Divan ⭐

Installation

important

For all Rust integrations, you will need the cargo-codspeed command to build and run your CodSpeed benchmarks

Install the divan compatibility layer:

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

Or directly change your Cargo.toml if you already have divan installed:

[dev-dependencies]
divan = { version = "*" }
divan = { package = "codspeed-divan-compat", version = "*" }

This will install the codspeed-divan-compat crate and rename it to divan in your Cargo.toml. This way, you can keep your existing imports and the compatibility layer will take care of the rest.

tip

Using the compatibility layer won't change the behavior of your benchmark suite outside of the CodSpeed instrumentation environment and divan will still run it as usual.

note

If you prefer, you can also install codspeed-divan-compat as is and change your imports to use this new crate name.

Usage

Creating benchmarks

As an example, let's follow the example from the divan documentation: a benchmark suite for the Fibonacci function:

benches/my_benchmark.rs

fn main() {
    // Run registered benchmarks.
    divan::main();
}

// Register a `fibonacci` function and benchmark it over multiple cases.
#[divan::bench(args = [1, 2, 4, 8, 16, 32])]
fn fibonacci(n: u64) -> u64 {
    if n <= 1 {
        1
    } else {
        fibonacci(n - 2) + fibonacci(n - 1)
    }
}

The last step in creating the divan benchmark is to add the new benchmark target in your Cargo.toml:

Cargo.toml

[[bench]]
name = "my_benchmark"
harness = false

And that's it! You can now run your benchmark suite with CodSpeed

Testing the benchmarks locally

Congrats ! 🎉 You can now run those benchmark in your CI to get the actual performance measurements.

Running the benchmarks in your CI

To generate performance reports, you need to run the benchmarks in your CI. This allows CodSpeed to detect the CI environment and properly configure the instrumented environment.

tip

If you want more details on how to configure the CodSpeed action, you can check out the Continuous Reporting section.

Here is an example of a GitHub Actions workflow that runs the benchmarks and reports the results to CodSpeed on every push to the main branch and every pull request:

.github/workflows/codspeed.yml

name: CodSpeed

on:
  push:
    branches:
      - "main" # or "master"
  pull_request:
  # `workflow_dispatch` allows CodSpeed to trigger backtest
  # performance analysis in order to generate initial data.
  workflow_dispatch:

jobs:
  benchmarks:
    name: Run benchmarks
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Setup rust toolchain, cache and cargo-codspeed binary
        uses: moonrepo/setup-rust@v1
        with:
          channel: stable
          cache-target: release
          bins: cargo-codspeed

      - name: Build the benchmark target(s)
        run: cargo codspeed build

      - name: Run the benchmarks
        uses: CodSpeedHQ/action@v3
        with:
          run: cargo codspeed run
          token: ${{ secrets.CODSPEED_TOKEN }}

Advanced usage

Divan provides a lot of convenient features to help you write benchmars, below is a selection that can be useful in CodSpeed benchmarks, but check out the divan documentation for an exhaustive list of features.

Type generics

benches/types.rs

#[divan::bench(types = [&str, String])]
fn from_str<'a, T>() -> T
where
    T: From<&'a str>,
{
    divan::black_box("hello world").into()
}

Combining type generics and arguments

benches/types_and_args.rs

use std::collections::{BTreeSet, HashSet};

#[divan::bench(
    types = [Vec<i32>, BTreeSet<i32>, HashSet<i32>],
    args = [0, 2, 4, 16, 256, 4096],
)]
fn from_range<T>(n: i32) -> T
where
    T: FromIterator<i32>,
{
    (0..n).collect()
}

Generating dynamic inputs

Time spent generating inputs is not measured in benchmarks.

benches/with_inputs.rs

#[divan::bench]
fn bench(bencher: divan::Bencher) {
    bencher
        .with_inputs(|| {
            // Generate input:
            String::from("...")
        })
        .bench_values(|s| {
            // Use input by-value:
            s + "123"
        });
}

Recipes

Running benchmarks in parallel CI jobs

With Rust, if you use multiple packages, a first sharding optimization is to split your benchmarks across these packages.

For example, using Github Actions:

jobs:
  benchmarks:
    name: Run benchmarks
    runs-on: ubuntu-latest
    strategy:
      matrix:
        package:
          - my-first-package
          - my-second-package
    steps:
      - uses: actions/checkout@v4

      - name: Setup rust toolchain, cache and cargo-codspeed binary
        uses: moonrepo/setup-rust@v1
        with:
          channel: stable
          cache-target: release
          bins: cargo-codspeed

      - name: Build the benchmark target(s)
        run: cargo codspeed build -p ${{ matrix.package }}
        run: cargo codspeed build

      - name: Run the benchmarks
        uses: CodSpeedHQ/action@v3
        with:
          # Note: it is not required to pass a `-p` flag as only the benchmarks
          # built by `cargo codspeed build` will be run
          run: cargo codspeed run
          token: ${{ secrets.CODSPEED_TOKEN }}

For more information about multiple packages, check the cargo-codspeed docs.

warning

For now, you cannot run the same benchmarks several times within the same run. If the same benchmark is run multiple times, you will receive the following comment on your pull request:

Learn more about benchmark sharding and how to integrate with your CI provider.