.exists():
        raise FileNotFoundError(f"Required file not found: {p}")
    return pd.read_csv(p)


def save_df(df: pd.DataFrame, p) -> None:
    """Save a DataFrame to CSV, creating parent directories as needed."""
    p = Path(p)
    p.parent.mkdir(parents=True, exist_ok=True)
    df.to_csv(p, index=False)


def save_json(obj: dict, p) -> None:
    """Save a dict to JSON."""
    p = Path(p)
    p.parent.mkdir(parents=True, exist_ok=True)
    with open(p, "w") as f:
        json.dump(obj, f, indent=2)