technical
Comprehensions, generators, decorators, the GIL, and how real Python engineers write code — the questions asked in backend, ML, and data rounds.
Sample questions
These are the kinds of questions you'll drill. Real mock rounds will generate many more — tailored to the exact JD you paste in.
Explain the GIL. When does it bite you, and when doesn't it?
What's the difference between a generator and an iterator?
When would you use a decorator? Walk me through writing one.
How do you structure a large Python codebase?
Reading Python questions isn't the same as answering them live. You need the rep — the pause, the clarifying question, the moment where you realize you forgot the framework. We put you in that exact spot, then show you what a strong answer would have looked like.
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Joins, indexes, and query plans.
Data Structures & Algorithms
Arrays, graphs, trees, and the classics.
Behavioural
STAR answers that actually land.
Leadership
Influence without authority, grown-up feedback.
Paste the JD, pick your topics, and go. Full session, full feedback, no fluff.
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