[devops] remove post commit ci (#5566)

* [devops] remove post commit ci

* [misc] run pre-commit on all files

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

applications/ColossalQA/colossalqa/data_loader/table_dataloader.py

@@ -1,39 +1,40 @@
-'''
+"""
 Class for loading table type data. please refer to Pandas-Input/Output for file format details.
-'''
+"""
 
 
-import os
 import glob
+import os
+
 import pandas as pd
-from sqlalchemy import create_engine
-from colossalqa.utils import drop_table
 from colossalqa.mylogging import get_logger
+from colossalqa.utils import drop_table
+from sqlalchemy import create_engine
 
 logger = get_logger()
 
-SUPPORTED_DATA_FORMAT = ['.csv','.xlsx', '.xls','.json','.html','.h5', '.hdf5','.parquet','.feather','.dta']
+SUPPORTED_DATA_FORMAT = [".csv", ".xlsx", ".xls", ".json", ".html", ".h5", ".hdf5", ".parquet", ".feather", ".dta"]
+
 
 class TableLoader:
-    '''
+    """
     Load tables from different files and serve a sql database for database operations
-    '''
-    def __init__(self, files: str, 
-                 sql_path:str='sqlite:///mydatabase.db', 
-                 verbose=False, **kwargs) -> None:
-        '''
+    """
+
+    def __init__(self, files: str, sql_path: str = "sqlite:///mydatabase.db", verbose=False, **kwargs) -> None:
+        """
         Args:
             files: list of files (list[file path, name])
             sql_path: how to serve the sql database
-            **kwargs: keyword type arguments, useful for certain document types 
-        '''
+            **kwargs: keyword type arguments, useful for certain document types
+        """
         self.data = {}
         self.verbose = verbose
         self.sql_path = sql_path
         self.kwargs = kwargs
         self.sql_engine = create_engine(self.sql_path)
         drop_table(self.sql_engine)
-        
+
         self.sql_engine = create_engine(self.sql_path)
         for item in files:
             path = item[0]
@@ -42,68 +43,68 @@ class TableLoader:
                 raise FileNotFoundError(f"{path} doesn't exists")
             if not any([path.endswith(i) for i in SUPPORTED_DATA_FORMAT]):
                 raise TypeError(f"{path} not supported. Supported type {SUPPORTED_DATA_FORMAT}")
-            
+
             logger.info("loading data", verbose=self.verbose)
             self.load_data(path)
             logger.info("data loaded", verbose=self.verbose)
             self.to_sql(path, dataset_name)
 
     def load_data(self, path):
-        '''
+        """
         Load data and serve the data as sql database.
         Data must be in pandas format
-        '''
+        """
         files = []
         # Handle glob expression
         try:
             files = glob.glob(path)
         except Exception as e:
             logger.error(e)
-        if len(files)==0:
+        if len(files) == 0:
             raise ValueError("Unsupported file/directory format. For directories, please use glob expression")
-        elif len(files)==1:
+        elif len(files) == 1:
             path = files[0]
         else:
             for file in files:
                 self.load_data(file)
 
-        if path.endswith('.csv'):
+        if path.endswith(".csv"):
             # Load csv
             self.data[path] = pd.read_csv(path)
-        elif path.endswith('.xlsx') or path.endswith('.xls'):
+        elif path.endswith(".xlsx") or path.endswith(".xls"):
             # Load excel
             self.data[path] = pd.read_excel(path)  # You can adjust the sheet_name as needed
-        elif path.endswith('.json'):
+        elif path.endswith(".json"):
             # Load json
             self.data[path] = pd.read_json(path)
-        elif path.endswith('.html'):
+        elif path.endswith(".html"):
             # Load html
             html_tables = pd.read_html(path)
             # Choose the desired table from the list of DataFrame objects
             self.data[path] = html_tables[0]  # You may need to adjust this index
-        elif path.endswith('.h5') or path.endswith('.hdf5'):
+        elif path.endswith(".h5") or path.endswith(".hdf5"):
             # Load h5
-            self.data[path] = pd.read_hdf(path, key=self.kwargs.get('key', 'data'))  # You can adjust the key as needed
-        elif path.endswith('.parquet'):
+            self.data[path] = pd.read_hdf(path, key=self.kwargs.get("key", "data"))  # You can adjust the key as needed
+        elif path.endswith(".parquet"):
             # Load parquet
-            self.data[path] = pd.read_parquet(path, engine='fastparquet')
-        elif path.endswith('.feather'):
+            self.data[path] = pd.read_parquet(path, engine="fastparquet")
+        elif path.endswith(".feather"):
             # Load feather
             self.data[path] = pd.read_feather(path)
-        elif path.endswith('.dta'):
+        elif path.endswith(".dta"):
             # Load dta
             self.data[path] = pd.read_stata(path)
         else:
             raise ValueError("Unsupported file format")
-        
+
     def to_sql(self, path, table_name):
-        '''
+        """
         Serve the data as sql database.
-        '''
-        self.data[path].to_sql(table_name, con=self.sql_engine, if_exists='replace', index=False)
+        """
+        self.data[path].to_sql(table_name, con=self.sql_engine, if_exists="replace", index=False)
         logger.info(f"Loaded to Sqlite3\nPath: {path}", verbose=self.verbose)
         return self.sql_path
-    
+
     def get_sql_path(self):
         return self.sql_path
 
@@ -113,7 +114,3 @@ class TableLoader:
             self.sql_engine.dispose()
             del self.data
             del self.sql_engine
-
-
-
-