Lesson 15 — Heap / priority

Priority queue: most urgent first

A priority queue always hands you the most important item next, not the oldest. Python's heapq keeps a list arranged as a heap, where the smallest item is always at position 0. Push tuples (priority, task): tuples compare by their first item, so priority 1 comes out before priority 3.

import heapq
h = []
heapq.heappush(h, (2, "email"))
heapq.heappush(h, (1, "fire!"))
heapq.heappop(h)   # (1, 'fire!')

Why it matters: hospital triage, OS schedulers and Dijkstra's algorithm all need "give me the most urgent".