mirror of
https://ghfast.top/https://github.com/aeroxw/easy_tdx_max.git
synced 2026-09-12 15:44:18 +08:00
Justin Gu
02701952ca
- K-line: daily+ periods output 'date' only, minute periods output 'datetime' - Transactions (tick-by-tick): combine date param + hour/minute into 'datetime' - XdxrRecord, HistoricalFundFlow: year/month/day merged to 'date' - MinuteBar: rename unknown_1 to _unknown_1 (hidden from DataFrame) - MinuteBar: add datetime column computed from bar index (A-share 240-bar pattern) - get_minute_time_data: use history endpoint only (current-day endpoint broken in pytdx too) - Update all examples to reflect new DataFrame column names
112 lines
3.8 KiB
Python
112 lines
3.8 KiB
Python
"""Dataclass → DataFrame 转换工具。"""
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from __future__ import annotations
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from dataclasses import asdict, is_dataclass
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from typing import Any
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import pandas as pd
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def _to_df(data: Any) -> pd.DataFrame:
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"""将 list[dataclass] 或单个 dataclass 转为 DataFrame。
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自动丢弃以 ``_`` 开头的内部字段（如 ``_raw``）。
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仅处理 year/month/day（无 hour/minute）→ date 的合并；
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SecurityBar 的完整 datetime 合并由调用方按周期决定。
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"""
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if isinstance(data, list):
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if not data:
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return pd.DataFrame()
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rows = []
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for item in data:
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d = _clean_dict(item)
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rows.append(d)
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return pd.DataFrame(rows)
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if is_dataclass(data) and not isinstance(data, type):
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return pd.DataFrame([_clean_dict(data)])
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raise TypeError(f"不支持转换为 DataFrame 的类型: {type(data)}")
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def _clean_dict(item: Any) -> dict[str, Any]:
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d = asdict(item)
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d = {k: v for k, v in d.items() if not k.startswith("_")}
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return _merge_datetime_fields(d)
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def _merge_datetime_fields(d: dict[str, Any]) -> dict[str, Any]:
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"""将仅含 year/month/day（无 hour/minute）的模型合并为 date 列。"""
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if all(k in d for k in ("year", "month", "day")) and not all(
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k in d for k in ("hour", "minute")
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):
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dt = pd.Timestamp(year=d["year"], month=d["month"], day=d["day"])
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result: dict[str, Any] = {"date": dt}
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result.update({k: v for k, v in d.items() if k not in {"year", "month", "day"}})
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return result
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return d
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def _merge_bar_datetime(df: pd.DataFrame, daily_plus: bool) -> pd.DataFrame:
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"""根据 K 线周期将 SecurityBar 的分散字段合并为 date 或 datetime。
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Args:
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daily_plus: True 表示日线及以上周期（DAY/WEEK/MONTH/YEAR），只保留 date；
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False 表示分钟线（MIN_1/5/15/30/60），保留完整 datetime。
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"""
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if df.empty or "year" not in df.columns:
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return df
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date_str = (
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df["year"].astype(str)
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+ "-"
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+ df["month"].astype(str).str.zfill(2)
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+ "-"
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+ df["day"].astype(str).str.zfill(2)
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)
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if daily_plus:
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df.insert(0, "date", pd.to_datetime(date_str))
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else:
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full_str = (
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date_str
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+ " "
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+ df["hour"].astype(str).str.zfill(2)
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+ ":"
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+ df["minute"].astype(str).str.zfill(2)
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)
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df.insert(0, "datetime", pd.to_datetime(full_str))
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df.drop(columns=["year", "month", "day", "hour", "minute"], inplace=True)
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return df
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def _merge_txn_datetime(df: pd.DataFrame, date_int: int) -> pd.DataFrame:
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"""将逐笔成交的 date + hour:minute 合并为 datetime 列。"""
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if df.empty or "hour" not in df.columns:
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return df
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year = date_int // 10000
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month = (date_int // 100) % 100
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day = date_int % 100
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base = pd.Timestamp(year=year, month=month, day=day)
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offsets = pd.to_timedelta(df["hour"] * 3600 + df["minute"] * 60, unit="s")
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df.insert(0, "datetime", base + offsets)
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df.drop(columns=["hour", "minute"], inplace=True)
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return df
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def _add_minute_datetime(df: pd.DataFrame, date_int: int) -> pd.DataFrame:
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"""为分时 DataFrame 添加 datetime 列（从 bar 索引计算时间）。
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A 股分时 240 条：0-119 = 9:30~11:29（上午），120-239 = 13:00~14:59（下午）。
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"""
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if df.empty:
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return df
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year = date_int // 10000
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month = (date_int // 100) % 100
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day = date_int % 100
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base = pd.Timestamp(year=year, month=month, day=day)
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n = len(df)
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morning = list(range(9 * 60 + 30, 9 * 60 + 30 + 120))
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afternoon = list(range(13 * 60, 13 * 60 + 120))
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all_minutes = (morning + afternoon)[:n]
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offsets = pd.to_timedelta(all_minutes, unit="m")
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df.insert(0, "datetime", base + offsets)
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return df
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