Python Interview Questions

This tests whether the candidate understands immutability as a concept, not just as a trivia answer. Developers who pick the right data structure write fewer bugs.

List comprehensions are Pythonic and everywhere in real codebases. The generator follow-up shows whether the candidate thinks about memory and performance, even at a junior level.

Decorators are used constantly in Python frameworks (Flask routes, Django views, pytest fixtures). A junior who can write one from scratch understands functions as first-class objects.

This gotcha trips up developers at all levels and causes real bugs in production. Knowing about it shows the candidate has written enough Python to get bitten by it, or at least studied the language carefully.

Python's tooling ecosystem (venvs, linters, formatters, type checkers) is fragmented. A developer who has a clean local setup will onboard faster and produce more consistent code.

Identity vs equality is a subtle distinction that causes confusing bugs, especially with Python's integer interning. It tests whether the candidate understands what's happening in memory, not just at the syntax level.

File I/O is bread-and-butter Python work. This reveals whether the candidate uses context managers, handles large files properly, and picks the right tool (csv module vs pandas) for the job.