Data structures & algorithms.
Each data structure from the first idea to expert level, with interactive demos, exercises and where it shows up in real systems.
In study order. Each article starts at beginner level, so you can begin anywhere.
Big-O notation, from first idea to production
How to read time and space complexity, from counting loop steps to amortized analysis, query plans and N+1 bugs, with demos and production code.
Hash maps, from first idea to production
How hash maps and sets work, from a coat check to CPython's dict, Swiss tables and hash flooding, with demos, exercises and real production code.
The two pointers technique, from first idea to production
How two pointers work, from reversing a string to Floyd's cycle detection, PostgreSQL merge joins and one-pass sync diffs, with demos and exercises.
The sliding window technique, from first idea to production
How the sliding window technique works, from a running sum to monotonic deques, stream windows and TCP, with step-through demos and real production code.
Binary search, from first idea to production
How binary search works, from a guessing game to bisect, answer-space search, cache-friendly layouts, B-tree indexes and git bisect, with demos.
Heaps and priority queues, from first idea to production
How heaps and priority queues work, from ER triage to heapq, heapify, Dijkstra, timing wheels and the asyncio scheduler, with demos and production code.