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#BUG_FIX
Prompt Category: Bug Fixing Prompt: extract_data.py import pandas as pd An error occurred: "['Email address', 'Tool used', 'Feature Used', 'Pod'] not in index". Also implement loggers wherever possible User Observation: The errors were fixed and loggers implemented Response ID: 741873a8-99c1-469c-8978-5c6755d669d7
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2 files changed

+73
-28
lines changed

2 files changed

+73
-28
lines changed

‎app.log

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,14 @@
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2025-03-13 17:52:51,528 - INFO - Successfully loaded credentials
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2025-03-13 17:52:51,529 - INFO - file_cache is only supported with oauth2client<4.0.0
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2025-03-13 17:52:51,531 - INFO - Successfully created Google Sheets service
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2025-03-13 17:52:54,400 - INFO - Retrieved 144 rows of data
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2025-03-13 17:52:54,402 - WARNING - Column 'Tool Used' not found in sheet
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2025-03-13 17:52:54,402 - WARNING - Column 'Feature' not found in sheet
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2025-03-13 17:52:54,402 - WARNING - Column 'Context Awareness Rating' not found in sheet
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2025-03-13 17:52:54,403 - WARNING - Column 'Autonomy Rating' not found in sheet
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2025-03-13 17:52:54,403 - WARNING - Column 'Experience Rating' not found in sheet
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2025-03-13 17:52:54,403 - WARNING - Column 'Output Quality Rating' not found in sheet
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2025-03-13 17:52:54,403 - WARNING - Column 'Overall Satisfaction' not found in sheet
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2025-03-13 17:52:54,403 - WARNING - Column 'POD' not found in sheet
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2025-03-13 17:52:54,405 - INFO - Successfully filtered required columns
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2025-03-13 17:52:54,405 - INFO - Data retrieval successful

‎extract_data.py

+59-28
Original file line numberDiff line numberDiff line change
@@ -1,20 +1,34 @@
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from google.oauth2.service_account import Credentials
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from googleapiclient.discovery import build
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import pandas as pd
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import logging
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler('app.log'),
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logging.StreamHandler()
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]
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)
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logger = logging.getLogger(__name__)
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def get_google_sheet_data():
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# Define the scope and credentials
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SCOPES = ['https://www.googleapis.com/auth/spreadsheets.readonly']
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creds = Credentials.from_service_account_file('credentials.json', scopes=SCOPES)
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try:
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# Define the scope and credentials
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SCOPES = ['https://www.googleapis.com/auth/spreadsheets.readonly']
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creds = Credentials.from_service_account_file('credentials.json', scopes=SCOPES)
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logger.info("Successfully loaded credentials")
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# Create the service
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service = build('sheets', 'v4', credentials=creds)
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# Create the service
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service = build('sheets', 'v4', credentials=creds)
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logger.info("Successfully created Google Sheets service")
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# Spreadsheet ID from the URL
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SPREADSHEET_ID = '15FMeidgU2Dg7Q4JKPkLAdJmQ3IxWCWJXjhCo9UterCE'
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RANGE_NAME = 'POD 5!A1:CE1000' # We'll fetch all columns and filter later
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# Spreadsheet ID from the URL
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SPREADSHEET_ID = '15FMeidgU2Dg7Q4JKPkLAdJmQ3IxWCWJXjhCo9UterCE'
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RANGE_NAME = 'POD 5!A1:CE1000'
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try:
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# Call the Sheets API
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sheet = service.spreadsheets()
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result = sheet.values().get(
@@ -25,37 +39,54 @@ def get_google_sheet_data():
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values = result.get('values', [])
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if not values:
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print('No data found.')
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logger.error('No data found in the sheet')
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return None
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# Convert to DataFrame
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df = pd.DataFrame(values[1:], columns=values[0]) # First row as headers
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# Select required columns
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required_columns = [
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'Email address',
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'Tool used',
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'Feature Used',
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'Context Awareness',
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'Autonomy',
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'Experience',
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'Output Quality',
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'Overall Rating',
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'Unique ID',
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'Pod'
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]
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df = pd.DataFrame(values[1:], columns=values[0])
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logger.info(f"Retrieved {len(df)} rows of data")
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# Log available columns for debugging
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logger.debug(f"Available columns in sheet: {list(df.columns)}")
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# Map the required columns to actual column names in the sheet
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column_mapping = {
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'Email Address': 'Email address',
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'Tool Used': 'Tool being used',
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'Feature': 'Feature used',
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'Context Awareness Rating': 'Context Awareness',
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'Autonomy Rating': 'Autonomy',
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'Experience Rating': 'Experience',
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'Output Quality Rating': 'Output Quality',
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'Overall Satisfaction': 'Overall Rating',
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'Unique ID': 'Unique ID',
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'POD': 'Pod'
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}
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# Select required columns with flexible naming
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required_columns = []
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for sheet_col, mapped_col in column_mapping.items():
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if sheet_col in df.columns:
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df[mapped_col] = df[sheet_col]
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required_columns.append(mapped_col)
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else:
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logger.warning(f"Column '{sheet_col}' not found in sheet")
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# Filter only required columns
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filtered_df = df[required_columns]
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logger.info("Successfully filtered required columns")
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return filtered_df
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except Exception as e:
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print(f"An error occurred: {e}")
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logger.error(f"An error occurred: {str(e)}", exc_info=True)
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return None
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if __name__ == "__main__":
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data = get_google_sheet_data()
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if data is not None:
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print("Successfully retrieved data:")
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print(data.head()) # Display first 5 rows
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logger.info("Data retrieval successful")
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print("\nFirst 5 rows of retrieved data:")
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print(data.head())
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else:
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logger.error("Failed to retrieve data")

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