Sorting Algorithms Tutorial

This course is for developers who already write Python comfortably and want to understand sorting properly rather than memorise a table of complexities. It suits interview preparation, but it is aimed at the habit behind good answers: measure what an algorithm does, explain why, and know when not to write your own.

You will implement the simple quadratic sorts and count their comparisons to see why they are slow, build merge sort and quicksort and watch pivot choice decide between fast and catastrophic, learn why counting and radix sort can legitimately beat the O(n log n) barrier, and finish with what you will actually use in production: Python's stable sorted(), key functions and multi-key ordering.

The lessons run from simple to practical. First the quadratic sorts and why they cost what they cost, then the divide-and-conquer sorts, then the non-comparison sorts, then stability and Timsort. Every snippet is complete Python and its output was produced by running it, with counters instead of stopwatches so the numbers are repeatable. For background, see Data Structures and Arrays and Strings.