performance-profiling

name	performance-profiling
description	Measuring CPU performance metrics and memory bottlenecks in Python code blocks.
allowed-tools	Read Write Edit Bash
license	MIT license
metadata	{"skill-author":"Lord1Egypt"}

Performance Profiling

Overview

Profiling calculates statistics of code execution, revealing bottleneck processes.

When to Use This Skill

Use to analyze slow mathematical scripts, inspect pillow memory footprint, or optimize algorithms.

Quick Start (with runnable code examples)

import cProfile

def count_primes():
    primes = []
    for num in range(2, 5000):
        if all(num % i != 0 for i in range(2, int(num**0.5) + 1)):
            primes.append(num)
    return len(primes)

# Run profile statistics output
cProfile.run('count_primes()')

Advanced Usage

Use line_profiler to trace memory and speed per script line, investigate memory leaks via tracemalloc, and generate flamegraphs.

Key References

• Python Profiling documentation

Dependencies

• Python Standard Library