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.