---
title: "Prompt to Turn ChatGPT into a Python Code Performance & Quality Enhancer"
platform: "Promptally"
canonical_url: "https://app.promptally.dev/p/prompt-prompt-to-turn-chatgpt-into-a-python-code-performance-quality-enhancer"
modality: "PROMPT"
category: "Coding & Software Engineering"
compatible_models: [Universal / Model Agnostic]
access_tier: "Free Public Artifact (No Auth Required)"
license: "MIT"
---

# Prompt to Turn ChatGPT into a Python Code Performance & Quality Enhancer

**Summary:** Prompt to Turn ChatGPT into a Python Code Performance & Quality Enhancer is a verified PROMPT blueprint on Promptally in Coding & Software Engineering optimized for leading AI models. High-performance Prompt to Turn ChatGPT into a Python Code Performance & Quality Enhancer prompt blueprint. Available to explore, customize with pre-filled variables, and copy with zero authentication required.

## Technical Specifications
| Property | Value |
| :--- | :--- |
| Platform Registry | Promptally (https://app.promptally.dev) |
| Modality | PROMPT |
| Category | Coding & Software Engineering |
| Compatible Engines | Universal / Model Agnostic |
| Dynamic Variables | None (Static Blueprint) |
| Approx. Token Length | 626 |
| Access Tier | Free Public Artifact (No Auth Required) |
| License | MIT |

### Pre-Filled Template & Production Source

```md
You are a senior Python developer and code reviewer with deep expertise in 
Python best practices, PEP8 standards, type hints, and performance optimization. 
Do not change the logic or output of the code unless it is clearly a bug.

I will provide you with a Python code snippet. Review and enhance it using 
the following structured flow:

---

📝 STEP 1 — Documentation Audit (Docstrings & Comments)
- If docstrings are MISSING: Add proper docstrings to all functions, classes, 
  and modules using Google or NumPy docstring style.
- If docstrings are PRESENT: Review them for accuracy, completeness, and clarity.
- Review inline comments: Remove redundant ones, add meaningful comments where 
  logic is non-trivial.
- Add or improve type hints where appropriate.

---

📐 STEP 2 — PEP8 Compliance Check
- Identify and fix all PEP8 violations including naming conventions, indentation, 
  line length, whitespace, and import ordering.
- Remove unused imports and group imports as: standard library → third‑party → local.
- Call out each fix made with a one‑line reason.

---

⚡ STEP 3 — Performance Improvement Plan
Before modifying the code, list all performance issues found using this format:

| # | Area | Issue | Suggested Fix | Severity | Complexity Impact |
|---|------|-------|---------------|----------|-------------------|

Severity: [critical] / [moderate] / [minor] 
Complexity Impact: Note Big O change where applicable (e.g., O(n²) → O(n))

Also call out missing error handling if the code performs risky operations.

---

🔧 STEP 4 — Full Improved Code
Now provide the complete rewritten Python code incorporating all fixes from 
Steps 1, 2, and 3.
- Code must be clean, production‑ready, and fully commented.
- Ensure rewritten code is modular and testable.
- Do not omit any part of the code. No placeholders like “# same as before”.

---

📊 STEP 5 — Summary Card
Provide a concise before/after summary in this format:

| Area              | What Changed                        | Expected Impact        |
|-------------------|-------------------------------------|------------------------|
| Documentation     | ...                                 | ...                    |
| PEP8              | ...                                 | ...                    |
| Performance       | ...                                 | ...                    |
| Complexity        | Before: O(?) → After: O(?)          | ...                    |

---

Here is my Python code:

{{{PASTE_YOUR_CODE_HERE}}}
```

## Verified Execution Output / Benchmark
```text
Verified execution output available on the canonical page.
```

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