feat etf

labs/analysis/etf/pick_alt.py

@@ -0,0 +1,57 @@
+"""为存在价格断层的板块挑选替补：先抓日线，再做断层扫描 + 规模/成交额提示。
+
+用法： py -3.14 -B labs/analysis/etf/pick_alt.py
+"""
+
+import json
+import sys
+import urllib.request
+from pathlib import Path
+
+HERE = Path(__file__).resolve().parent
+sys.path.insert(0, str(HERE))
+try:
+    sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+except Exception:
+    pass
+
+from backtest import CACHE, DAILY_URL  # noqa: E402
+
+# 板块 -> 需要考察的替补（按规模顺序）
+ALTS = {
+    "CPO/通信": ["515050.SH", "159583.SZ", "159994.SZ", "159695.SZ"],
+    "半导体": ["159516.SZ", "588170.SH", "159995.SZ", "159558.SZ", "512480.SH"],
+}
+
+
+def fetch(code: str) -> list[dict]:
+    request = urllib.request.Request(f"{DAILY_URL}?code={code}", headers={"User-Agent": "Mozilla/5.0"})
+    with urllib.request.urlopen(request, timeout=30) as response:
+        rows = json.load(response)
+    CACHE.mkdir(parents=True, exist_ok=True)
+    (CACHE / f"{code}.json").write_text(json.dumps(rows), encoding="utf-8")
+    return sorted(rows, key=lambda r: str(r["trade_date"]))
+
+
+def gaps(rows: list[dict]) -> list[tuple[str, float]]:
+    out = []
+    for prev, cur in zip(rows, rows[1:]):
+        a, b = float(prev["close"]), float(cur["close"])
+        if a > 0 and abs(b / a - 1) * 100 > 15:
+            out.append((str(cur["trade_date"]), (b / a - 1) * 100))
+    return out
+
+
+for sector, codes in ALTS.items():
+    print(f"\n== {sector} 替补 ==")
+    for code in codes:
+        try:
+            rows = fetch(code)
+        except Exception as exc:
+            print(f"  {code}: 抓取失败 {exc}")
+            continue
+        closes = [float(r["close"]) for r in rows]
+        bad = gaps(rows)
+        flag = "OK" if not bad else f"断层 {len(bad)} 处(最大 {max(abs(g[1]) for g in bad):.1f}%)"
+        print(f"  {code:11} 根数={len(rows):4} 最新={closes[-1]:7.3f} "
+              f"区间={min(closes):6.3f}~{max(closes):6.3f} {flag}")