diff --git a/qlib/data/data.py b/qlib/data/data.py index cea2f42ebd..c2638e2344 100644 --- a/qlib/data/data.py +++ b/qlib/data/data.py @@ -522,6 +522,9 @@ def load_calendar(self, freq, future): # if future calendar not exists, return current calendar if not os.path.exists(fname): get_module_logger("data").warning(f"{freq}_future.txt not exists, return current calendar!") + get_module_logger("data").warning( + "You can get future calendar by referring to the following document: https://github.com/microsoft/qlib/blob/main/scripts/data_collector/contrib/README.md" + ) fname = self._uri_cal.format(freq) else: fname = self._uri_cal.format(freq) diff --git a/scripts/data_collector/contrib/README.md b/scripts/data_collector/contrib/README.md new file mode 100644 index 0000000000..011ff56e6f --- /dev/null +++ b/scripts/data_collector/contrib/README.md @@ -0,0 +1,24 @@ +# Get future trading days + +> `D.calendar(future=True)` will be used + +## Requirements + +```bash +pip install -r requirements.txt +``` + +## Collector Data + +```bash +# parse instruments, using in qlib/instruments. +python future_trading_date_collector.py --qlib_dir ~/.qlib/qlib_data/cn_data --freq day +``` + +## Parameters + +- qlib_dir: qlib data directory +- freq: value from [`day`, `1min`], default `day` + + + diff --git a/scripts/data_collector/contrib/future_trading_date_collector.py b/scripts/data_collector/contrib/future_trading_date_collector.py new file mode 100644 index 0000000000..4da62d4654 --- /dev/null +++ b/scripts/data_collector/contrib/future_trading_date_collector.py @@ -0,0 +1,87 @@ +# Copyright (c) Microsoft Corporation. +# Licensed under the MIT License. + +import sys +from typing import List +from pathlib import Path + +import fire +import numpy as np +import pandas as pd +from loguru import logger + +# get data from baostock +import baostock as bs + +CUR_DIR = Path(__file__).resolve().parent +sys.path.append(str(CUR_DIR.parent.parent)) + + +from data_collector.utils import generate_minutes_calendar_from_daily + + +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) + + +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")) + + np.savetxt(calendar_path, date_list, fmt="%s", encoding="utf-8") + logger.info(f"write future calendars success: {calendar_path}") + + +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}") + + +def future_calendar_collector(qlib_dir: [str, Path], freq: str = "day"): + """get future calendar + + 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)) + + 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") + + +if __name__ == "__main__": + fire.Fire(future_calendar_collector) diff --git a/scripts/data_collector/contrib/requirements.txt b/scripts/data_collector/contrib/requirements.txt new file mode 100644 index 0000000000..92dcb23749 --- /dev/null +++ b/scripts/data_collector/contrib/requirements.txt @@ -0,0 +1,5 @@ +baostock +fire +numpy +pandas +loguru diff --git a/scripts/data_collector/utils.py b/scripts/data_collector/utils.py index e8c9b9dc4b..3f45396128 100644 --- a/scripts/data_collector/utils.py +++ b/scripts/data_collector/utils.py @@ -10,7 +10,9 @@ import requests import functools from pathlib import Path +from typing import Iterable, Tuple +import numpy as np import pandas as pd from lxml import etree from loguru import logger @@ -418,5 +420,40 @@ def get_trading_date_by_shift(trading_list: list, trading_date: pd.Timestamp, sh return res +def generate_minutes_calendar_from_daily( + calendars: Iterable, + freq: str = "1min", + am_range: Tuple[str, str] = ("09:30:00", "11:29:00"), + pm_range: Tuple[str, str] = ("13:00:00", "14:59:00"), +) -> pd.Index: + """generate minutes calendar + + Parameters + ---------- + calendars: Iterable + daily calendar + freq: str + by default 1min + am_range: Tuple[str, str] + AM Time Range, by default China-Stock: ("09:30:00", "11:29:00") + pm_range: Tuple[str, str] + PM Time Range, by default China-Stock: ("13:00:00", "14:59:00") + + """ + daily_format: str = "%Y-%m-%d" + res = [] + for _day in calendars: + for _range in [am_range, pm_range]: + res.append( + pd.date_range( + f"{pd.Timestamp(_day).strftime(daily_format)} {_range[0]}", + f"{pd.Timestamp(_day).strftime(daily_format)} {_range[1]}", + freq=freq, + ) + ) + + return pd.Index(sorted(set(np.hstack(res)))) + + if __name__ == "__main__": assert len(get_hs_stock_symbols()) >= MINIMUM_SYMBOLS_NUM diff --git a/scripts/data_collector/yahoo/collector.py b/scripts/data_collector/yahoo/collector.py index f0e110694c..a6e06613ed 100644 --- a/scripts/data_collector/yahoo/collector.py +++ b/scripts/data_collector/yahoo/collector.py @@ -24,7 +24,12 @@ CUR_DIR = Path(__file__).resolve().parent sys.path.append(str(CUR_DIR.parent.parent)) from data_collector.base import BaseCollector, BaseNormalize, BaseRun -from data_collector.utils import get_calendar_list, get_hs_stock_symbols, get_us_stock_symbols +from data_collector.utils import ( + get_calendar_list, + get_hs_stock_symbols, + get_us_stock_symbols, + generate_minutes_calendar_from_daily, +) INDEX_BENCH_URL = "http://push2his.eastmoney.com/api/qt/stock/kline/get?secid=1.{index_code}&fields1=f1%2Cf2%2Cf3%2Cf4%2Cf5&fields2=f51%2Cf52%2Cf53%2Cf54%2Cf55%2Cf56%2Cf57%2Cf58&klt=101&fqt=0&beg={begin}&end={end}" @@ -418,21 +423,9 @@ def calendar_list_1d(self): return calendar_list_1d def generate_1min_from_daily(self, calendars: Iterable) -> pd.Index: - res = [] - daily_format = self.DAILY_FORMAT - am_range = self.AM_RANGE - pm_range = self.PM_RANGE - for _day in calendars: - for _range in [am_range, pm_range]: - res.append( - pd.date_range( - f"{_day.strftime(daily_format)} {_range[0]}", - f"{_day.strftime(daily_format)} {_range[1]}", - freq="1min", - ) - ) - - return pd.Index(sorted(set(np.hstack(res)))) + return generate_minutes_calendar_from_daily( + calendars, freq="1min", am_range=self.AM_RANGE, pm_range=self.PM_RANGE + ) def adjusted_price(self, df: pd.DataFrame) -> pd.DataFrame: # TODO: using daily data factor