feat: phase 1 — data downloader, backtrader runner, SMA strategy

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-07 09:21:16 +08:00
parent 338c912029
commit fd86190e9a
19 changed files with 456 additions and 0 deletions
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+from dataclasses import dataclass, field
+from datetime import date
+from typing import Optional
+import pandas as pd
+
+
+@dataclass
+class DailyBar:
+    """Single daily bar for one stock."""
+    symbol: str
+    date: date
+    open: float
+    high: float
+    low: float
+    close: float
+    volume: float
+    amount: float  # turnover in yuan
+
+    @classmethod
+    def from_dataframe(cls, df: pd.DataFrame, symbol_col: str = "symbol") -> list["DailyBar"]:
+        """Convert akshare/baostock DataFrame to list of DailyBar."""
+        bars = []
+        for _, row in df.iterrows():
+            bars.append(cls(
+                symbol=row.get(symbol_col, ""),
+                date=pd.Timestamp(row["date"]).date(),
+                open=float(row["open"]),
+                high=float(row["high"]),
+                low=float(row["low"]),
+                close=float(row["close"]),
+                volume=float(row["volume"]),
+                amount=float(row.get("amount", 0)),
+            ))
+        return bars
+
+    def to_series(self) -> dict:
+        return {
+            "date": self.date,
+            "open": self.open,
+            "high": self.high,
+            "low": self.low,
+            "close": self.close,
+            "volume": self.volume,
+        }