Algorithms in Python

Build your algorithm skills in Python with hands-on tutorials that cover sorting, searching, graphs, greedy techniques, and dynamic programming. You will learn to think in Big O, pick the right data structures, and turn pseudocode into clean, Pythonic solutions you can ship and discuss in interviews.

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Work with battle-tested tools from the standard library to write fast, readable code. Use heapq for priority queues, bisect for binary search, collections.deque for BFS, itertools for combinatorics, and functools.lru_cache for memoization. Measure real performance with timeit and cProfile, and reach for NumPy or NetworkX when vectorization or graph tooling helps.

Browse all resources below, or commit to a guided Learning Path with progress tracking: