name: code-profiler
description: Use when asked to profile Python code performance, identify bottlenecks, measure execution time, or analyze function call statistics.

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

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

# 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