Build direction isn’t just about performance—it determines what’s even possible. Understand how to choose between top-down, bottom-up, and hybrid strategies when constructing trees from data.
Start With This Excellent Explanation
🧠 The Problem: Efficiently Diffing Large Arrays
Explore multiple techniques for converting flat or semi-structured data into trees in Python, including recursive, map-based, and bottom-up builds like Merkle trees.
How reframing recursion as structure, not control flow, finally made graph traversal click for me.
Hash maps aren’t fast because of magic or randomness — they’re fast because hashing is deterministic. Learn why this property powers O(1) lookups, Bloom filters, and consistent hashing.
Heaps are binary trees, so why aren't they stored like one? Discover why arrays are the perfect data structure for implementing heaps — and how heaps work in the first place.