Python developer test for hiring

Why test Python skills before the interview?

Python appears on CVs for data scientists, back-end engineers, automation testers and analysts, and the depth behind it varies a lot. Some candidates have written production services; others have run a few notebooks. A quick, timed screen tells you which is which before an engineer spends an hour on a technical interview.

What this template covers

• Core types: lists, tuples, dictionaries, sets and which of them are mutable or hashable.
• Syntax in practice: slicing, comprehensions and the difference between is and ==.
• Errors and resources: try/except/else and context managers with with.
• Classic bugs: mutable default arguments and shared references to the same list.
• Working at scale: generators and streaming large files instead of loading them whole.

How to run it well

For a first screen, twelve questions in 15 minutes is about right. Most questions show a short snippet, so candidates need time to read code but should not need to run it. A pass mark of 65% fits junior and mid-level roles. For senior hires, push it to 75% and add your own questions on typing, async code or packaging.

Turn on question and option shuffling, and use a random subset if you send the test to a large applicant pool. In the results, look at the bug-spotting questions first. Someone who recognises the mutable default argument problem usually has real debugging experience behind them.

Who this test is for

Use it for back-end and full-stack Python developers, automation and scripting roles, junior data engineers and graduates coming out of coding bootcamps. Teams that hire data scientists can use it to confirm the general Python level before testing statistics or machine learning separately. Because the questions rely on reading short snippets rather than any particular library, the results compare fairly between people who learnt Python at university, at work or on their own. That makes it a good equaliser for career changers whose CVs look thin but whose skills may be solid.

Make it yours

Add questions on the frameworks you actually use, such as Django, Flask, FastAPI or pandas, and on your own conventions for testing and type hints. You can ask the AI generator for more questions on a narrow topic like decorators or asyncio and review each one before it goes live. Answers are scored on the server, so the key cannot be found by inspecting the page.