dekun
132 lines
4.2 KiB
Python
132 lines
4.2 KiB
Python
"""三日数据统计：连续三日 Top30 且 |涨跌|>=5%。"""
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from typing import Any
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from .config import settings
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from .db import get_latest_snapshot
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def _items_by_symbol(items: list[dict]) -> dict[str, dict]:
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return {x["symbol"]: x for x in items if x.get("symbol")}
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def compute_three_day_stats() -> dict[str, Any]:
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today_snap = get_latest_snapshot("today")
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yesterday_snap = get_latest_snapshot("yesterday")
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daybefore_snap = get_latest_snapshot("daybefore")
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threshold = settings.change_threshold
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top_n = settings.top_n
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missing = []
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if not today_snap:
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missing.append("今日")
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if not yesterday_snap:
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missing.append("昨日")
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if not daybefore_snap:
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missing.append("前日")
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if missing:
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return {
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"ok": False,
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"missing_periods": missing,
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"message": f"缺少快照：{', '.join(missing)}，请等待刷新或手动触发",
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"criteria": _criteria_text(threshold, top_n),
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"count": 0,
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"items": [],
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"periods": _period_meta(today_snap, yesterday_snap, daybefore_snap),
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}
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today_map = _items_by_symbol(today_snap["items"])
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yesterday_map = _items_by_symbol(yesterday_snap["items"])
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daybefore_map = _items_by_symbol(daybefore_snap["items"])
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symbols = set(today_map) & set(yesterday_map) & set(daybefore_map)
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qualified: list[dict] = []
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for sym in sorted(symbols):
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t, y, b = today_map[sym], yesterday_map[sym], daybefore_map[sym]
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if not (
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abs(t.get("price_change_pct", 0)) >= threshold
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and abs(y.get("price_change_pct", 0)) >= threshold
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and abs(b.get("price_change_pct", 0)) >= threshold
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):
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continue
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qualified.append(
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{
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"symbol": sym,
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"today": _pick_fields(t),
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"yesterday": _pick_fields(y),
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"daybefore": _pick_fields(b),
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"avg_change_pct": round(
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(
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t.get("price_change_pct", 0)
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+ y.get("price_change_pct", 0)
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+ b.get("price_change_pct", 0)
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)
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/ 3,
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4,
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),
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"total_quote_volume": (
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(t.get("quote_volume") or 0)
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+ (y.get("quote_volume") or 0)
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+ (b.get("quote_volume") or 0)
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),
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}
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)
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qualified.sort(key=lambda x: x["total_quote_volume"], reverse=True)
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return {
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"ok": True,
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"criteria": _criteria_text(threshold, top_n),
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"count": len(qualified),
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"items": qualified,
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"periods": _period_meta(today_snap, yesterday_snap, daybefore_snap),
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"summary": {
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"today_top30": len(today_map),
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"yesterday_top30": len(yesterday_map),
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"daybefore_top30": len(daybefore_map),
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"intersection": len(symbols),
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},
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}
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def _criteria_text(threshold: float, top_n: int) -> str:
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return (
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f"连续三日成交额 Top{top_n} 且每日 |涨跌幅| ≥ {threshold:g}%"
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f"（今日/昨日/前日三个完整切日周期）"
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)
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def _pick_fields(row: dict) -> dict:
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return {
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"rank": row.get("rank"),
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"quote_volume": row.get("quote_volume"),
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"quote_volume_fmt": row.get("quote_volume_fmt"),
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"price_change_pct": row.get("price_change_pct"),
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"price_change_pct_fmt": row.get("price_change_pct_fmt"),
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"funding_rate_fmt": row.get("funding_rate_fmt"),
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"is_high_volume": row.get("is_high_volume"),
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"is_high_change": row.get("is_high_change"),
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}
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def _period_meta(today, yesterday, daybefore) -> dict:
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def one(snap, label):
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if not snap:
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return {"label": label, "ready": False}
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return {
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"label": label,
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"ready": True,
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"period_start": snap["period_start"],
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"period_end": snap["period_end"],
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"updated_at": snap.get("created_at"),
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}
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return {
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"today": one(today, "今日"),
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"yesterday": one(yesterday, "昨日"),
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"daybefore": one(daybefore, "前日"),
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}
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