Sorting by key: how engineers actually sort

Sorting by key

Real-world sorting is rarely about bare numbers — it is about records: users by signup date, posts by score, files by size. You will write a keyed sort at work this week, guaranteed. Python's sorted handles it with the key argument: a function that, given one item, returns the value to sort by. sorted(words, key=len) sorts words by length because Python calls len on each word and orders by those results.

The rules that make key powerful:

• The key function runs once per item; the O(n log n) comparisons then happen between the precomputed key values. Even an expensive key stays affordable.
• Keys can be tuples, which compare position by position. key=lambda s: (-s[1], s[0]) means "by score, highest first (negating a number reverses its order), then by name A→Z among ties".
• reverse=True flips the entire order when negation is awkward (strings cannot be negated).

There is no separate algorithm to learn here: every sort in this unit simply routes its comparisons through the key.

Stability: the invisible guarantee

A sort is stable when items that compare equal keep their original left-to-right order. Python's sort is guaranteed stable, and that guarantee is a tool: to sort by several criteria you can sort by the secondary key first, then by the primary key — the second sort preserves the first sort's order among ties.

Why you care: league tables, spreadsheets, paginated feeds ("order by score, newest first among ties"). With an unstable sort, equal-score rows would shuffle on every re-sort, and users file that as a bug.

Look back at the first output above: pear came before kiwi (both length 4) precisely because pear came first in the input. That is stability in action.