A structured practice repository for data structures and algorithms in Python, picking up where the original leetcode repo left off. The goal wasn’t just to collect solutions, it was to build a codebase I’d be comfortable showing in an interview: tested, documented, and idiomatic.
32 problems solved, at the time of this writing, across 7 Easy, 23 Medium, and 2 Hard.
What makes this different from a solution dump
Every solution file includes the full problem statement, examples, constraints, and explicit time/space complexity analysis in the docstring. And every solution has a paired test file, not as an afterthought, but as a design constraint from the start.
A shared utils/ library abstracts the boilerplate of building tree and list structures
for tests:
root = TreeNode.from_list([3, 9, 20, None, None, 15, 7])
assert Solution().maxDepth(root) == 3TreeNode, ListNode, and graph node classes include structural __eq__ so assertions
read naturally without manual traversal.
Idiomatic Python patterns
Solutions lean on the standard library rather than reinventing primitives:
collections.dequefor O(1)popleftin BFSheapqfor priority queuesbisectfor binary search on sorted datacollections.Counteranddefaultdictfor frequency maps- Comprehensions and slicing over manual index arithmetic
Notable implementations
Median of Two Sorted Arrays (#4) — O(log(min(m, n))) binary search on partitions rather than the naive O(m+n) merge.
LRU Cache (#146) — dict + doubly linked list for O(1) get, put, and evict.
Course Schedule I & II (#207, #210) — Topological sort via DFS cycle detection.
Word Ladder (#127) — BFS shortest path across a word graph.
Topics covered
Arrays, binary search, binary trees, bit manipulation, dynamic programming, graph search (BFS/DFS), linked lists, matrices, stacks, strings, and tries.
Tooling
CI runs ruff (lint + format), pyright, and pytest on every push. On main merges,
the workflow auto-commits an updated progress table to the README. Built on Python 3.12+
with uv for dependency management.