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111 lines
3.5 KiB
Python
111 lines
3.5 KiB
Python
"""历史股本解析。
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财务股本按公告日可用，历史缺失时回退 instruments 最新流通股本。
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"""
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from __future__ import annotations
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from datetime import date
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from pathlib import Path
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import polars as pl
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def load_share_history(data_dir: Path) -> pl.DataFrame:
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"""读取本地财务股本表；未同步或损坏时返回空表。"""
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path = data_dir / "financials" / "shares" / "part.parquet"
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if not path.exists():
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return pl.DataFrame()
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try:
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shares = pl.read_parquet(path)
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if not {"symbol", "period_end", "float_shares"} <= set(shares.columns):
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return pl.DataFrame()
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return shares
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except Exception:
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return pl.DataFrame()
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def apply_historical_float_shares(
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rows: pl.DataFrame,
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shares: pl.DataFrame | None,
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*,
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today: date,
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) -> pl.DataFrame:
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"""为行情行解析有效流通股本。
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当日保留 rows.float_shares；历史日期使用公告日不晚于交易日的最新股本，
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找不到历史记录时继续使用 rows.float_shares。
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"""
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required = {"symbol", "date", "float_shares"}
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if (
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rows.is_empty()
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or not required <= set(rows.columns)
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or shares is None
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or shares.is_empty()
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or not {"symbol", "period_end", "float_shares"} <= set(shares.columns)
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):
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return rows
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def as_date_expr(column: str) -> pl.Expr:
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dtype = shares.schema[column]
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if dtype == pl.Utf8:
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return pl.col(column).str.to_date(strict=False)
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return pl.col(column).cast(pl.Date, strict=False)
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available_date = as_date_expr("period_end")
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if "announce_date" in shares.columns:
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available_date = as_date_expr("announce_date").fill_null(available_date)
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history = (
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shares
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.select(
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pl.col("symbol").cast(pl.Utf8),
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available_date.alias("_share_available_date"),
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pl.col("period_end").cast(pl.Utf8).alias("_share_period_end"),
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pl.col("float_shares").cast(pl.Float64, strict=False).alias("_historical_float_shares"),
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)
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.filter(
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pl.col("symbol").is_not_null()
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& pl.col("_share_available_date").is_not_null()
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& (pl.col("_historical_float_shares") > 0)
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)
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.sort(["symbol", "_share_available_date", "_share_period_end"])
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.unique(subset=["symbol", "_share_available_date"], keep="last")
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.sort(["symbol", "_share_available_date"])
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)
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if history.is_empty():
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return rows
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resolved = (
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rows
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.with_row_index("_share_row_order")
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.with_columns(
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pl.col("symbol").cast(pl.Utf8),
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pl.col("date").cast(pl.Date, strict=False).alias("_share_trade_date"),
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)
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.sort(["symbol", "_share_trade_date"])
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.join_asof(
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history,
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left_on="_share_trade_date",
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right_on="_share_available_date",
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by="symbol",
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strategy="backward",
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check_sortedness=False,
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)
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.with_columns(
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pl.when(pl.col("_share_trade_date") == pl.lit(today))
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.then(pl.col("float_shares"))
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.otherwise(
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pl.coalesce("_historical_float_shares", "float_shares")
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)
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.alias("float_shares")
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)
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.sort("_share_row_order")
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)
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return resolved.drop(
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"_share_row_order",
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"_share_trade_date",
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"_share_available_date",
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"_share_period_end",
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"_historical_float_shares",
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)
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