Initial commit: Mad Turtle v2.0 ML EA for XAUUSD H1 with Python inference server and MQL5 EA

python/ml_pipeline/fetch_xauusd.py

@@ -0,0 +1,52 @@
+"""
+Fetch real XAUUSD H1 data from Yahoo Finance (GC=F gold futures).
+Saves to CSV for training pipeline.
+"""
+
+import argparse
+from datetime import datetime, timezone
+from pathlib import Path
+
+import pandas as pd
+import yfinance as yf
+
+ROOT = Path(__file__).resolve().parent.parent
+DATA_DIR = ROOT / "data"
+DATA_DIR.mkdir(exist_ok=True)
+OUT_CSV = DATA_DIR / "xauusd_h1.csv"
+
+
+def fetch_xauusd(period: str = "2y", interval: str = "1h") -> pd.DataFrame:
+    ticker = yf.Ticker("GC=F")
+    df = ticker.history(period=period, interval=interval, auto_adjust=True)
+    if df.empty:
+        raise RuntimeError("No data returned from Yahoo Finance for GC=F")
+    df.index = df.index.tz_convert("UTC").tz_localize(None)
+    df.index.name = "datetime"
+    df.reset_index(inplace=True)
+    df.rename(columns={
+        "Open": "open", "High": "high", "Low": "low",
+        "Close": "close", "Volume": "volume"
+    }, inplace=True)
+    df = df[["datetime", "open", "high", "low", "close", "volume"]].copy()
+    df.dropna(subset=["open", "high", "low", "close"], inplace=True)
+    df["volume"] = df["volume"].fillna(0)
+    return df
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--period", default="2y", help="yfinance period (1y, 2y, max)")
+    parser.add_argument("--interval", default="1h", help="yfinance interval (1h, 4h, 1d)")
+    parser.add_argument("--out", default=str(OUT_CSV))
+    args = parser.parse_args()
+
+    print(f"Fetching XAUUSD (GC=F) {args.interval} for {args.period}...")
+    df = fetch_xauusd(args.period, args.interval)
+    df.to_csv(args.out, index=False)
+    print(f"Saved {len(df)} rows -> {args.out}")
+    print(df.tail(3).to_string(index=False))
+
+
+if __name__ == "__main__":
+    main()