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* add_baostock_collector * modify_comments * fix_pylint_error * solve_duplication_methods * modified the logic of update_data_to_bin * modified the logic of update_data_to_bin * optimize code * optimize pylint issue * fix pylint error * changes suggested by the review * fix CI faild * fix CI faild * fix issue 1121 * format with black * optimize code logic * optimize code logic * fix error code * drop warning during code runs * optimize code * format with black * fix bug * format with black * optimize code * optimize code * add comments
81 lines
4.5 KiB
Markdown
81 lines
4.5 KiB
Markdown
## Collector Data
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### Get Qlib data(`bin file`)
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- get data: `python scripts/get_data.py qlib_data`
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- parameters:
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- `target_dir`: save dir, by default *~/.qlib/qlib_data/cn_data_5min*
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- `version`: dataset version, value from [`v2`], by default `v2`
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- `v2` end date is *2022-12*
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- `interval`: `5min`
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- `region`: `hs300`
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- `delete_old`: delete existing data from `target_dir`(*features, calendars, instruments, dataset_cache, features_cache*), value from [`True`, `False`], by default `True`
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- `exists_skip`: traget_dir data already exists, skip `get_data`, value from [`True`, `False`], by default `False`
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- examples:
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```bash
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# hs300 5min
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python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/hs300_data_5min --region hs300 --interval 5min
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```
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### Collector *Baostock high frequency* data to qlib
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> collector *Baostock high frequency* data and *dump* into `qlib` format.
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> 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.
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1. download data to csv: `python scripts/data_collector/baostock_5min/collector.py download_data`
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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.
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- parameters:
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- `source_dir`: save the directory
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- `interval`: `5min`
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- `region`: `HS300`
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- `start`: start datetime, by default *None*
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- `end`: end datetime, by default *None*
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- examples:
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```bash
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# cn 5min data
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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
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```
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2. normalize data: `python scripts/data_collector/baostock_5min/collector.py normalize_data`
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This will:
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1. Normalize high, low, close, open price using adjclose.
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2. Normalize the high, low, close, open price so that the first valid trading date's close price is 1.
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- parameters:
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- `source_dir`: csv directory
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- `normalize_dir`: result directory
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- `interval`: `5min`
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> if **`interval == 5min`**, `qlib_data_1d_dir` cannot be `None`
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- `region`: `HS300`
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- `date_field_name`: column *name* identifying time in csv files, by default `date`
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- `symbol_field_name`: column *name* identifying symbol in csv files, by default `symbol`
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- `end_date`: if not `None`, normalize the last date saved (*including end_date*); if `None`, it will ignore this parameter; by default `None`
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- `qlib_data_1d_dir`: qlib directory(1d data)
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if interval==5min, qlib_data_1d_dir cannot be None, normalize 5min needs to use 1d data;
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```
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# qlib_data_1d can be obtained like this:
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python scripts/get_data.py qlib_data --target_dir ~/.qlib/qlib_data/cn_data --interval 1d --region cn --version v3
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```
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- examples:
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```bash
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# normalize 5min cn
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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
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```
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3. dump data: `python scripts/dump_bin.py dump_all`
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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.
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- parameters:
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- `csv_path`: stock data path or directory, **normalize result(normalize_dir)**
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- `qlib_dir`: qlib(dump) data director
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- `freq`: transaction frequency, by default `day`
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> `freq_map = {1d:day, 5mih: 5min}`
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- `max_workers`: number of threads, by default *16*
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- `include_fields`: dump fields, by default `""`
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- `exclude_fields`: fields not dumped, by default `"""
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> dump_fields = `include_fields if include_fields else set(symbol_df.columns) - set(exclude_fields) exclude_fields else symbol_df.columns`
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- `symbol_field_name`: column *name* identifying symbol in csv files, by default `symbol`
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- `date_field_name`: column *name* identifying time in csv files, by default `date`
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- examples:
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```bash
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# dump 5min cn
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python dump_bin.py dump_all --csv_path ~/.qlib/stock_data/source/hs300_5min_nor --qlib_dir ~/.qlib/qlib_data/hs300_5min_bin --freq 5min --exclude_fields date,symbol
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``` |