8 docs tagged with "performance"

A side-by-side look at iteration patterns across JavaScript, Python, Go, and C++, comparing lambdas, traditional for loops, method chaining, and the tradeoffs between readability, control, and performance.

🧠 The Problem: Efficiently Diffing Large Arrays

See why hash maps feel instant compared to scanning a list or walking a tree — and why trees still have their place.

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.

A practical framework for understanding where performance optimization actually matters—and where it doesn’t.

Compare recursive tree traversal with and without generators, highlighting performance and readability tradeoffs.

DSA and Big-O notation aren't just for interviews — they directly impact real-world performance and costs, from serverless runtime billing to optimizing data pipelines. This article explores their practical value through personal experience and potential demos.

Performance tuning isn’t about speed — it’s about discovery. Pushing systems to their limits forces you to uncover hidden behaviors, go deep, and master the fundamentals.