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L2 数据加载器（基于 HF 数据集，按需下载单日文件）。
数据集: kangkangchen/a-share-l2-600809
kangkangchen/a-share-tushare-context-600809
"""
from __future__ import annotations
import os
from typing import Dict, Iterable, List
import pandas as pd
from huggingface_hub import hf_hub_download
L2_REPO = "kangkangchen/a-share-l2-600809"
TUSHARE_REPO = "kangkangchen/a-share-tushare-context-600809"
TS_CODE = "600809.SH"
# 2025-09-25: 上交所被动方 order-link 命中率异常，整日剔除
BLACKLIST_DATES = {20230102, 20250925}
L2_TABLES = ("level2_trades", "level2_orders")
def _parquet_path(table: str, date: int) -> str:
ds = str(date)
year, month = ds[:4], ds[4:6]
if table in ("level2_quotes", "level2_orders", "level2_trades"):
return f"data/{table}/year={year}/month={month}/ts_code={TS_CODE}/{ds}.parquet"
# tushare tables
if table == "moneyflow_hsgt_daily":
return f"data/{table}/year={year}/month={month}/*.parquet" # market-level, no ts_code
return f"data/{table}/year={year}/month={month}/ts_code={TS_CODE}/*.parquet"
def download_l2_table(table: str, date: int) -> str:
"""下载单日单张 L2 表，返回本地 parquet 路径（使用 HF 缓存）。"""
if date in BLACKLIST_DATES:
raise ValueError(f"date {date} is blacklisted")
path = _parquet_path(table, date)
return hf_hub_download(L2_REPO, path, repo_type="dataset")
def load_trades(date: int) -> pd.DataFrame:
"""加载单日逐笔成交。"""
p = download_l2_table("level2_trades", date)
return pd.read_parquet(p)
def load_orders(date: int) -> pd.DataFrame:
"""加载单日逐笔委托。"""
p = download_l2_table("level2_orders", date)
return pd.read_parquet(p)
def load_l2_day(date: int) -> Dict[str, pd.DataFrame]:
"""加载单日 trades + orders。"""
return {
"trades": load_trades(date),
"orders": load_orders(date),
}
def list_available_dates(
start: int = 20230101, end: int = 20260331
) -> List[int]:
"""
通过 HF API 列出可用日期。
注意：这需要一次 API 调用。在 sandbox 里可以直接扫描快照目录。
本地测试时手动指定日期范围即可。
"""
from huggingface_hub import list_repo_tree
dates = set()
for table in ("level2_quotes", "level2_orders", "level2_trades"):
tree = list_repo_tree(
L2_REPO, repo_type="dataset", recursive=True
)
for item in tree:
path = item.path
if path.endswith(".parquet") and "ts_code=600809.SH" in path:
try:
d = int(os.path.splitext(os.path.basename(path))[0])
if start <= d <= end and d not in BLACKLIST_DATES:
dates.add(d)
except ValueError:
pass
return sorted(dates)
def load_tushare_table(root: str, table: str) -> pd.DataFrame:
"""加载 tushare 单表全量。root 是 HF snapshot 本地路径。"""
import glob
if table == "moneyflow_hsgt_daily":
pattern = f"{root}/data/{table}/year=*/month=*/*.parquet"
else:
pattern = f"{root}/data/{table}/year=*/month=*/ts_code={TS_CODE}/*.parquet"
files = sorted(glob.glob(pattern))
if not files:
return pd.DataFrame()
dfs = [pd.read_parquet(f) for f in files]
df = pd.concat(dfs, ignore_index=True)
if "trade_date" in df.columns:
df = df.sort_values("trade_date").reset_index(drop=True)
return df
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