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Add future trading date collector
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scripts/data_collector/contrib/README.md
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scripts/data_collector/contrib/README.md
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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
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pip install -r requirements.txt
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```
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## Collector Data
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```bash
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# parse instruments, using in qlib/instruments.
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python future_trading_date_collector.py --qlib_dir ~/.qlib/qlib_data/cn_data --freq day
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```
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## Parameters
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- qlib_dir: qlib data directory
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- freq: value from [`day`, `1min`], default `day`
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT License.
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import sys
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from typing import List
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from pathlib import Path
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import fire
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import numpy as np
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import pandas as pd
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from loguru import logger
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# get data from baostock
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import baostock as bs
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CUR_DIR = Path(__file__).resolve().parent
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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:
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calendar_path = qlib_dir.joinpath("calendars").joinpath("day.txt")
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if not calendar_path.exists():
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return pd.DataFrame()
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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"):
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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")
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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]:
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print(freq)
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if freq == "day":
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return date_list
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elif freq == "1min":
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date_list = generate_minutes_calendar_from_daily(date_list, freq=freq).tolist()
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return list(map(lambda x: pd.Timestamp(x).strftime("%Y-%m-%d %H:%M:%S"), date_list))
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else:
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raise ValueError(f"Unsupported freq: {freq}")
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def future_calendar_collector(qlib_dir: [str, Path], freq: str = "day"):
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"""get future calendar
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Parameters
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----------
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qlib_dir: str or Path
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qlib data directory
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freq: str
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value from ["day", "1min"], by default day
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"""
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qlib_dir = Path(qlib_dir).expanduser().resolve()
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if not qlib_dir.exists():
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raise FileNotFoundError(str(qlib_dir))
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lg = bs.login()
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if lg.error_code != "0":
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logger.error(f"login error: {lg.error_msg}")
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return
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# read daily calendar
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daily_calendar = read_calendar_from_qlib(qlib_dir)
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end_year = pd.Timestamp.now().year
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if daily_calendar.empty:
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start_year = pd.Timestamp.now().year
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else:
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start_year = pd.Timestamp(daily_calendar.iloc[-1, 0]).year
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rs = bs.query_trade_dates(start_date=pd.Timestamp(f"{start_year}-01-01"), end_date=f"{end_year}-12-31")
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data_list = []
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while (rs.error_code == "0") & rs.next():
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_row_data = rs.get_row_data()
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if int(_row_data[1]) == 1:
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data_list.append(_row_data[0])
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data_list = sorted(data_list)
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date_list = generate_qlib_calendar(data_list, freq=freq)
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write_calendar_to_qlib(qlib_dir, date_list, freq=freq)
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bs.logout()
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logger.info(f"get trading dates success: {start_year}-01-01 to {end_year}-12-31")
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if __name__ == "__main__":
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fire.Fire(future_calendar_collector)
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5
scripts/data_collector/contrib/requirements.txt
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scripts/data_collector/contrib/requirements.txt
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baostock
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fire
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numpy
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pandas
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loguru
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