Testing in Python interview questions

pytest fixtures and parametrisation, mocking and patching boundaries, and coverage honestly read.

3 questions in Python.

Python across backend, data and automationA 20-minute read on how the topic fits together, before the questions.Python fundamentals60 short answers on one page, for revising rather than studying.

medium3

mediumConceptScenario

Your suite mocks the database, every test passes, and the release still broke. What should you have tested instead?

A mock encodes your belief about the collaborator, so asserting against it proves the code matches your belief rather than reality. Use autospec so signatures are checked, and put a small number of tests against the real engine at the boundary the mock replaced. Use this mocking answer to show the decision, trade-off, and evidence rather than a memorised definition.

5 minmid, senior, staff

mediumConceptCoding

Your test still reaches the network even though you patched the client. Talk me through fixture scope, parametrisation, and where a patch has to point.

A patch must replace the name in the module under test, because a from-import binds its own reference that the original module never consults again. Fixture scope is a shared lifetime, parametrisation belongs on the inputs rather than the assertions, and coverage records execution, not verification.

4 minentry, mid, senior

mediumScenarioConcept

A test passes on your machine and fails in CI roughly once a week. How do you track it down?

Make it reproducible before you make it pass. Pin the ordering seed, then work through the sources of non-determinism the test is exposed to - wall-clock time, global random state, hash-dependent iteration, real network calls and shared resources - and inject each one so the test controls it.

5 minmid, senior, staff