# Code Profiler

> Use when asked to profile Python code performance, identify bottlenecks, measure execution time, or analyze function call statistics.

- Skill: `majiayu000/code-profiler` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds add majiayu000/code-profiler`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/code-profiler/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/majiayu000/code-profiler

---


# Code Profiler

Analyze Python code performance, identify bottlenecks, and optimize execution with comprehensive profiling tools.

## Purpose

Performance analysis for:
- Bottleneck identification
- Function execution time measurement
- Memory usage profiling
- Call graph visualization
- Optimization validation

## Features

- **Time Profiling**: Measure function execution times
- **Line-by-Line Analysis**: Profile each line of code
- **Call Statistics**: Function call counts and cumulative time
- **Memory Profiling**: Track memory allocation and usage
- **Flamegraph Visualization**: Visual call stack analysis
- **Comparison**: Before/after optimization comparison

## Quick Start

```python
from code_profiler import CodeProfiler

# Profile function
profiler = CodeProfiler()
profiler.profile_function(my_function, args=(arg1, arg2))
profiler.print_stats(top=10)

# Profile script
profiler.profile_script('script.py')
profiler.export_report('profile_report.html')
```

## CLI Usage

```bash
# Profile Python script
python code_profiler.py script.py

# Profile with line-by-line analysis
python code_profiler.py script.py --line-by-line

# Export HTML report
python code_profiler.py script.py --output report.html
```