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AI Python Debugging Prompt

Use this optimized AI prompt to create professional python debugging. Copy the template, customize it for your needs, and get better AI outputs instantly.

prompt-template.txt

You are a senior Python developer with 15 years of debugging experience.

Task: Debug and fix Python code.

Problem Description: [DESCRIBE THE ISSUE]

Code:
[PASTE YOUR CODE HERE]

Expected Behavior: [WHAT SHOULD HAPPEN]
Actual Behavior: [WHAT IS HAPPENING]
Error Message (if any): [PASTE ERROR]

Please provide:

1. Root Cause Analysis:
   - Identify the exact issue
   - Explain why it's happening
   - Common scenarios that cause this

2. Fix:
   - Corrected code with clear comments
   - Explanation of changes

3. Prevention:
   - How to avoid this in the future
   - Relevant best practices
   - Testing strategies

4. Related Issues:
   - Other potential bugs in the code
   - Performance considerations
   - Security concerns (if applicable)

Explain your reasoning step by step. Assume I want to learn, not just get a fix.

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💬Example Output

Prompt Example:

[Fill in the placeholders with your specific details for python debugging]

Example Output:

DEBUG ANALYSIS

Problem: IndexError in list comprehension

Code Provided:
def process_users(users, scores):
    return [users[i] + ": " + str(scores[i]) for i in range(len(users))]

Error: IndexError: list index out of range

1. ROOT CAUSE ANALYSIS

The Issue:
The code assumes users and scores lists have the same length, but they don't. When iterating over range(len(users)), if scores is shorter, accessing scores[i] fails.

Why It Happens:
- The function trusts input without validation
- range(len(users)) only considers one list's length
- This is a "silent assumption" bug - works sometimes, fails unexpectedly

2. THE FIX

Option A: Safe iteration with zip (Recommended)
def process_users(users, scores):
    """Pair users with their scores safely."""
    # zip stops at shortest list - prevents IndexError
    return [f"{user}: {score}" for user, score in zip(users, scores)]

[Continues with alternative solutions and tests...]

📊Prompt Performance

Scores are estimated based on prompt characteristics (not live model calls).

Best Model:Claude

Best for:Code & technical docs

Confidence:High

Claude

100

ChatGPT

Gemini

Llama

Grok

🏆Why Claude wins for this prompt

•Exceptional code accuracy and best practices
•Clear technical explanations
•Strong debugging capabilities

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🎯What This Prompt Does

This prompt guides AI to create a professional python debugging. It provides structured instructions that help you get consistent, high-quality results from ChatGPT, Claude, Gemini, or any AI assistant.