5 ChatGPT prompts I use every day as a Python developer

5 ChatGPT prompts I use every day as a Python developer
I've been writing Python for years — Flask apps on my own VPS, scrapers, trading bots, the occasional React frontend bolted on top. The last 12 months I've used ChatGPT (and Claude, and Gemini) daily as part of my workflow.
What I've noticed: most devs use AI like a search engine. They type "how do I do X in Python" and paste the first answer. That's fine, but it's leaving 80% of the value on the table.
The real leverage is in reusable prompt templates — structured prompts you fill in with your code or error, that consistently get you a useful answer. Below are five I use almost every day. Copy them, save them in a snippets file, thank me later.

1. The "explain this error like I'm tired" prompt When you've been debugging for two hours and the stacktrace is starting to look like ancient runes. I'm getting this Python error:

{paste full traceback here}

Here's the relevant code:

{paste 10-30 lines of context}

Explain in 3 parts:

1. What is actually breaking, in plain English
2. The most likely root cause given my code
3. The smallest possible fix

Don't rewrite my whole function. Don't add features. Just fix it.
Why it works: the "don't rewrite my whole function" line is critical. Without it, you get back 80 lines of "improved" code when you only needed one line changed.

1. The refactor prompt that doesn't go rogue For when a function works but you know it's ugly. Refactor this Python function for readability and maintainability.

Constraints:

• Keep the exact same input/output behavior
• Keep the same function signature
• No new dependencies
• Add type hints if missing
• Add a one-line docstring if missing
• Explain each change in a bullet list AFTER the code

Here's the function:

{paste function}
The "explain each change" part is what makes this useful. You learn why it's better, not just see different code.

1. The test generator that actually thinks about edge cases Generate pytest tests for this Python function.

Cover:

• The happy path (1-2 tests)
• Edge cases (empty input, None, wrong type, boundary values)
• Any failure modes the code clearly handles

Use pytest fixtures only if genuinely needed. No mocks unless the function makes external calls. Group tests in a single class.

Function:

{paste function}
The trick here is being explicit about what you don't want (mocks, fixtures everywhere). Default AI output loves both.

1. The "is this code review-ready" prompt Before I open a PR I run this on the diff. Review this Python code as a senior developer would.

Focus on:

• Bugs or logic errors
• Security issues (especially around input handling, SQL, file paths)
• Performance red flags
• Naming and clarity

Don't comment on style if a linter would catch it. Don't suggest comments. Be direct — if it's fine, say "looks good" and move on.

Code:

{paste code}
The "if it's fine, say it's fine" instruction stops the model from inventing problems just to seem thorough. Game-changer.

1. The architecture sanity check For when you're about to commit to a design decision and want a second opinion before writing 500 lines. I'm building {short description of feature, 1-2 sentences}.

My current plan:
{bullet list of your approach}

Tech stack: {your stack}

Tell me:

1. What's the biggest risk in this approach
2. One simpler alternative I should consider
3. One thing I'm probably underestimating

Keep it to under 200 words total. I don't need a treatise.
This one saves me hours per week. Not because the AI is always right, but because forcing yourself to write down your plan in this format already surfaces half the issues.
A note on what makes these work
You'll notice a pattern: every prompt tells the model what not to do. That's not paranoia, that's the whole game. Default AI output is verbose, hedging, and tries to add features. Constraining the output is where the productivity gain lives.

I've collected 130+ of these — organized by use case (debugging, refactoring, testing, API design, deployment, SQL) — over at devpromptsbyrick.com . Launch-week discount is live until this weekend if you find this stuff useful.

Either way, save these five somewhere you'll find them. Future-you at 11pm debugging a production issue will thank you.