# Sorting Choice

> Choose the right sorting approach using Python's built-in Timsort, heapq, or custom strategies. Use when sorting arrays, finding top-k elements, or ordering by multiple keys.

- Skill: `knoopx/sorting-choice` (Agent Skill)
- Install (CLI): `npx skillmds@latest add knoopx/sorting-choice`
- Raw SKILL.md: https://api.skillmd.com/api/skills/knoopx/sorting-choice/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: knoopx (https://skillmd.com/u/knoopx)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/knoopx/sorting-choice

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## When to use

Python's built-in sorted()/list.sort() is Timsort — O(n log n), stable, and almost always the right choice.

## Rules

- Use key= for custom ordering
- For top-k elements, use heapq.nlargest/nsmallest (O(n log k)) instead of full sort
- For finding just the kth element, consider quickselect or statistics.median
- Counting sort / radix sort help only when values are bounded integers
- When the problem says "sort by X then by Y," use a tuple key: key=lambda x: (x.a, x.b)
- For reverse on one field only, negate it or use functools.cmp_to_key
- ALWAYS prefer built-in sort — it's optimized and stable
- NEVER implement your own sort algorithm unless the problem requires it

## Complexity

Timsort: O(n log n). heapq.nlargest/nsmallest: O(n log k).

## Example

"Top 3 scores" → `heapq.nlargest(3, scores)` in O(n log 3). "Sort by name then age" → `sorted(items, key=lambda x: (x.name, x.age))`.