Python's Built-In ADTs: heapq, bisect, and dict/set in Practice

This unit has derived the cost guarantees of heaps, hash tables, and balanced search trees from first principles — the point of this closing lesson is to map those guarantees directly onto what a quant researcher actually types: heapq, bisect, dict, and set. Per this unit's "quant-practice-track" framing, most day-to-day work leans on these standard-library structures rather than hand-rolled red-black or B-trees, and knowing exactly which cost table each one inherits — and where the standard library has no built-in equivalent (an augmented balanced tree, notably) — is what turns the preceding lessons into usable engineering judgement rather than trivia.