import os
import threading
from typing import List, Optional

import pandas as pd


_lock = threading.Lock()


def ensure_storage(base_dir: str):
    os.makedirs(base_dir, exist_ok=True)


def _path(base_dir: str, symbol: str, timeframe: str) -> str:
    safe_symbol = symbol.replace("/", "_").replace(":", "_")
    d = os.path.join(base_dir, timeframe)
    os.makedirs(d, exist_ok=True)
    return os.path.join(d, f"{safe_symbol}.parquet")


def read_candles(base_dir: str, symbol: str, timeframe: str, start: Optional[int], end: Optional[int]) -> pd.DataFrame:
    p = _path(base_dir, symbol, timeframe)
    if not os.path.exists(p):
        return pd.DataFrame(columns=["timestamp", "open", "high", "low", "close", "volume"])  # empty
    df = pd.read_parquet(p)
    if start is not None:
        df = df[df["timestamp"] >= int(start)]
    if end is not None:
        df = df[df["timestamp"] <= int(end)]
    df = df.sort_values("timestamp")
    return df


def upsert_candles(base_dir: str, symbol: str, timeframe: str, candles: List[List[float]]):
    p = _path(base_dir, symbol, timeframe)
    new_df = pd.DataFrame(candles, columns=["timestamp", "open", "high", "low", "close", "volume"])
    with _lock:
        if os.path.exists(p):
            old = pd.read_parquet(p)
            merged = pd.concat([old, new_df], ignore_index=True)
            merged = merged.drop_duplicates(subset=["timestamp"], keep="last").sort_values("timestamp")
        else:
            merged = new_df.sort_values("timestamp")
        merged.to_parquet(p, index=False)


def get_last_timestamp(base_dir: str, symbol: str, timeframe: str) -> Optional[int]:
    p = _path(base_dir, symbol, timeframe)
    if not os.path.exists(p):
        return None
    df = pd.read_parquet(p)
    if df.empty:
        return None
    return int(df["timestamp"].iloc[-1])