Python for Coding Interviews

Who This Book Is For

For Engineers Who Already Know How to Code

This book is not a data structures and algorithms textbook. The sole focus is Python — the idioms, built-ins, and standard library tools that let you implement your algorithmic thinking faster, more cleanly, and with fewer mistakes during a live interview.

If you're coming from Java, C++, Go, or JavaScript, you already have the hardest part covered: you know how to think algorithmically. This book handles the rest.

🗂️

Collections & Built-ins

Counter, defaultdict, deque — the standard library tools that eliminate boilerplate and signal Python fluency.

collections module

⚡

Sorting & Pythonic Code

Custom sort keys, cmp_to_key, list comprehensions, generators, and idiomatic patterns that make Python solutions half the length of Java equivalents.

sorted() · key functions

🏔️

Heaps & Binary Search

heapq patterns, min/max heaps, bisect for O(log n) insertion, and the manual binary search template every interviewer expects.

heapq · bisect

🔧

Functools & Itertools

@functools.cache for memoization, reduce, and the itertools combinatorics toolkit for permutations and combinations.

@cache · combinations

🧩

Interview Patterns

Two pointers, sliding window, BFS/DFS, dynamic programming, and backtracking — all implemented with idiomatic Python so the language features come together.

patterns · templates

📅

4-Week Practice Plan

30 curated LeetCode problems mapped to each chapter's techniques, with a structured weekly schedule and complexity notes for every solution.

30 LeetCode problems

See It in Action

Python That Wins Interviews

The same problem that takes 12–15 lines in Java takes 3 in Python — when you know the right tools. This book teaches you exactly those tools.

Every chapter builds on the last, from basic idioms to full interview patterns.

interview_solution.py
# Top 3 most frequent words
# Java: ~12-15 lines. Python:
from collections import Counter

words = ["apple", "banana", "apple",
         "cherry", "banana", "apple"]

top3 = Counter(words).most_common(3)

# Memoized fibonacci — zero boilerplate
import functools

@functools.cache
def fib(n):
    if n <= 1: return n
    return fib(n-1) + fib(n-2)

# Binary search — the template
def binary_search(nums, target):
    lo, hi = 0, len(nums) - 1
    while lo <= hi:
        mid = (lo + hi) // 2
        if nums[mid] == target: return mid
        elif nums[mid] < target: lo = mid + 1
        else: hi = mid - 1
    return -1

Table of Contents

12 Chapters, One Goal

Every chapter targets a specific category of Python knowledge that comes up in interviews — from sorting and collections to graphs and dynamic programming.

CH 00

Python Crash Course for Programmers

Optional: syntax, types, and idioms from day one

CH 01

Sorting

sorted(), key functions, cmp_to_key, stability

CH 02

Pythonic Code

Comprehensions, generators, unpacking, enumerate

CH 03

Lists & Arrays

Slicing, two pointers, in-place operations

CH 04

Strings

Immutability, join, split, sliding window patterns

CH 05

Stacks & Queues

list as stack, deque, monotonic stack patterns

CH 06

Hash Maps & Sets

Counter, defaultdict, OrderedDict, set operations

CH 07

Heaps & Binary Search

heapq, bisect, manual binary search template

CH 08

Itertools

combinations, permutations, accumulate, groupby

CH 09

Functools & Closures

@cache, @lru_cache, reduce, cmp_to_key

CH 10

Math & Bit Manipulation

Integer arithmetic, bit ops, math module patterns

CH 11

Interview Patterns

Two pointers, BFS/DFS, DP, backtracking, graphs

CH 12

Complexity & Gotchas

Big-O of every built-in, common Python traps

BONUS

Algorithms in Python

Trees, graphs, linked lists, tries, union-find

About the Author

Vlad Azarkhin

Principal / Staff Engineer · 25+ Years Experience

Vlad Azarkhin is a Principal/Staff-level software engineer and infrastructure architect with 25+ years of experience spanning distributed systems, infrastructure platforms, performance engineering, and AI-native applications.

He has held senior engineering and architecture roles at Microsoft, Meta, and multiple high-growth startups, and has been on both sides of the technical interview table hundreds of times — as a candidate and as an interviewer.

Read Full Bio →

Python forCodingInterviews

For Engineers Who Already Know How to Code

Python That Wins Interviews

12 Chapters, One Goal

Ready to Ace Your Next Interview?

Python for
Coding
Interviews