Python coding interview practice

Python is the most common language for coding interviews because it lets you spend your minutes on the idea instead of the syntax. That only helps if you know which parts of the standard library to reach for and which habits quietly make a solution slow.

How do I practise a Python coding interview?

To practise a Python coding interview, solve problems out loud in a live editor and learn the standard tools interviewers expect: dict and set for lookups, collections.deque for queues, heapq for heaps, Counter for counting and bisect for sorted data. Then defend your code against follow-up questions about complexity.

Practise a Python interview

What interviewers expect in Python

Interviewers expect idiomatic Python without it becoming a puzzle. Comprehensions, tuple unpacking, enumerate and zip are welcome when they make the code shorter and clearer, and a liability when you cannot explain them. If you choose a one-liner, be ready to say what it costs.

You are still graded on the same things as in any language: did you clarify the problem, pick a sensible approach, state time and space complexity, and test an edge case without being asked. Python removes boilerplate, not the need to reason about cost.

Python tools worth knowing cold

dict and set give average constant-time lookups; use them for seen-before checks and for counting. collections.Counter and defaultdict(list) or defaultdict(int) remove the setup code around grouping and counting.

collections.deque is the queue: popleft() is constant time, while list.pop(0) shifts every element and is linear. Breadth-first search should use a deque.

heapq is a min-heap on a list. For a max-heap push negated values, or push tuples such as (priority, item). heapq.nlargest and nsmallest are fine for small k but say why you chose them.

bisect finds insertion points in a sorted list in logarithmic time; sorted(items, key=...) and sort(key=...) cover most ordering questions; functools.lru_cache or a dict memoises recursion in one line.

Python mistakes that cost points

Using list.pop(0) or insert(0, x) in a loop, which turns a linear solution into a quadratic one. Reach for deque.

Building a grid with [[0] * n] * m. Every row is the same list, so changing one cell changes the whole column. Use [[0] * n for _ in range(m)].

Forgetting the recursion limit. CPython stops at about a thousand frames by default, so a recursive depth-first search on a long chain can crash. Say that you would use an explicit stack or raise the limit.

Assuming integer division behaves like other languages: // rounds toward negative infinity, so -7 // 2 is -4. Mutable default arguments, and comparing with is instead of ==, are classic follow-up questions.

Concatenating strings in a loop. Collect pieces in a list and join them once.

Practising Python here

On giveinterview you practise Python in the format you will face: you explain your approach first, write the solution in a live editor that runs Python, and then the interviewer asks cross-questions about edge cases, complexity and a changed constraint. The session ends with a scored report that shows whether you lost points explaining, coding or defending.

Your first 3 single-question interviews are free for life, every interview report is free, and a new account also gets 6 welcome credits. After that a single-question interview costs 1 credit, and credits do not expire.

Frequently asked questions

Is Python allowed in coding interviews?

Almost always. Most companies let you pick the language you are strongest in. If a role names a language in the description, practise in that one.

Is Python too slow for interview problems?

Interview inputs are sized for the algorithm, not the language. A correct linear or n log n solution in Python passes. A quadratic solution does not, in any language.

Can I run Python code in the interview here?

Yes. The live editor runs Python, and the interviewer reads what you wrote and asks about it.