Python Performance Optimization
Helps with Python, performance optimization, optimization as part of developing backend services and APIs workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add prof-ramos-python-performance-optimization npx -- -y @trustedskills/prof-ramos-python-performance-optimization
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"prof-ramos-python-performance-optimization": {
"command": "npx",
"args": [
"-y",
"@trustedskills/prof-ramos-python-performance-optimization"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill helps optimize Python code for improved performance. It identifies bottlenecks in existing code, suggests efficient algorithms and data structures, and provides guidance on profiling techniques to pinpoint areas needing improvement. The skill aims to reduce execution time and resource consumption of Python applications.
When to use it
- You have a slow-running Python script or application that needs to be faster.
- You're encountering performance bottlenecks in your data processing pipelines.
- You want to understand how to profile your Python code to identify areas for optimization.
- You need help choosing the most efficient algorithms and data structures for a specific task.
Key capabilities
- Code profiling suggestions
- Algorithm selection guidance
- Data structure recommendations
- Bottleneck identification
Example prompts
- "Analyze this Python code snippet and suggest performance improvements."
- "What are some more efficient alternatives to using lists in this scenario?"
- "How can I profile my Python script to find the slowest parts?"
Tips & gotchas
The skill requires access to the Python code you want to optimize. Be prepared to provide clear examples and context for best results.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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