add_baostock_collector

.github/workflows/test_qlib_from_source.yml

@@ -102,6 +102,7 @@ jobs:
     - name: Check Qlib with pylint
       run: |
         pylint --disable=C0104,C0114,C0115,C0116,C0301,C0302,C0411,C0413,C1802,R0401,R0801,R0902,R0903,R0911,R0912,R0913,R0914,R0915,R1720,W0105,W0123,W0201,W0511,W0613,W1113,W1514,E0401,E1121,C0103,C0209,R0402,R1705,R1710,R1725,R1735,W0102,W0212,W0221,W0223,W0231,W0237,W0612,W0621,W0622,W0703,W1309,E1102,E1136 --const-rgx='[a-z_][a-z0-9_]{2,30}$' qlib --init-hook "import astroid; astroid.context.InferenceContext.max_inferred = 500; import sys; sys.setrecursionlimit(2000)"
+        pylint --disable=C0104,C0114,C0115,C0116,C0301,C0302,C0411,C0413,C1802,R0401,R0801,R0902,R0903,R0911,R0912,R0913,R0914,R0915,R1720,W0105,W0123,W0201,W0511,W0613,W1113,W1514,E0401,E1121,C0103,C0209,R0402,R1705,R1710,R1725,R1735,W0102,W0212,W0221,W0223,W0231,W0237,W0246,W0612,W0621,W0622,W0703,W1309,E1102,E1136 --const-rgx='[a-z_][a-z0-9_]{2,30}$' scripts --init-hook "import astroid; astroid.context.InferenceContext.max_inferred = 500; import sys; sys.setrecursionlimit(2000)"
 
     # The following flake8 error codes were ignored:
       # E501 line too long

scripts/data_collector/baostock_5min/README.md

@@ -0,0 +1,81 @@
+## 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:
+    ```bash
+    # 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:
+          ```bash
+          # 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:
+        ```bash
+        # 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:
+       - `csv_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`
+     - examples:
+       ```bash
+       # dump 5min cn
+       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
+       ```