Python Performance
Helps with Python, performance 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 athola-python-performance npx -- -y @trustedskills/athola-python-performance
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"athola-python-performance": {
"command": "npx",
"args": [
"-y",
"@trustedskills/athola-python-performance"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The athola-python-performance skill optimizes Python code for improved execution speed and resource utilization. It analyzes existing Python scripts, identifies bottlenecks, and applies techniques like profiling, algorithm optimization, and efficient data structures to enhance performance. The goal is to reduce runtime and improve overall efficiency of Python applications.
When to use it
- Slow Scripts: When a Python script takes an unacceptably long time to complete.
- Resource Intensive Tasks: For scripts that consume excessive memory or CPU resources.
- Performance Bottlenecks: Identifying areas within code where performance can be significantly improved through optimization.
- Large Datasets: Optimizing processing of large datasets in Python applications.
Key capabilities
- Code Profiling
- Algorithm Optimization
- Efficient Data Structure Implementation
- Bottleneck Identification
Example prompts
- "Optimize this Python script for speed: [paste code here]"
- "Analyze the performance of my data processing pipeline and suggest improvements."
- "Identify bottlenecks in this function: [paste function definition]"
Tips & gotchas
The skill requires access to the Python code being analyzed. Complex or heavily reliant on external libraries may require more extensive optimization efforts.
Tags
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Security Audits
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