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* add period ops class * black format * add pit data read * fix bug in period ops * update ops runnable * update PIT test example * black format * update PIT test * update tets_PIT * update code format * add check_feature_exist * black format * optimize the PIT Algorithm * fix bug * update example * update test_PIT name * add pit collector * black format * fix bugs * fix try * fix bug & add dump_pit.py * Successfully run and understand PIT * Add some docs and remove a bug * mv crypto collector * black format * Run succesfully after merging master * Pass test and fix code * remove useless PIT code * fix PYlint * Rename Co-authored-by: Young <afe.young@gmail.com>
36 lines
1.2 KiB
Markdown
36 lines
1.2 KiB
Markdown
# Collect Point-in-Time Data
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> *Please pay **ATTENTION** that the data is collected from [baostock](http://baostock.com) and the data might not be perfect. We recommend users to prepare their own data if they have high-quality dataset. For more information, users can refer to the [related document](https://qlib.readthedocs.io/en/latest/component/data.html#converting-csv-format-into-qlib-format)*
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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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### Download Quarterly CN Data
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```bash
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cd qlib/scripts/data_collector/pit/
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# download from baostock.com
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python collector.py download_data --source_dir ./csv_pit --start 2000-01-01 --end 2020-01-01 --interval quarterly
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```
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Downloading all data from the stock is very time consuming. If you just want run a quick test on a few stocks, you can run the command below
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``` bash
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python collector.py download_data --source_dir ./csv_pit --start 2000-01-01 --end 2020-01-01 --interval quarterly --symbol_flt_regx "^(600519|000725).*"
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```
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### Dump Data into PIT Format
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```bash
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cd qlib/scripts
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# data_collector/pit/csv_pit is the data you download just now.
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python dump_pit.py dump --csv_path data_collector/pit/csv_pit --qlib_dir ~/.qlib/qlib_data/cn_data --interval quarterly
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```
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