| 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
profiler = CodeProfiler()
profiler.profile_function(my_function, args=(arg1, arg2))
profiler.print_stats(top=10)
profiler.profile_script('script.py')
profiler.export_report('profile_report.html')
CLI Usage
python code_profiler.py script.py
python code_profiler.py script.py --line-by-line
python code_profiler.py script.py --output report.html
