Debug Sandbox Execution Failures

When execute_code_sandbox fails with unknown errors or incomplete output, use this debugging pattern to identify the root cause and recover incrementally.

Problem

The execute_code_sandbox tool may fail silently, truncate output, or produce opaque errors. Complex scripts with multiple file outputs are especially prone to partial failures.

Solution

Use a three-phase debugging approach:

Phase 1: Capture Partial Execution Traces

When a sandbox execution fails, rerun the code using run_shell with output piping to capture whatever output is produced before the failure:

python your_script.py 2>&1 | head -100

This reveals:

• Which functions/steps executed successfully
• Where the failure occurred
• Any error messages that were suppressed

Phase 2: Isolate Failing Functions

Break the script into smaller, testable units. Execute each function or code block independently:

# Test individual components
if __name__ == "__main__":
    # Step 1: Test imports
    import numpy as np
    print("Imports OK")
    
    # Step 2: Test function A in isolation
    result_a = function_a()
    print(f"Function A: {result_a}")
    
    # Step 3: Test function B
    result_b = function_b(result_a)
    print(f"Function B: {result_b}")

Run each section with execute_code_sandbox separately to identify which component fails.

Phase 3: Incremental Output Generation

Generate output files one at a time, verifying each before proceeding:

import numpy as np
import soundfile as sf

# Generate and save file 1
audio1 = np.random.randn(48000 * 10).astype(np.float32)
sf.write('output_01.wav', audio1, 48000, subtype='FLOAT')

# Verify file 1 exists and has expected properties
import os
assert os.path.exists('output_01.wav'), "File 1 not created"

# Generate and save file 2
audio2 = np.random.randn(48000 * 10).astype(np.float32)
sf.write('output_02.wav', audio2, 48000, subtype='FLOAT')