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Maelstrom is a suite of tools for running tests in isolated micro-containers
locally on your machine or distributed across arbitrarily large clusters.
Maelstrom currently has test runners for Rust, Go, and Python, with more on the
way. You might use Maelstrom to run your tests because:

It's easy. Maelstrom provides drop-in replacements for cargo test, go test, and pytest. In most cases, it just works with your existing tests
with minimal configuration.
It's reliable. Maelstrom runs every test isolated in its own lightweight
container, eliminating confusing errors caused by inter-test or implicit
test-environment dependencies.
It's scalable. Maelstrom can be run as a cluster. You can add more worker
machines to linearly increase test throughput.
It's clean. Maelstrom has built a rootless container implementation (not
relying on Docker or RunC) from scratch, in Rust, optimized to be
low-overhead and start quickly.
It's fast. In most cases, Maelstrom is faster than cargo test or go test, even without using clustering. Maelstrom’s test-per-process model is
inherently slower than pytest’s shared-process model, but Maelstrom
provides test isolation at a low performance cost.

While our focus thus far has been on running tests, Maelstrom's underlying
job execution system is general-purpose. We provide a command
line utility to run arbitrary commands, as well a gRPC-based API and Rust
bindings for programmatic access and control.

The project is currently Linux-only (x86 and ARM), as it relies on namespaces
to implement containers.

See the book for more information.

Provide Feedback

We want to learn how you want to use Maelstrom! Your feedback helps us prioritize features, expand the languages we support, and improve the overall experience for developers like you. Share your insight with this quick survey.

Getting Started

Installing Pre-Built Binaries

To run your tests using Maelstrom, you need a test runner binary.
The easiest way to get it is using
cargo-binstall:

For Rust tests:

bash
cargo binstall cargo-maelstrom

For Go tests:

bash
cargo binstall maelstrom-go-test

For Python tests:

bash
cargo binstall maelstrom-pytest

This will install a pre-built binary from the github releases page.

If you're on Arch Linux, you can install a package using pacman:

bash
pacman -S cargo-maelstrom
pacman -S maelstrom-go-test
pacman -S maelstrom-pytest

If you don't have cargo-binstall, you can download the binaries manually.

Check out the book for more ways to get Maelstrom.

Running `cargo-maelstrom`

To run your Rust tests, use cargo-maelstrom:

bash
cargo maelstrom

This runs in "standalone" mode, meaning all tests are run locally. Each test is
run in its own container, configured with a few common dependencies. It may
work for your project without any further configuration.

If some tests fail, however, it likely means those tests have dependencies on
their execution environment that aren't packaged in their containers.
You can remedy this by adding directives to the cargo-maelstrom.toml file. To
do this, run:

bash
cargo maelstrom --init

Then edit the created cargo-maelstrom.toml file as described in the
book.

Running `maelstrom-go-test`

To run your Go tests, use maelstrom-go-test:

bash
maelstrom-go-test

If some tests fail, however, it likely means those tests have dependencies on
their execution environment that aren't packaged in their containers. You can
remedy this by adding directives to the maelstrom-go-test.toml file. To do
this, run:

bash
maelstrom-go-test --init

Then edit the created maelstrom-go-test.toml file as described in the
book.

Running `maelstrom-pytest`

Before running tests, we need to do a little setup.

Choosing a Python Image

First generate a maelstrom-pytest.toml file

bash
maelstrom-pytest --init

Then update the image in the file to have the version of Python you desire.

toml
[[directives]]
image = "docker://python:3.11-slim"

The default configuration and our example uses an
image from Docker

Including Your Project Python Files

So that your tests can be run from the container, your project's python must be included.
Update the added_layers in the file to make sure it includes your project's Python.

toml
added_layers = [ { glob = "**.py" } ]

This example just adds all files with a .py extension. You may also need to include .pyi files
or other files.

Including `pip` Packages

If you have an image named "python", maelstrom-pytest will automatically include pip packages for
you as part of the container. It expects to read these packages from a test-requirements.txt file
in your project directory. This needs to at a minimum include the pytest package

test-requirements.txt

pytest==8.1.1

Now we are ready to try to run tests. Just invoke maelstrom-pytest:

bash
maelstrom-pytest

This runs in "standalone" mode, meaning all tests are run locally. Each test is run in its own
container.

Running Tests

Once you have finished the configuration, you only need invoke maelstrom-pytest to run all the
tests in your project. It must be run from an environment where pytest is in the Python path. If
you are using virtualenv for your project make sure to source that first.

Setting Up a Cluster

To get even more out of Maelstrom, you can set up a cluster to run your tests on.
You will need to run one copy of the broker (maelstrom-broker) somewhere, and
one copy of the worker (maelstrom-worker) on each node of the cluster.

You can install these using multiple
methods,
including cargo-binstall:

bash
cargo binstall maelstrom-worker maelstrom-broker

Then you can start the broker:

bash
maelstrom-broker --port=1234

Then a few workers:

bash
maelstrom-worker --broker=broker-host:1234

And then run cargo-maelstrom or maelstrom-pytest against the cluster:

bash
cargo maelstrom --broker=broker-host:1234
maelstrom-pytest --broker=broker-host:1234

Running a Cluster in GitHub Actions

You can use Maelstrom to run your tests in parallel in GitHub Actions. This
chapter of the
book explains how to set this up.

Learn More

Find our complete documentation in the book.

Licensing

This project is available under the terms of either the Apache 2.0 license or the MIT license.