python-performance-optimization
Profile and optimize Python code using cProfile, memory profilers, and performance best practices.
- Covers CPU profiling with cProfile, line-by-line profiling with line_profiler, memory tracking with memory_profiler, and production profiling with py-spy
- Includes 20+ optimization patterns: list comprehensions, generators, string concatenation, dictionary lookups, NumPy vectorization, caching, multiprocessing, and async I/O
- Provides database optimization techniques including batch operations, query planning, and indexing strategies
- Features memory leak detection with tracemalloc, weak references for caches, and benchmarking tools including custom decorators and pytest-benchmark integration
Python Performance Optimization
Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.
When to Use This Skill
- Identifying performance bottlenecks in Python applications
- Reducing application latency and response times
- Optimizing CPU-intensive operations
- Reducing memory consumption and memory leaks
- Improving database query performance
- Optimizing I/O operations
- Speeding up data processing pipelines
- Implementing high-performance algorithms
- Profiling production applications
Core Concepts
1. Profiling Types
More from wshobson/agents
tailwind-design-system
Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.
41.0Ktypescript-advanced-types
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.
40.4Knodejs-backend-patterns
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
31.8Kapi-design-principles
Master REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.
20.3Kpython-testing-patterns
Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
19.7Kcode-review-excellence
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
17.3K