Update google_sheets.py

google_sheets.py

@@ -4,22 +4,15 @@ from googleapiclient.discovery import build
 from env_setup import config
 import pandas as pd
 
-# Define the required scopes for accessing Google Sheets
 SCOPES = ['https://www.googleapis.com/auth/spreadsheets']
 
 def authenticate_google_account():
-    """
-    Authenticate the Google account using service account credentials.
-    """
     service_account_file = config["google_creds"]
     if not service_account_file:
         raise ValueError("Service account credentials path is missing in env_setup.py.")
     return service_account.Credentials.from_service_account_file(service_account_file, scopes=SCOPES)
 
 def store_data_in_sheet(sheet_id, chunks, summary, overall_sentiment):
-    """
-    Store data into a Google Sheet.
-    """
     creds = authenticate_google_account()
     service = build('sheets', 'v4', credentials=creds)
     sheet = service.spreadsheets()
@@ -50,43 +43,32 @@ def store_data_in_sheet(sheet_id, chunks, summary, overall_sentiment):
         print(f"Error updating Google Sheets: {e}")
 
 def fetch_call_data(sheet_id, sheet_range="Sheet1!A1:E"):
-    """
-    Fetches data from the specified Google Sheet and returns a pandas DataFrame.
-    """
     try:
-        # Authenticate and get credentials
         creds = authenticate_google_account()
         service = build('sheets', 'v4', credentials=creds)
         sheet = service.spreadsheets()
 
-        # Fetch the data
         result = sheet.values().get(
             spreadsheetId=sheet_id,
             range=sheet_range
         ).execute()
         
-        # Get the rows
         rows = result.get("values", [])
         
-        # Log the fetched rows for debugging
-        print(f"Fetched rows: {rows}")
+        print(f"Fetched rows: {rows}")  # Log fetched rows
         
-        # If rows exist, convert to DataFrame
         if rows:
-            # Use the first row as column headers
             headers = rows[0]
             data = rows[1:]
             
-            # Create DataFrame
             df = pd.DataFrame(data, columns=headers)
+            print(f"DataFrame: {df}")  # Log DataFrame
             
             return df
         else:
-            # Return an empty DataFrame if no data
             print("No data found in the specified range.")
             return pd.DataFrame()
     
     except Exception as e:
         print(f"Error fetching data from Google Sheets: {e}")
-        # Return an empty DataFrame in case of error
         return pd.DataFrame()