Algorithm efficiency

How the work an algorithm does grows as its input grows - linear, quadratic, constant - measured by counting steps and written in Big-O, which decides whether a program that is instant on small data can cope with real data.

Depth 1 · Foundation

You can count the steps of a loop and of nested loops, predict what doubling the input does, time code with time.perf_counter, name O(1), O(n) and O(n²), and spot a hidden loop like x in some_list.

Depths of understanding

1
Foundation
You can count the steps of a loop and of nested loops, predict what doubling the input does, time code with time.perf_counter, name O(1), O(n) and O(n²), and spot a hidden loop like x in some_list.
Opens after
AlgorithmEfficiency is a property of an algorithm, a method with exact steps, so meet algorithms first.Sets in codeThe classic fast fix replaces a search through a list with a set, so you need sets first.

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What's still between you and Algorithm efficiency, depth 1, in the order you can learn it.

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Algorithm efficiencyAlgorithms

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Builds onThis conceptOpens upAlgorithm Sets in codeData Structures Algorithm efficiencyAlgorithms Binary search Sorting