from __future__ import annotations

import os
from copy import deepcopy
from dataclasses import dataclass
from typing import Any, List

import numpy as np
import pandas as pd


@dataclass(frozen=True)
class RuntimePaths:
    current_dir: str
    project_root: str


def parse_cors_origins(raw_origins: str) -> List[str]:
    origins = [origin.strip() for origin in raw_origins.split(",") if origin.strip()]
    return origins or ["*"]


def clone_cache_payload(payload: Any) -> Any:
    if payload is None or isinstance(payload, (str, int, float, bool)):
        return payload
    if isinstance(payload, list):
        return [clone_cache_payload(item) for item in payload]
    if isinstance(payload, tuple):
        return tuple(clone_cache_payload(item) for item in payload)
    if isinstance(payload, dict):
        return {clone_cache_payload(key): clone_cache_payload(value) for key, value in payload.items()}
    if isinstance(payload, set):
        return {clone_cache_payload(item) for item in payload}
    try:
        return deepcopy(payload)
    except Exception:
        return payload


def make_json_compatible(value: Any) -> Any:
    if isinstance(value, dict):
        return {str(key): make_json_compatible(item) for key, item in value.items()}
    if isinstance(value, (list, tuple, set)):
        return [make_json_compatible(item) for item in value]
    if isinstance(value, np.ndarray):
        return [make_json_compatible(item) for item in value.tolist()]
    if isinstance(value, np.generic):
        return make_json_compatible(value.item())
    if isinstance(value, pd.Timestamp):
        return value.isoformat()
    return value


def resolve_runtime_paths(
    module_file: str,
    is_frozen: bool,
    bundle_dir: str,
) -> RuntimePaths:
    current_dir = os.path.dirname(os.path.abspath(module_file))
    if is_frozen:
        return RuntimePaths(current_dir=bundle_dir, project_root=bundle_dir)
    return RuntimePaths(
        current_dir=current_dir,
        project_root=os.path.dirname(current_dir),
    )