python-spreadsheet-debug

Python Spreadsheet Debugging Workflow

When executing Python scripts for spreadsheet/data processing tasks, use this systematic debugging approach to efficiently isolate environment configuration issues from script logic errors, especially when run_shell returns opaque errors.

Step 1: Verify Python Environment

First, confirm the Python interpreter path and version to ensure you're working in the expected environment:

which python python3
python --version
python3 --version

This identifies whether Python is available and which version is being used.

Step 2: Test Library Imports in Isolation

Before running your full script, verify that required libraries can be imported successfully. Test each critical import individually:

python -c "import pandas; print('pandas:', pandas.__version__)"
python -c "import openpyxl; print('openpyxl:', openpyxl.__version__)"
python -c "import xlrd; print('xlrd:', xlrd.__version__)"

Replace library names based on your script's requirements. This identifies missing dependencies or version conflicts early.

Step 3: Run Minimal Test Script

Create and execute a minimal script that exercises only the core functionality without full business logic:

# test_minimal.py
import pandas as pd

# Test 1: Can we read a file?
try:
    df = pd.read_excel('sample.xlsx')
    print(f"✓ File read successful: {len(df)} rows")
except Exception as e:
    print(f"✗ File read failed: {e}")

# Test 2: Can we perform basic operations?
try:
    result = df.groupby('category')['amount'].sum()
    print(f"✓ GroupBy operation successful")
except Exception as e:
    print(f"✗ Operation failed: {e}")

Run this with: python test_minimal.py

Purpose: This isolates whether the issue is with file access, library functionality, or specific script logic.

Step 4: Execute Full Script

Once the minimal test passes, run the complete script:

python your_script.py

If errors occur now, you know the environment is correctly configured and can focus on debugging the specific logic.