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Add future trading date collector #405
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# Get future trading days | ||
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> `D.calendar(future=True)` will be used | ||
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## Requirements | ||
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```bash | ||
pip install -r requirements.txt | ||
``` | ||
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## Collector Data | ||
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```bash | ||
# parse instruments, using in qlib/instruments. | ||
python future_trading_date_collector.py --qlib_dir ~/.qlib/qlib_data/cn_data --freq day | ||
``` | ||
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## Parameters | ||
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- qlib_dir: qlib data directory | ||
- freq: value from [`day`, `1min`], default `day` | ||
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scripts/data_collector/contrib/future_trading_date_collector.py
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# Copyright (c) Microsoft Corporation. | ||
# Licensed under the MIT License. | ||
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import sys | ||
from typing import List | ||
from pathlib import Path | ||
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import fire | ||
import numpy as np | ||
import pandas as pd | ||
from loguru import logger | ||
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# get data from baostock | ||
import baostock as bs | ||
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CUR_DIR = Path(__file__).resolve().parent | ||
sys.path.append(str(CUR_DIR.parent.parent)) | ||
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from data_collector.utils import generate_minutes_calendar_from_daily | ||
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def read_calendar_from_qlib(qlib_dir: Path) -> pd.DataFrame: | ||
calendar_path = qlib_dir.joinpath("calendars").joinpath("day.txt") | ||
if not calendar_path.exists(): | ||
return pd.DataFrame() | ||
return pd.read_csv(calendar_path, header=None) | ||
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def write_calendar_to_qlib(qlib_dir: Path, date_list: List[str], freq: str = "day"): | ||
calendar_path = str(qlib_dir.joinpath("calendars").joinpath(f"{freq}_future.txt")) | ||
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np.savetxt(calendar_path, date_list, fmt="%s", encoding="utf-8") | ||
logger.info(f"write future calendars success: {calendar_path}") | ||
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def generate_qlib_calendar(date_list: List[str], freq: str) -> List[str]: | ||
print(freq) | ||
if freq == "day": | ||
return date_list | ||
elif freq == "1min": | ||
date_list = generate_minutes_calendar_from_daily(date_list, freq=freq).tolist() | ||
return list(map(lambda x: pd.Timestamp(x).strftime("%Y-%m-%d %H:%M:%S"), date_list)) | ||
else: | ||
raise ValueError(f"Unsupported freq: {freq}") | ||
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def future_calendar_collector(qlib_dir: [str, Path], freq: str = "day"): | ||
"""get future calendar | ||
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Parameters | ||
---------- | ||
qlib_dir: str or Path | ||
qlib data directory | ||
freq: str | ||
value from ["day", "1min"], by default day | ||
""" | ||
qlib_dir = Path(qlib_dir).expanduser().resolve() | ||
if not qlib_dir.exists(): | ||
raise FileNotFoundError(str(qlib_dir)) | ||
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lg = bs.login() | ||
if lg.error_code != "0": | ||
logger.error(f"login error: {lg.error_msg}") | ||
return | ||
# read daily calendar | ||
daily_calendar = read_calendar_from_qlib(qlib_dir) | ||
end_year = pd.Timestamp.now().year | ||
if daily_calendar.empty: | ||
start_year = pd.Timestamp.now().year | ||
else: | ||
start_year = pd.Timestamp(daily_calendar.iloc[-1, 0]).year | ||
rs = bs.query_trade_dates(start_date=pd.Timestamp(f"{start_year}-01-01"), end_date=f"{end_year}-12-31") | ||
data_list = [] | ||
while (rs.error_code == "0") & rs.next(): | ||
_row_data = rs.get_row_data() | ||
if int(_row_data[1]) == 1: | ||
data_list.append(_row_data[0]) | ||
data_list = sorted(data_list) | ||
date_list = generate_qlib_calendar(data_list, freq=freq) | ||
write_calendar_to_qlib(qlib_dir, date_list, freq=freq) | ||
bs.logout() | ||
logger.info(f"get trading dates success: {start_year}-01-01 to {end_year}-12-31") | ||
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if __name__ == "__main__": | ||
fire.Fire(future_calendar_collector) |
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baostock | ||
fire | ||
numpy | ||
pandas | ||
loguru |
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Will it be better to use backed storage if it is merged?