profiling-optimization

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Profile application performance, identify bottlenecks, and optimize hot paths using CPU profiling, flame graphs, and benchmarking. Use when investigating performance issues or optimizing critical code paths.

Generalscripts

What this skill does


# Profiling & Optimization

## Table of Contents

- [Overview](#overview)
- [When to Use](#when-to-use)
- [Quick Start](#quick-start)
- [Reference Guides](#reference-guides)
- [Best Practices](#best-practices)

## Overview

Profile code execution to identify performance bottlenecks and optimize critical paths using data-driven approaches.

## When to Use

- Performance optimization
- Identifying CPU bottlenecks
- Optimizing hot paths
- Investigating slow requests
- Reducing latency
- Improving throughput

## Quick Start

Minimal working example:

```typescript
import { performance, PerformanceObserver } from "perf_hooks";

class Profiler {
  private marks = new Map<string, number>();

  mark(name: string): void {
    this.marks.set(name, performance.now());
  }

  measure(name: string, startMark: string): number {
    const start = this.marks.get(startMark);
    if (!start) throw new Error(`Mark ${startMark} not found`);

    const duration = performance.now() - start;
    console.log(`${name}: ${duration.toFixed(2)}ms`);

    return duration;
  }

  async profile<T>(name: string, fn: () => Promise<T>): Promise<T> {
    const start = performance.now();

    try {
      return await fn();
    } finally {
// ... (see reference guides for full implementation)
```

## Reference Guides

Detailed implementations in the `references/` directory:

| Guide | Contents |
|---|---|
| [Node.js Profiling](references/nodejs-profiling.md) | Node.js Profiling |
| [Chrome DevTools CPU Profile](references/chrome-devtools-cpu-profile.md) | Chrome DevTools CPU Profile |
| [Python cProfile](references/python-cprofile.md) | Python cProfile |
| [Benchmarking](references/benchmarking.md) | Benchmarking |
| [Database Query Profiling](references/database-query-profiling.md) | Database Query Profiling |
| [Flame Graph Generation](references/flame-graph-generation.md) | Flame Graph Generation |

## Best Practices

### ✅ DO

- Profile before optimizing
- Focus on hot paths
- Measure impact of changes
- Use production-like data
- Consider memory vs speed tradeoffs
- Document optimization rationale

### ❌ DON'T

- Optimize without profiling
- Ignore readability for minor gains
- Skip benchmarking
- Optimize cold paths
- Make changes without measurement

Files: 9

Size: 10.7 KB

Complexity: 47/100

Category: General

Source: https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/profiling-optimization

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