Python Execution Fallback Workflow
This skill provides a systematic debugging approach when inline Python code execution fails, particularly in heredoc or shell_agent contexts.
Pattern Overview
When Python code execution fails, follow this recovery workflow:
- Attempt inline execution first - Try running Python code directly
- Write script to file on failure - Persist the code to a
.pyfile - Execute the file - Run the saved script via shell
- Validate output - Verify results are correct and complete
When to Use
Apply this pattern when:
- Inline Python execution fails with syntax or runtime errors
- Heredoc-based code execution encounters parsing issues
- Working with complex multi-line scripts that need debugging
- Need systematic approach to isolate execution failures
- Spreadsheet/data generation tasks fail in inline mode
Step-by-Step Instructions
Step 1: Attempt Inline Execution
Try executing Python code inline first (using execute_code_sandbox or similar):
# Example: Attempt inline execution
import pandas as pd
import openpyxl
df = pd.read_excel("input.xlsx")
# Process data...
df.to_excel("output.xlsx", index=False)
If this succeeds, proceed. If it fails, move to Step 2.
Step 2: Write Script to File (On Failure)
When inline execution fails, write the complete script to a persistent file:
# Capture the script content
script_content = '''
import pandas as pd
import openpyxl
import sys
try:
# Your original code here
df = pd.read_excel("input.xlsx")
# Processing logic
result_df = df.groupby("category").sum()
# Output
result_df.to_excel("output.xlsx", index=False)
print("SUCCESS: File generated")
except Exception as e:
print(f"ERROR: {e}", file=sys.stderr)
sys.exit(1)
'''
# Write to file
with open("script.py", "w") as f:
f.write(script_content)
print("Script written to script.py")
Step 3: Execute the File
Run the saved script using shell execution:
python script.py
Or with error capture:
python script.py 2>&1 | tee execution.log
This approach:
- Avoids heredoc parsing issues
- Provides clearer error messages
- Allows script inspection and modification
- Enables re-execution without rewriting
Step 4: Validate Output
Verify the results are correct:
# Validation script
import pandas as pd
import os
# Check file exists
if os.path.exists("output.xlsx"):
df = pd.read_excel("output.xlsx")
print(f"Rows: {len(df)}, Columns: {len(df.columns)}")
print(df.head())
print("VALIDATION: PASSED")
else:
print("VALIDATION: FAILED - Output file missing")
Code Example: Complete Workflow
# Full fallback workflow example
def generate_spreadsheet_fallback(data, output_path):
"""Generate spreadsheet with fallback workflow"""
# Step 1: Try inline
inline_script = f'''
import pandas as pd
data = {data}
df = pd.DataFrame(data)
df.to_excel("{output_path}", index=False)
'''
try:
# Attempt inline execution
result = execute_code_sandbox(code=inline_script)
if "error" not in result.lower():
return "SUCCESS_INLINE"
except Exception as e:
pass
# Step 2: Write to file
file_script = f'''
import pandas as pd
import sys
try:
data = {data}
df = pd.DataFrame(data)
df.to_excel("{output_path}", index=False)
print("SUCCESS")
except Exception as e:
print(f"ERROR: {{e}}", file=sys.stderr)
sys.exit(1)
'''
with open("generate.py", "w") as f:
f.write(file_script)
# Step 3: Execute file
shell_result = run_shell(command="python generate.py")
# Step 4: Validate
if os.path.exists(output_path):
return "SUCCESS_FILE"
else:
return "FAILED"
Best Practices
- Include error handling in file-based scripts (try/except with sys.stderr)
- Add success indicators (print statements) to confirm execution
- Preserve original logic when converting from inline to file
- Check return codes when executing scripts via shell
- Clean up temporary files after successful validation
- Log both stdout and stderr for debugging
Common Failure Scenarios
This pattern helps resolve:
- Heredoc string escaping issues
- Multi-line code formatting problems
- Import path resolution failures
- Environment variable access issues
- Complex indentation in inline code
Related Patterns
- Combine with
retry-with-modificationfor iterative debugging - Use alongside
output-validation-checkfor result verification - Pair with
error-log-analysisfor root cause identification
Converted and distributed by TomeVault — claim your Tome and manage your conversions.