ChatGPT Prompt for Debugging Python Code

Use this ChatGPT prompt template to debug Python code faster. Copy the prompt and paste it into ChatGPT to analyze errors, identify bugs, and get corrected code.

Prompt Template

prompt.txt

You are a senior Python engineer.

Analyze the following Python code and identify the bug.

Explain the root cause clearly, then provide a corrected version of the code with inline comments describing what was changed and why.

Code:
[PASTE CODE HERE]

Open in ChatGPT Open in Claude

How to Use This Prompt

1Copy the prompt template above.
2Paste it into ChatGPT at chat.openai.com.
3Replace [PASTE CODE HERE] with your actual Python code.
4Include the error message or unexpected output if you have one.
5Review the AI explanation and corrected code.

When to Use This Prompt

You have a Python function that throws an unexpected exception.
Your script produces incorrect output and you cannot identify why.
You need a second opinion on a failing test or broken logic.
You want to understand a bug before fixing it yourself.

Example Input

def calculate_average(numbers):
    total = 0
    for n in numbers:
        total += n
    return total / len(numbers)

result = calculate_average([])
print(result)

Expected Output

The AI will identify the ZeroDivisionError caused by calling the function with an empty list, explain why it fails, and provide a corrected version with a guard clause and clear comments.

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Frequently Asked Questions

Can ChatGPT debug Python code?

Yes. ChatGPT can analyze Python code, identify bugs, explain the root cause, and suggest corrected versions. Results are best when you provide the error message, stack trace, and relevant code snippet.

What Python errors can AI help debug?

AI assistants can help with syntax errors, logic bugs, runtime exceptions, type errors, off-by-one errors, and incorrect algorithm implementations. They are especially useful for explaining unfamiliar error messages.

Should I trust AI-generated Python fixes?

AI-generated fixes should always be reviewed and tested before use. The AI may misunderstand context or edge cases, so treat its output as a starting point rather than a final solution.

What context should I include when debugging with ChatGPT?

Include the full error message or stack trace, the relevant code block, the Python version if relevant, and a description of what the code is supposed to do. More context leads to more accurate suggestions.