feat (hub): add style checking workflow and reformat some files

.github/workflows/ci.yml

@@ -0,0 +1,66 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - main
+      - release
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  build:
+    name: ${{ matrix.os }} x py${{ matrix.python }}
+    strategy:
+      fail-fast: false
+      matrix:
+        python: ["3.10", "3.11"]
+        os: [ubuntu-latest, windows-latest]
+        include:
+          - os: ubuntu-latest
+            install_graphviz:
+              sudo apt-get install graphviz libgraphviz-dev
+          - os: windows-latest
+            install_graphviz:
+              choco install graphviz --version=2.48.0;
+              poetry run pip install --global-option=build_ext --global-option="-IC:\Program Files\Graphviz\include" --global-option="-LC:\Program Files\Graphviz\lib" pygraphviz;
+
+    runs-on: ${{ matrix.os }}
+    steps:
+      - uses: actions/checkout@v2
+
+      - uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python }}
+
+      - name: Cache venv
+        uses: actions/cache@v2
+        with:
+          path: ~/.cache/pypoetry/virtualenvs
+          key: ${{ runner.os }}-build-${{ matrix.python }}-${{ secrets.CACHE_VERSION }}-${{ hashFiles('poetry.lock') }}
+
+      - name: Install dependencies
+        run: |
+          echo "Cache Version ${{ secrets.CACHE_VERSION }}"
+          pip install poetry
+          ${{ matrix.install_graphviz }}
+          poetry install
+          poetry run pip install ERAlchemy
+          poetry config --list
+
+      - name: Print tool versions
+        run: |
+          poetry run black --version
+
+      - name: Check if the code is formatted
+        run: poetry run black --check dbgpt_hub
+
+      # - name: Type check the project
+      #   run: poetry run pyright dbgpt_hub || true
+
+      # - name: Style check the project
+      #   run: poetry run pylint dbgpt_hub || true
+
+      - name: Build binary dependencies
+        run: poetry build

.github/workflows/release.yml

@@ -0,0 +1,56 @@
+name: release
+
+on:
+  push:
+    branches:
+      - release
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v2
+        with:
+          fetch-depth: "0"
+
+      - uses: actions/setup-python@v1
+        with:
+          python-version: ${{ matrix.python }}
+
+      - name: Cache venv
+        uses: actions/cache@v2
+        with:
+          path: ~/.cache/pypoetry/virtualenvs
+          key: ${{ runner.os }}-build-${{ matrix.python }}-${{ secrets.CACHE_VERSION }}-${{ hashFiles('poetry.lock') }}
+
+      - name: Install dependencies
+        run: |
+          echo "Cache Version ${{ secrets.CACHE_VERSION }}"
+          pip install poetry toml-cli
+          poetry install
+          poetry config --list
+
+      - name: Print tool versions
+        run: |
+          poetry run black --version
+
+      - name: Build wheels
+        run: poetry build
+
+      - name: Parse version from pyproject.toml
+        run: echo "DBGPT_HUB_VERSION=`toml get --toml-path pyproject.toml tool.poetry.version`" >> $GITHUB_ENV
+
+      - name: Create release note
+        run: poetry run python scripts/release-note.py $(git rev-parse --short HEAD) > RELEASE.md
+
+      - uses: ncipollo/release-action@v1
+        with:
+          artifacts: "dist/*.whl,dist/*.tar.gz"
+          bodyFile: "RELEASE.md"
+          token: ${{ secrets.GITHUB_TOKEN }}
+          draft: true
+          tag: v${{ env.DBGPT_HUB_VERSION }}
+          commit: ${{ env.GITHUB_SHA }}
+
+      - name: Upload wheels
+        run: poetry publish --username __token__ --password ${{ secrets.PYPI_TOKEN }}

dbgpt_hub/data_process/__init__.py

@@ -5,6 +5,4 @@
 
 from .sql_data_process_api import preprocess_sft_data
 
-__all__ = [
-    "preprocess_sft_data"
-]
+__all__ = ["preprocess_sft_data"]

dbgpt_hub/data_process/connectors/anydb_connector.py

@@ -1,12 +1,13 @@
 from typing import Any
 from .mysql_connector import MySQLConnector
 
+
 class AnyDBConnector(BaseConnector):
     def __init__(
         self,
         db_type: str = "mysql",
-        host: str ="127.0.0.1",
-        port: str =3306,
+        host: str = "127.0.0.1",
+        port: str = 3306,
         user: Optional[str] = None,
         passwd: Optional[str] = None,
         db: Optional[str] = None,
@@ -15,15 +16,12 @@ def __init__(
         **kwargs
     ) -> Any:
         super().__init__(db_type, host, port, user, passwd, db, charset, args, kwargs)
-        if self.db_type == 'mysql':
+        if self.db_type == "mysql":
             self.connector = MySQLConnector(
-                host=self.host,
-                port=self.port,
-                user=self.user,
-                passwd=self.passwd
+                host=self.host, port=self.port, user=self.user, passwd=self.passwd
             )
         """TO DO: postgres, bigquery, etc."""
-    
+
     def __del__(self) -> Any:
         super().__del__()
 
@@ -51,7 +49,7 @@ def get_version(self, args=None):
 
     def get_all_table_metadata(self, args=None):
         """查询所有表的元数据信息"""
-        return self.connector.get_all_table_metadata(args)     
+        return self.connector.get_all_table_metadata(args)
 
     def get_table_metadata(self, db, table, args=None):
         """查询指定表的元数据信息"""

dbgpt_hub/data_process/specialized_scenario_data_processing.py

@@ -13,18 +13,14 @@ class SpecialScenarioDataProcessor(object):
     def __init__(
         self,
         db_type: str = "mysql",
-        host: str ="127.0.0.1",
-        port: str =3306,
+        host: str = "127.0.0.1",
+        port: str = 3306,
         user: Optional[str] = None,
         passwd: Optional[str] = None,
     ) -> Any:
         self.db_type = db_type
         self.connector = AnyDBConnector(
-            db_type = db_type,
-            host = host,
-            port = port, 
-            user = user,
-            passwd = passwd
+            db_type=db_type, host=host, port=port, user=user, passwd=passwd
         )
 
     def generate_spider_nl2sql_metadata(
@@ -33,81 +29,66 @@ def generate_spider_nl2sql_metadata(
         output_folder: str = "",
         training_ratio: float = 0.7,
         valid_ratio: float = 0.3,
-        test_ratio: float = 0.0
+        test_ratio: float = 0.0,
     ):
         # Generate table.json file according to Database Info
         """
-        TO DO: 
+        TO DO:
         1. need to solve config data
         """
         table_meta_data_processor = TableMetaDataProcessor(
-            conn = self.connector,
-            config_data = None
+            conn=self.connector, config_data=None
         )
-        spider_table_metadata = \
+        spider_table_metadata = (
             table_meta_data_processor.generate_spider_table_metadata()
+        )
 
-        with open(os.path.join(output_folder, 'tables.json'), 'w', encoding='utf-8') as json_file:
+        with open(
+            os.path.join(output_folder, "tables.json"), "w", encoding="utf-8"
+        ) as json_file:
             json.dump(spider_table_metadata, json_file, ensure_ascii=False, indent=4)
 
-        text2sql_pairs = self._parse_text2sql_pairs(
-            input_folder = input_folder
-        )
+        text2sql_pairs = self._parse_text2sql_pairs(input_folder=input_folder)
 
-        metadata_with_tokens = self._parse_tokens(
-            text2sql_pairs = text2sql_pairs
-        )
+        metadata_with_tokens = self._parse_tokens(text2sql_pairs=text2sql_pairs)
 
         # split metadata into training valid and test data
         train_data, remain_data = train_test_split(
-            metadata_with_tokens, 
-            test_size = (1 - training_ratio), 
-            random_state = 42
+            metadata_with_tokens, test_size=(1 - training_ratio), random_state=42
         )
-        
+
         if test_ratio > 0:
             valid_data, test_data = train_test_split(
-                remain_data, 
-                test_size = test_ratio / (valid_ratio + test_ratio), 
-                random_state = 42
+                remain_data,
+                test_size=test_ratio / (valid_ratio + test_ratio),
+                random_state=42,
             )
 
             with open(
-                os.path.join(output_folder, 'train.json'), 
-                'w', 
-                encoding='utf-8'
+                os.path.join(output_folder, "train.json"), "w", encoding="utf-8"
             ) as json_file:
                 json.dump(train_data, json_file, ensure_ascii=False, indent=4)
 
             with open(
-                os.path.join(output_folder, 'valid.json'), 
-                'w', 
-                encoding='utf-8'
+                os.path.join(output_folder, "valid.json"), "w", encoding="utf-8"
             ) as json_file:
                 json.dump(valid_data, json_file, ensure_ascii=False, indent=4)
 
             with open(
-                os.path.join(output_folder, 'test.json'), 
-                'w', 
-                encoding='utf-8'
+                os.path.join(output_folder, "test.json"), "w", encoding="utf-8"
             ) as json_file:
                 json.dump(test_data, json_file, ensure_ascii=False, indent=4)
         else:
             with open(
-                os.path.join(output_folder, 'train.json'), 
-                'w', 
-                encoding='utf-8'
+                os.path.join(output_folder, "train.json"), "w", encoding="utf-8"
             ) as json_file:
                 json.dump(train_data, json_file, ensure_ascii=False, indent=4)
 
             with open(
-                os.path.join(output_folder, 'valid.json'), 
-                'w', 
-                encoding='utf-8'
+                os.path.join(output_folder, "valid.json"), "w", encoding="utf-8"
             ) as json_file:
                 json.dump(remain_data, json_file, ensure_ascii=False, indent=4)
 
-
     def _parse_text2sql_pairs(
         self,
         input_folder: Optional[str] = None,
@@ -123,35 +104,35 @@ def _parse_text2sql_pairs(
 
         # Iterate through all files in the folder
         for filename in os.listdir(input_folder):
-            if filename.endswith('.csv'):
+            if filename.endswith(".csv"):
                 file_path = os.path.join(input_folder, filename)
-                
+
                 # Open and read the CSV file
-                with open(file_path, 'r', encoding='utf-8') as csv_file:
+                with open(file_path, "r", encoding="utf-8") as csv_file:
                     csv_reader = csv.DictReader(csv_file)
-                    
+
                     # Iterate through each row in the CSV file
                     for row in csv_reader:
-                        db_name = row['db_name']
-                        nl_question = row['nl_question']
-                        query = row['query']
-                        
+                        db_name = row["db_name"]
+                        nl_question = row["nl_question"]
+                        query = row["query"]
+
                         # Create a dictionary for the current row and append it to the list
-                        data_list.append({'db_id': db_name, 'question': nl_question, 'query': query})
+                        data_list.append(
+                            {"db_id": db_name, "question": nl_question, "query": query}
+                        )
 
         # Now, data_list contains all the rows from all CSV files as dictionaries
         return data_list
-
-    def _parse_tokens(
-        self,
-        text2sql_pairs: Optional[Dict] = None
-    ) -> Any:
+
+    def _parse_tokens(self, text2sql_pairs: Optional[Dict] = None) -> Any:
         """
         TO DO:
-        need to parse SQL and NL into list of tokens 
+        need to parse SQL and NL into list of tokens
         """
         pass
 
+
 if __name__ == "__main__":
     data_processor = SpecialScenarioDataProcessor()
     data_processor.generate_spider_nl2sql_metadata()

dbgpt_hub/data_process/sql_data_process.py

@@ -15,6 +15,7 @@
     INSTRUCTION_PROMPT,
 )
 
+
 class ProcessSqlData:
     def __init__(self, train_file=None, dev_file=None) -> None:
         self.train_file = train_file
@@ -165,4 +166,4 @@ def create_sft_raw_data(self):
     precess = ProcessSqlData(
         train_file=all_in_one_train_file, dev_file=all_in_one_dev_file
     )
-    precess.create_sft_raw_data()
+    precess.create_sft_raw_data()