添加k线动能理论

datasvc/app/storage.py

@@ -0,0 +1,57 @@
+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])
+
+