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