qlib/scripts/data_collector/baostock_5min

Collector Data

Get Qlib data(bin file)

• get data: python scripts/get_data.py qlib_data
• parameters:
  • target_dir: save dir, by default ~/.qlib/qlib_data/cn_data_5min
  • version: dataset version, value from [v2], by default v2
    • v2 end date is 2022-12
  • interval: 5min
  • region: hs300
  • delete_old: delete existing data from target_dir(features, calendars, instruments, dataset_cache, features_cache), value from [True, False], by default True
  • exists_skip: traget_dir data already exists, skip get_data, value from [True, False], by default False
• examples:

  # hs300 5min
  python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/hs300_data_5min --region hs300 --interval 5min
  

Collector Baostock high frequency data to qlib

collector Baostock high frequency data and dump into qlib format. If the above ready-made data can't meet users' requirements, users can follow this section to crawl the latest data and convert it to qlib-data.

1. download data to csv: python scripts/data_collector/baostock_5min/collector.py download_data

   This will download the raw data such as date, symbol, open, high, low, close, volume, amount, adjustflag from baostock to a local directory. One file per symbol.

   • parameters:
     • source_dir: save the directory
     • interval: 5min
     • region: HS300
     • start: start datetime, by default None
     • end: end datetime, by default None
   • examples:

     # cn 5min data
     python collector.py download_data --source_dir ~/.qlib/stock_data/source/hs300_5min_original --start 2022-01-01 --end 2022-01-30 --interval 5min --region HS300
     

2. normalize data: python scripts/data_collector/baostock_5min/collector.py normalize_data

   This will:

   1. Normalize high, low, close, open price using adjclose.
   2. Normalize the high, low, close, open price so that the first valid trading date's close price is 1.
   • parameters:
     • source_dir: csv directory
     • normalize_dir: result directory
     • interval: 5min

       if interval == 5min, qlib_data_1d_dir cannot be None

     • region: HS300
     • date_field_name: column name identifying time in csv files, by default date
     • symbol_field_name: column name identifying symbol in csv files, by default symbol
     • end_date: if not None, normalize the last date saved (including end_date); if None, it will ignore this parameter; by default None
     • qlib_data_1d_dir: qlib directory(1d data) if interval==5min, qlib_data_1d_dir cannot be None, normalize 5min needs to use 1d data;

           # qlib_data_1d can be obtained like this:
           python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --interval 1d --region cn --version v3
       

   • examples:

     # normalize 5min cn
     python collector.py normalize_data --qlib_data_1d_dir ~/.qlib/qlib_data/cn_data --source_dir ~/.qlib/stock_data/source/hs300_5min_original --normalize_dir ~/.qlib/stock_data/source/hs300_5min_nor --region HS300 --interval 5min
     

3. dump data: python scripts/dump_bin.py dump_all

   This will convert the normalized csv in feature directory as numpy array and store the normalized data one file per column and one symbol per directory.

   • parameters:
     • data_path: stock data path or directory, normalize result(normalize_dir)
     • qlib_dir: qlib(dump) data director
     • freq: transaction frequency, by default day

       freq_map = {1d:day, 5mih: 5min}

     • max_workers: number of threads, by default 16
     • include_fields: dump fields, by default ""
     • exclude_fields: fields not dumped, by default `"""

       dump_fields = include_fields if include_fields else set(symbol_df.columns) - set(exclude_fields) exclude_fields else symbol_df.columns

     • symbol_field_name: column name identifying symbol in csv files, by default symbol
     • date_field_name: column name identifying time in csv files, by default date
     • file_suffix: stock data file format, by default ".csv"
   • examples:

     # dump 5min cn
     python dump_bin.py dump_all --data_path ~/.qlib/stock_data/source/hs300_5min_nor --qlib_dir ~/.qlib/qlib_data/hs300_5min_bin --freq 5min --exclude_fields date,symbol