// the find
MTrajK/coding-problems
Solutions for various coding/algorithmic problems and many useful resources for learning algorithms and data structures
A personal collection of LeetCode-style algorithm solutions in Python 3, paired with a hand-picked list of courses, books, and practice sites. It's for developers preparing for technical interviews or filling gaps in their algorithms knowledge, not for production use.
Each solution file follows a consistent template with problem statement, complexity analysis, and multiple approaches side by side — unusually disciplined for a personal repo. The resource section is genuinely useful: Stanford, MIT, and Princeton course links alongside book recommendations that are actually worth reading (CLRS, Skiena, Grokking). Solutions stick to stdlib only (collections, heapq, math), so there's nothing to install and the code is easy to port to another language. Multiple solutions per problem with explicit time/space complexity comparisons is more educational than just shipping the optimal answer.
No tests beyond print statements — the README acknowledges this and gestures at unittest, but none of the files actually use it, so you can't run the whole suite to verify nothing's broken. Coverage is thin in places: the Hashing DS section has 9 files, Trees has 11, while harder topics like graph algorithms (Dijkstra, topological sort, union-find) are mostly absent or buried in 'Other'. The repo hasn't had meaningful new solutions since mid-2023 based on the commit history, so it won't cover problems added to LeetCode in the last two years. Python-only by design, which is fine for learning but means someone prepping in Java or Go gets the logic but has to do the translation themselves.