/run-profiler

Run Profiler Command

Usage

Profiles Python code for performance bottlenecks using cProfile, memory_profiler, or py-spy.

Basic Usage

/run-profiler script.py

Runs CPU profiling on the specified script.

With Options

/run-profiler --memory script.py
/run-profiler --line function_name script.py

What It Does

1. **CPU Profiling**: Identifies time-consuming functions 2. **Memory Profiling**: Tracks memory allocations and leaks 3. **Line Profiling**: Profile specific functions line-by-line 4. **Flamegraph Generation**: Visual representation of call stacks 5. **Recommendations**: Suggests optimization patterns

Profiling Modes

CPU Mode (default)

/run-profiler script.py

Uses cProfile to identify slow functions.

Memory Mode

/run-profiler --memory script.py

Uses memory_profiler to track allocations.

Line Mode

/run-profiler --line expensive_function script.py

Uses line_profiler for detailed analysis.

Production Mode

/run-profiler --pid 12345

Uses py-spy for profiling running processes.

Output Format

• **Top Functions**: Ranked by cumulative time
• **Memory Usage**: Peak and average consumption
• **Hotspots**: Specific lines causing issues
• **Recommendations**: Optimization suggestions

Examples

# Profile with top 20 functions
/run-profiler --top 20 main.py

# Generate flamegraph
/run-profiler --flamegraph output.svg main.py

# Memory profile with threshold
/run-profiler --memory --threshold 100MB main.py

Integration

Uses the `python-performance` skill's profiling tools:

• `profiler-runner`: cProfile and py-spy execution
• `memory-analyzer`: Memory usage analysis
• `benchmark-suite`: Comparative benchmarking

This command helps identify and resolve performance bottlenecks efficiently.