Python Interview Algorithms Workbook

Clean, idiomatic Python implementations for senior/staff-level interview prep with complexity notes, pitfalls, demos, and tests.

Quick Navigation

• Engineering Study Plan - Structured study guide from Intern to Principal level
• Algorithms Portfolio - Complete portfolio of algorithm implementations
• Learning Path - 2-3 week structured learning plan with checkpoints
• Consistency Models - Distributed systems consistency patterns
• System Design Guide - Interview system design preparation
• NeetCode Top 100 - Must-know LeetCode problems

Modules Overview

• algorithms/sorting - Comparison (merge, quick, heap, insertion, selection, bubble) and non-comparison (counting, radix)
• algorithms/searching - Binary search family, advanced search, selection algorithms
• data_structures - Union-Find (DSU), Trie, LRU/LFU caches, Fenwick tree, Segment tree
• graphs - BFS/DFS, Topological sort, Dijkstra, A*, Bellman-Ford, Floyd-Warshall, MST, SCC
• dp - Fibonacci, coin change, LIS, knapsack, edit distance, bitmask TSP, LCS
• strings - KMP, Rabin-Karp, Z-algorithm, Manacher, suffix array/LCP
• math_utils - Sieve, GCD/LCM, modular arithmetic, prefix sums
• patterns - Sliding window, monotonic stack/queue, two pointers, backtracking
• systems/concurrency - Reservoir sampling, rate limiters, consensus notes

Getting Started

Install (editable) and run tests:

python -m pip install -U pip
python -m pip install -e .
pytest -q

Run demos:

python src/main.py --list
python src/main.py --demo sorting.merge_sort
python src/main.py --demo searching.binary_search
python src/main.py --demo dp.lcs
python src/main.py --demo graphs.scc

Repository

For the full source code and contributions, visit the GitHub repository.