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codspeed-setup-harness

Included with Lifetime
$97 forever

Set up performance benchmarks and CodSpeed harness for a project. Use this skill whenever the user wants to create benchmarks, add performance tests, set up CodSpeed, configure codspeed.yml, integrate a benchmarking framework (criterion, divan, pytest-benchmark, vitest bench, go test -bench, google benchmark), or when the user says 'add benchmarks', 'set up perf tests', 'create a benchmark', 'benchmark this', or wants to measure performance of their code for the first time. Also trigger when the optimize skill needs benchmarks that don't exist yet.

Code Review

What this skill does


# Setup Harness

You are a performance engineer helping set up benchmarks and CodSpeed integration for a project. Your goal is to create useful, representative benchmarks and wire them up so CodSpeed can measure and track performance.

## Step 1: Analyze the project

Before writing any benchmark code, understand what you're working with:

1. **Detect the language and build system**: Look at the project structure, package files (`Cargo.toml`, `package.json`, `pyproject.toml`, `go.mod`, `CMakeLists.txt`), and source files.

2. **Identify existing benchmarks**: Check for benchmark files, `codspeed.yml`, CI workflows mentioning CodSpeed or benchmarks.

3. **Identify hot paths**: Look at the codebase to understand what the performance-critical code is. Public API functions, data processing pipelines, I/O-heavy operations, and algorithmic code are good candidates.

4. **Check CodSpeed auth**: Ensure `codspeed auth login` has been run.

## Step 2: Choose the right approach

Based on the language and what the user wants to benchmark, pick the right harness:

### Language-specific harnesses (recommended when available)

These integrate deeply with CodSpeed and provide per-benchmark flamegraphs, fine-grained comparison, and simulation mode support.

| Language    | Framework                                        | How to set up                                                              |
| ----------- | ------------------------------------------------ | -------------------------------------------------------------------------- |
| **Rust**    | divan (recommended), criterion, bencher          | Add `codspeed-<framework>-compat` as dependency using `cargo add --rename` |
| **Python**  | pytest-benchmark                                 | Install `pytest-codspeed`, use `@pytest.benchmark` or `benchmark` fixture  |
| **Node.js** | vitest (recommended), tinybench v5, benchmark.js | Install `@codspeed/<framework>-plugin`, configure in vitest/test config    |
| **Go**      | go test -bench                                   | No packages needed — CodSpeed instruments `go test -bench` directly        |
| **C/C++**   | Google Benchmark                                 | Build with CMake, CodSpeed instruments via valgrind-codspeed               |

### Exec harness (universal)

For any language or when you want to benchmark a whole program (not individual functions):

- Use `codspeed exec -m <mode> -- <command>` for one-off benchmarks
- Or create a `codspeed.yml` with benchmark definitions for repeatable setups

The exec harness requires no code changes — it instruments the binary externally. This is ideal for:

- Languages without a dedicated CodSpeed integration
- End-to-end benchmarks (full program execution)
- Quick setup when you just want to track a command's performance

### Choosing simulation vs walltime mode

- **Simulation** (default for Rust, Python, Node.js, C/C++): Deterministic CPU simulation, <1% variance, automatic flamegraphs. Best for CPU-bound code. Does not measure system calls or I/O.
- **Walltime** (default for Go): Measures real execution time including I/O, threading, system calls. Best for I/O-heavy or multi-threaded code. Requires consistent hardware (use CodSpeed Macro Runners in CI).
- **Memory**: Tracks heap allocations. Best for reducing memory usage. Supported for Rust, C/C++ with libc/jemalloc/mimalloc.

## Step 3: Set up the harness

### Rust with divan (recommended)

1. Add the dependency:

```bash
cargo add divan
cargo add codspeed-divan-compat --rename divan --dev
```

2. Create a benchmark file in `benches/`:

```rust
// benches/my_bench.rs
use divan;

fn main() {
    divan::main();
}

#[divan::bench]
fn bench_my_function() {
    // Call the function you want to benchmark
    // Use divan::black_box() to prevent compiler optimization
    divan::black_box(my_crate::my_function());
}
```

3. Add to `Cargo.toml`:

```toml
[[bench]]
name = "my_bench"
harness = false
```

4. Build and run:

```bash
cargo codspeed build -m simulation --bench my_bench
codspeed run -m simulation -- cargo codspeed run --bench my_bench
```

### Rust with criterion

1. Add dependencies:

```bash
cargo add criterion --dev
cargo add codspeed-criterion-compat --rename criterion --dev
```

2. Create benchmark in `benches/`:

```rust
use criterion::{criterion_group, criterion_main, Criterion};

fn bench_my_function(c: &mut Criterion) {
    c.bench_function("my_function", |b| {
        b.iter(|| my_crate::my_function())
    });
}

criterion_group!(benches, bench_my_function);
criterion_main!(benches);
```

3. Add to `Cargo.toml` and build/run same as divan.

### Python with pytest-codspeed

1. Install:

```bash
pip install pytest-codspeed
# or
uv add --dev pytest-codspeed
```

2. Create benchmark tests:

```python
# tests/test_benchmarks.py
import pytest

def test_my_function(benchmark):
    result = benchmark(my_module.my_function, arg1, arg2)
    # You can still assert on the result
    assert result is not None

# Or using the pedantic API for setup/teardown:
def test_with_setup(benchmark):
    data = prepare_data()
    benchmark.pedantic(my_module.process, args=(data,), rounds=100)
```

3. Run:

```bash
codspeed run -m simulation -- pytest --codspeed
```

### Node.js with vitest (recommended)

1. Install:

```bash
npm install -D @codspeed/vitest-plugin
# or
pnpm add -D @codspeed/vitest-plugin
```

2. Configure vitest (`vitest.config.ts`):

```typescript
import { defineConfig } from "vitest/config";
import codspeed from "@codspeed/vitest-plugin";

export default defineConfig({
  plugins: [codspeed()],
});
```

3. Create benchmark file:

```typescript
// bench/my.bench.ts
import { bench, describe } from "vitest";

describe("my module", () => {
  bench("my function", () => {
    myFunction();
  });
});
```

4. Run:

```bash
codspeed run -m simulation -- npx vitest bench
```

### Go

No packages needed — CodSpeed instruments `go test -bench` directly.

1. Create benchmark tests:

```go
// my_test.go
func BenchmarkMyFunction(b *testing.B) {
    for i := 0; i < b.N; i++ {
        MyFunction()
    }
}
```

2. Run (walltime is the default for Go):

```bash
codspeed run -m walltime -- go test -bench . ./...
```

### C/C++ with Google Benchmark

1. Install Google Benchmark (via CMake FetchContent or system package)

2. Create benchmark:

```cpp
#include <benchmark/benchmark.h>

static void BM_MyFunction(benchmark::State& state) {
    for (auto _ : state) {
        MyFunction();
    }
}
BENCHMARK(BM_MyFunction);

BENCHMARK_MAIN();
```

3. Build and run with CodSpeed:

```bash
cmake -B build && cmake --build build
codspeed run -m simulation -- ./build/my_benchmark
```

### Exec harness (any language)

For benchmarking whole programs without code changes:

1. Create `codspeed.yml`:

```yaml
$schema: https://raw.githubusercontent.com/CodSpeedHQ/codspeed/refs/heads/main/schemas/codspeed.schema.json

options:
  warmup-time: "1s"
  max-time: 5s

benchmarks:
  - name: "My program - small input"
    exec: ./my_binary --input small.txt

  - name: "My program - large input"
    exec: ./my_binary --input large.txt
    options:
      max-time: 30s
```

2. Run:

```bash
codspeed run -m walltime
```

Or for a one-off:

```bash
codspeed exec -m walltime -- ./my_binary --input data.txt
```

## Step 4: Write good benchmarks

Good benchmarks are representative, isolated, and stable. Here are guidelines:

- **Benchmark real workloads**: Use realistic input data and sizes. A sort benchmark on 10 elements tells you nothing about how 10 million elements will perform.

- **Avoid benchmarking setup**: Use the framework's setup/teardown mechanisms to exclude initialization from measurements.

- **Prevent dead code elimination**: Use `black_box()` (Rust), `benchmark::DoNotOptimize` (C++), or `Blackhole.consume` (JMH) so the compiler doesn't optimize away unused results.

- **Cover the critical path**: Benchmark the functions that matter most to your users — the ones called frequently or on the h

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