Python Interview Prep

Introduction

Senior Python interviews mix language depth (GIL, mutability, decorators), data structures, and system design. Have crisp 60-second answers ready.

Understanding the topic

Core concepts to understand:

• Mutable vs immutable types — and why it matters.
• List vs tuple vs set vs dict — when which?
• GIL implications.
• Decorators end-to-end.
• Generators / iterators.
• async vs threads vs processes.

Syntax reference

Visual flow / code:

# Be ready to write live:

# 1. LRU cache from scratch
from collections import OrderedDict
class LRU:
    def __init__(self, cap): self.cap, self.d = cap, OrderedDict()
    def get(self, k):
        if k not in self.d: return -1
        self.d.move_to_end(k); return self.d[k]
    def put(self, k, v):
        if k in self.d: self.d.move_to_end(k)
        self.d[k] = v
        if len(self.d) > self.cap: self.d.popitem(last=False)

# 2. Timing decorator (see Decorators lesson)
# 3. async fetch many URLs (see async lesson)

Execution workflow

Real-world use

FAANG and scale-up interviews routinely ask: 'implement LRU cache', 'rate-limiter', 'producer-consumer with asyncio'. Practice these patterns until muscle memory.

Best practices

• Memorize 3 canonical patterns: LRU cache, decorator, async gather.
• Be ready to explain GIL + when to use processes/async/threads.
• Bring a real war story: a bug you debugged or a perf win.

Hands-on exercise

Interview preparation — practice these questions:

• Why is Python slow? How would you speed it up?
• Explain the GIL.
• How do decorators work?
• List vs generator — when?
• How do you design a rate limiter in Python?

Summary

In summary: Practice LRU, decorators, async live-coding. Know GIL trade-offs cold. Bring a real story.