16h ago · 26 min read · TLDR: Python's four built-in collections are not interchangeable — their internals are fundamentally different. list is a dynamic array: fast at the end, slow for membership. dict is a hash table: O(1) key lookup, insertion-order-preserving since Pyt...
Join discussionApr 5 · 30 min read · TLDR: Probabilistic data structures — Bloom Filters, Count-Min Sketch, HyperLogLog, and Cuckoo Filters — trade a small, bounded probability of being wrong for orders-of-magnitude better memory efficiency and O(1) speed. Bloom filters answer "definite...
Join discussionApr 5 · 32 min read · TLDR: Big O notation describes how an algorithm's resource usage grows as input size grows — not how fast it runs on your laptop. Learn to identify the 7 complexity classes (O(1) through O(n!)), derive time and space complexity by counting loops and ...
Join discussionMar 31 · 5 min read · Imagine that you are using Google Maps while you are driving somewhere, and suddenly there's a road blockage. In this case Google Maps quickly reroutes and gives a new route where there is no blockage
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Mar 30 · 8 min read · Every app you have ever built is secretly doing mathematics you never signed up to learn. Not in a frightening way. The mathematics was always there, running quietly underneath the architecture decisi
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