code-perf

Code Perf

Performance profiling and optimization workflow.

The Golden Rule

Never optimize without profiling.

You don't know where the bottleneck is until you measure. Making changes without profiling wastes time and often makes things worse.

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Workflow

1. Profile

Measure the current performance.

Questions:

• What's slow? (endpoint, operation, page load)
• How slow? (latency, throughput)
• Under what conditions? (load, data size)

Tools:

• Browser DevTools (Performance tab)
• Node clinic.js
• Python cProfile
• Go pprof

2. Identify

Find the hot paths.

Look for:

• Functions called many times
• Large memory allocations
• Blocking I/O
• Unnecessary computations

3. Optimize

Apply the right optimization pattern.

4. Verify

Re-profile to confirm improvement.

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Common Bottlenecks

See references/common-bottlenecks.md for detailed patterns:

Pattern	Symptom	Solution
N+1	Multiple DB queries	Eager load, batch
Memory leak	Growing RSS	Clear caches, weak refs
Blocking I/O	Thread blocked	Async, worker pool
Unnecessary work	CPU high	Skip redundant calc
Large data	Slow serialization	Pagination, streams

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Optimization Patterns

See references/optimization-patterns.md for:

Caching

// Before: every call hits DB
const user = await db.users.find(id);

// After: cache
const cacheKey = `user:${id}`;
let user = await redis.get(cacheKey);
if (!user) {
  user = await db.users.find(id);
  await redis.set(cacheKey, user, 'EX', 300);
}

Lazy Loading

// Before: load everything
const allUsers = await db.users.findMany();

// After: paginate
const users = await db.users.findMany({
  take: 20,
  skip: page * 20
});

Connection Pooling

// Before: new connection each time
const client = new Client();
await client.connect();

// After: pool
const pool = new Pool({ max: 20 });
// Use pool.query() throughout

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Profiling Tools

See references/profiling-tools.md for:

Node.js

# CPU profiling
node --prof app.js

# Memory
node --inspect app.js  # Chrome DevTools

# clinic.js
npx clinic doctor -- node app.js

Python

# cProfile
python -m cProfile -o profile.prof app.py

# view with: python -m cProfile -s cumulative app.py

Go

# pprof
go test -cpuprofile=cpu.prof
go tool pprof cpu.prof

# Web interface
go tool pprof -http=:8080 cpu.prof

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Skill Loading

• If optimization involves queries → load python-sqlalchemy or typescript-drizzle-orm
• If memory issues → load for heap snapshots
• If database → load appropriate database skill