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Python Optimization Skill for Claude Code

A Claude Code skill that optimizes Python code generation by selecting the most efficient data structures and number handling strategies based on real-world performance and memory characteristics.

Overview

This skill teaches Claude Code to write more efficient Python code by understanding:

  • Memory characteristics of Python numbers and collections
  • Performance implications of different data structures
  • When to use sets vs lists vs dicts
  • Memory optimization techniques like __slots__

Based On

This skill implements best practices from the article "Python Numbers Every Programmer Should Know" by Michael Kennedy.

Key Optimizations

1. Smart Container Selection

  • Sets/Dicts for membership testing: 200x faster than lists for x in container checks
  • Lists for ordered sequences: Most memory-efficient for iteration
  • Proper usage based on access patterns

2. Memory Optimization

  • Use __slots__ for classes with many instances (30% memory reduction)
  • Understanding memory footprint: Lists (36KB) < Sets (59.6KB) < Dicts (90.7KB) per 1000 integers

3. Performance Patterns

  • O(1) lookups with sets/dicts instead of O(n) with lists
  • Efficient counting with Counter or dict
  • Fast unique value extraction with sets

Installation

To use this skill with Claude Code:

  1. Copy python-number-optimization.skill to your Claude Code skills directory:

    • Linux/macOS: ~/.claude/skills/
    • Windows: %USERPROFILE%\.claude\skills\

  2. Or reference it in your project-specific .claude/skills/ directory

Usage

Once installed, Claude Code will automatically apply these optimizations when:

  • You ask for "optimized" or "efficient" Python code
  • Working with collections and data structures
  • The code involves membership testing or lookups
  • Creating classes with many instances

You can also explicitly invoke it:

Use the python-optimization skill to write a function that checks if user IDs are valid

Examples

See examples/ directory for before/after code samples demonstrating:

  • Membership testing optimization
  • Counting and grouping patterns
  • Class memory optimization with __slots__
  • Container selection for different use cases

Performance Quick Reference

Operation Best Container Complexity
Membership test (x in y) Set/Dict O(1)
Ordered iteration List O(n)
Key-value lookup Dict O(1)
Memory-efficient storage List 36KB/1000 ints
Unique values Set O(n) dedup

Contributing

To improve this skill:

  1. Test it with various Python coding scenarios
  2. Submit improvements based on real-world usage
  3. Add more patterns and anti-patterns

License

MIT