Python Code Refactoring & Comprehensive Unit Test Suite Generator
“Transform messy legacy Python scripts into clean, type-hinted, PEP-8 compliant code with 100% test coverage using pytest and mock fixtures.”
Curated by David Chen
Updated: Aug 23, 2026
Run Time: 2 mins
Verified: ChatGPT, Claude, Gemini
Architecture & Behavioral Blueprint
This prompt implements an end-to-end framework specifically designed for Software Testing & Code Maintenance. It enforces role authority, step-by-step structural reasoning, and negative constraints to prevent generic, repetitive AI filler.
Target Use CaseSoftware Testing & Code Maintenance
Engine CompatibilityChatGPT • Claude • Gemini
Complexity LevelINTERMEDIATE
The Complete AI Prompt
1-Click Clipboard Ready
System / Prompt Matrix|165 words (1189 chars)
Copied 3,950 times
Act as a Senior Python Core Developer and QA Architect.
Here is a Python function/module that requires refactoring:
[PASTE PYTHON CODE HERE]
Perform the following 4 engineering upgrades:
1. CODE REFACTORING:
- Refactor the code adhering to clean architecture, SOLID principles, and PEP 8 guidelines.
- Add strict type annotations from 'typing' module (Union, Optional, List, Dict, Callable).
- Use dataclasses / Pydantic models for structured data handling.
- Eliminate code smells, nested if-else pyramids, and redundant computations.
- Add Google-style docstrings explaining parameters, return values, and exceptions raised.
2. EDGE CASE & ERROR RESILIENCE:
- Implement explicit custom exception classes for domain failures.
- Add comprehensive input validation and graceful fallback handling.
3. PYTEST TEST SUITE:
- Generate a complete, robust 'test_module.py' using pytest.
- Include parameterized tests (@pytest.mark.parametrize) for boundary conditions.
- Mock all external network calls, file I/O, or database queries using 'pytest-mock' or 'unittest.mock'.
- Test happy paths, edge cases (empty lists, None values, maximum limits), and expected error raising (pytest.raises).
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