#!/usr/bin/env python3
"""Fetch BTC/USDT OHLCV data from Binance using ccxt."""

import os
import sys
import time
import ccxt
import pandas as pd
from datetime import datetime, timezone

DATA_DIR = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), "data")
SYMBOL = "BTC/USDT"
EXCHANGE_ID = "binance"
YEARS_HISTORY = 2
LIMIT_PER_REQUEST = 1000  # Binance max


def fetch_ohlcv(timeframe: str) -> pd.DataFrame:
    """Fetch OHLCV data for a given timeframe."""
    exchange = ccxt.binance({"enableRateLimit": True})

    # Calculate start time
    now_ms = int(time.time() * 1000)
    if timeframe == "1h":
        ms_per_candle = 3600 * 1000
    elif timeframe == "4h":
        ms_per_candle = 4 * 3600 * 1000
    else:
        raise ValueError(f"Unsupported timeframe: {timeframe}")

    since = now_ms - (YEARS_HISTORY * 365 * 24 * 3600 * 1000)

    all_candles = []
    print(f"  Fetching {SYMBOL} {timeframe} from {datetime.fromtimestamp(since / 1000, tz=timezone.utc).strftime('%Y-%m-%d')}...")

    while since < now_ms:
        try:
            candles = exchange.fetch_ohlcv(SYMBOL, timeframe, since=since, limit=LIMIT_PER_REQUEST)
        except Exception as e:
            print(f"  Warning: fetch error, retrying in 5s — {e}")
            time.sleep(5)
            continue

        if not candles:
            break

        all_candles.extend(candles)
        since = candles[-1][0] + ms_per_candle
        sys.stdout.write(f"\r  Downloaded {len(all_candles)} candles...")
        sys.stdout.flush()
        time.sleep(exchange.rateLimit / 1000)

    print(f"\r  Downloaded {len(all_candles)} candles total.")

    df = pd.DataFrame(all_candles, columns=["timestamp", "open", "high", "low", "close", "volume"])
    df["timestamp"] = pd.to_datetime(df["timestamp"], unit="ms", utc=True)
    df = df.drop_duplicates(subset=["timestamp"]).sort_values("timestamp").reset_index(drop=True)
    return df


def main():
    os.makedirs(DATA_DIR, exist_ok=True)

    for tf in ["1h", "4h"]:
        print(f"\n[*] Fetching {tf} data...")
        df = fetch_ohlcv(tf)
        out_path = os.path.join(DATA_DIR, f"btc_{tf}.csv")
        df.to_csv(out_path, index=False)
        print(f"  Saved {len(df)} rows to {out_path}")
        print(f"  Range: {df['timestamp'].iloc[0]} → {df['timestamp'].iloc[-1]}")

    print("\nData fetch complete!")


if __name__ == "__main__":
    main()