Brunch is a very simple Rust micro-benchmark runner inspired by easybench. It has roughly a million times fewer dependencies than criterion, does not require nightly, and maintains a (single) "last run" state for each benchmark, allowing it to show relative changes from run-to-run.

(The formatting is also quite pretty.)

As with all Rust benchmarking, there are a lot of caveats, and results might be artificially fast or slow. For best results:

• Build optimized;
• Collect lots of samples;
• Repeat identical runs to get a feel for the natural variation;

Brunch cannot measure time below the level of a nanosecond, so if you're trying to benchmark methods that are really fast, you may need to wrap them in a method that runs through several iterations at once. For example:

use brunch::Bench;

///# Generate Strings to Test.
fn string_seeds() -> Vec<String> {
    (0..10_000_usize).into_iter()
        .map(|i| "x".repeat(i))
        .collect()
}

///# Generate Strings to Test.
fn byte_seeds() -> Vec<Vec<u8>> {
    (0..10_000_usize).into_iter()
        .map(|i| "x".repeat(i).into_bytes())
        .collect()
}

brunch::benches!(
    Bench::new("String::len(_)")
        .run_seeded_with(string_seeds, |vals| {
            let mut len: usize = 0;
            for v in vals {
                len  = v.len();
            }
            len
        }),
    Bench::new("Vec::len(_)")
        .run_seeded_with(byte_seeds, |vals| {
            let mut len: usize = 0;
            for v in vals {
                len  = v.len();
            }
            len
        }),
);

Add brunch to your dev-dependencies in Cargo.toml, like:

[dev-dependencies]
brunch = "0.6.*"

Benchmarks should also be defined in Cargo.toml. Just be sure to set harness = false for each:

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

The following optional environmental variables are supported:

The heart of Brunch is the Bench struct, which defines a single benchmark. There isn't much configuration required, but each Bench has the following:

The struct uses builder-style methods to allow everything to be set in a single chain. You always need to start with Bench::new and end with one of the runner methods — Bench::run, Bench::run_seeded, or Bench::run_seeded_with. If you want to change the sample or timeout limits, you can add Bench::with_samples or Bench::with_timeout in between.

There is also a special Bench::spacer method that can be used to inject a linebreak into the results. See below for an example.

The benches! macro is the easiest way to run Brunch benchmarks.

Simply pass a comma-separated list of all the Bench objects you want to run, and it will handle the setup, running, tabulation, and give you a nice summary at the end.

By default, this macro will generate the main() entrypoint too, but you can suppress this by adding "inline:" as the first argument.

Anyhoo, the default usage would look something like the following:

use brunch::{Bench, benches};

// Example benchmark adding 2 2.
fn callback() -> Option<usize> { 2_usize.checked_add(2) }

// Example benchmark multiplying 2x2.
fn callback2() -> Option<usize> { 2_usize.checked_mul(2) }

// Let the macro handle everything for you.
benches!(
    Bench::new("usize::checked_add(2)")
        .run(callback),

    Bench::new("usize::checked_mul(2)")
        .run(callback2),
);

When declaring your own main entrypoint, you need to add "inline:" as the first argument. The list of Bench instances follow as usual after that.

use brunch::{Bench, benches};

/// # Custom Main.
fn main() {
    // A typical use case for the "inline" variant would be to declare
    // an owned variable for a benchmark that needs to return a reference
    // (to e.g. keep Rust from complaining about lifetimes).
    let v = vec![0_u8, 1, 2, 3, 4, 5];

    // The macro call goes here!
    benches!(
        inline:

        Bench::new("vec::as_slice()").run(|| v.as_slice()),
    );

    // You can also do other stuff afterwards if you want.
    eprintln!("Done!");
}

For even more control over the flow, skip the macro and just use Benches directly.

If you run the example benchmark for this crate, you should see a summary like the following:

Method                         Mean    Change        Samples
------------------------------------------------------------
fibonacci_recursive(30)     2.22 ms     1.02%    2,408/2,500
fibonacci_loop(30)         56.17 ns       ---    2,499/2,500

The Method column speaks for itself, but the numbers deserve a little explanation:

See also: CREDITS.md

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This work is free. You can redistribute it and/or modify it under the terms of the Do What The Fuck You Want To Public License, Version 2.

DO WHAT THE FUCK YOU WANT TO PUBLIC LICENSE
Version 2, December 2004

Copyright (C) 2004 Sam Hocevar <[email protected]>

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