Bazel rules to test Bazel rules

6 October 2022 — by Ilya Polyakovskiy

As frequent Bazel rule writers, at Tweag we need ways to test our rulesets. In this post I will describe the approach that I’ve recently introduced in rules_haskell to achieve clear, maintainable and efficient tests for Bazel rules.

Why even bother?

All software needs to be tested and verified, and Bazel rules are no exception. Some of them are popular public libraries with a lot of projects depending on them, and they need a proper test set to allow every contributor, frequent or occasional, to propose a change with little risk of breaking the public API those rules represents. The same applies to the rules that live in huge monorepos growing every day, where they often act as a glue between different components and can become complex, tricky and fragile.

Also every Bazel rule introduces an API and a proper test-suite provides a clear and valid example of its usage. The usual practice among rule writers is to include an examples/ folder in their package with a bunch of example workspaces and test on CI that all their targets are built and run successfully. Look at rules_rust and rules_nixpkgs for example. There are some serious flaws in this approach:

  • It’s non-hermetic: since Bazel is not executed inside a sandbox those test doesn’t benefit from Bazel’s approach of tests sandboxing: any local files, specifics of the shell and environment variables can influence the execution of examples
  • It’s non-reproducible: in addition to lack of sandboxing this approach doesn’t pin the Bazel version which should be used to execute those examples
  • It’s inconvenient: unlike any other tests you may have in your project, these tests are not invoked by Bazel and lose all benefits of Bazel’s tests runner.

An overview of existing tools

There are several projects addressing this problem. I will concentrate on the two I draw inspiration from. I will first show how to apply each of them to the rules_haskell project. Then I’ll explain the solution that I’ve eventually used for testing rules_haskell.

rules_go and go_bazel_test:

This rule was created in the rules_go repository to do integration testing of go_*-rules. It consists of a Starlark macro and a Go library with some helper functions to set up a test workspace and run Bazel commands inside it. This allows writing test scenarios in the form of a Go program. Lets see how it would look like if we tried to write a simple test for the haskell_binary rule from rules_haskell.

Every Bazel rule requires its sources to be declared explicitly. In this case we want to test our rules as a package, so we need to define a target which would represent the rules_haskell distribution to pass it to the test. Let’s create a filegroup in the top-level BUILD.bazel file (we can use the example from rules_go as an inspiration):

    name = "all_files",
    src = [
        # All top-level rules files
        # and all sub-level "all_files" filegroups

Using this filegroup we can create a test target in a BUILD.bazel file:

load("@rules_go//go/tools/bazel_testing:def.bzl", "go_bazel_test")

    name = "sample",
    srcs = ["sample_test.go"],
    rule_files = "//:all_files",

Now let’s create the actual test scenario. In our case it would be located in the sample_test.go file:

package sample_test

import (

We need to define our test workspace. The bazel_testing library requires it to be specified as a string using a specific format:

const workspace = `
    name = rules_haskell,
    # I will explain where this path came from a bit later
    path = "../rules_haskell",

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
load("@rules_haskell//haskell:repositories.bzl", "rules_haskell_dependencies")


    version = "8.10.7",

-- BUILD.bazel --

    name = "base",

    name = "Sample",
    srcs = ["Sample.hs"],
    deps = [":base"],
-- Sample.hs --
main = putStrLn "Hello World!"

Now we can use bazel_testing functions to unpack this workspace as a real directory and run some Bazel commands in it.

func TestMain(m *testing.M) {
        bazel_testing.TestMain(m, bazel_testing.Args{
                Main: workspace,

func SampleTest(t *testing.T) {
        if err := bazel_testing.RunBazel("build", "//:sample"); err != nil {

There is one more important thing about the go_bazel_test implementation worth mentioning: bazel_testing.TestMain unpacks the test workspace and its dependencies in a specific place outside of the sandbox in Bazel’s outputUserBase directory

Here is an example of the directory structure created by go_bazel_test on my Linux machine:

 | # This is the directory where bazel creates "sandboxed" folders for every test
 | #   tests are encouraged to keep all their data inside those directories
 +-- execroot/
 | # This is created by `go_bazel_test`
 +-- bazel_testing/
    +-- bazel_go_test/
        +-- main/
        |   |
        |   +-- WORKSPACE
        |   |
        |   +-- BUILD.bazel
        |   |
        |   +-- Sample.hs
        +-- rules_haskell/
        |   |
            # files included in "all_files" filegroup

So why is go_bazel_test not using the “sandboxed” directory which Bazel creates for every test? To answer this question we need to understand some aspects of how Bazel does caching. If we look at the Bazel output directory layout description, we’ll see that for every project which Bazel builds, it creates its own outputBase directory. The name of this directory is based on the md5sum of the project’s absolute path, so it’s unique for every project you build on your machine. Every target built is stored in a directory corresponding to this project’s absolute path.

If we create a new Go project to build it with rules_go, when we run bazel build //... for the first time it will spend a lot of time fetching and configuring the go-toolchain. For the following build executions this toolchain would be reused from the cache and the overall build time significantly smaller.

Returning to go_bazel_test, if it used sandbox directories for every test workspace, their absolute path would differ for every test and Bazel would be forced to build every test workspace from scratch. So it will do fetching and configuration of the same toolchain every time, which would take a lot of time and disk space.

To avoid this, go_bazel_test unpacks all tests workspaces into the same directory, keeping the same absolute path across all test workspaces. In our example it’s:


This will make Bazel reuse the same build cache between tests and significantly improve tests performance. This approach of choosing a fixed directory weakens hermeticity, because tests are sharing some context between each other which makes them less deterministic. Also it makes it impossible to run such tests in parallel, so they have to use the exclusive tag. The rules_haskell test bench will inherit these downsides.


There is a project created specifically for the purpose of testing Bazel rules and was recently added into the bazel-contrib organization. It provides the bazel_integration_test rule which supports:

  • Creating test workspaces as nested directories inside a parent workspace
  • Using arbitrary executable targets as test scenarios
  • Using multiple Bazel versions to run tests against

With this ruleset we can rewrite our test in a clearer and more straightforward manner. We can create a directory somewhere inside our project that looks like this:

+-- BUILD.bazel
+-- sample_test/
|   |
|   |
|   +-- BUILD.bazel
|   |
|   +-- Sample.hs

The contents of the sample_test directory would be the same as what was contained in our go-string in the previous paragraph, except for sample_test/WORKSPACE. The path to parent workspace in local_repository would differ since there is no specific optimizations moving everything outside of the sandbox anymore:

    name = rules_haskell,
    path = "../",
) could look somewhat like:

# BIT_BAZEL_BINARY and BIT_WORKSPACE_DIR are environment variables set up by the test suite
# BIT is an acronym for Bazel Integration Testing

output=$("$BIT_BAZEL_BINARY" run //:sample)
test "$output" == "Hello World!\n" || exit 1

and test-scenarios/BUILD.bazel like:

load("@rules_bazel_integration_test//bazel_integration_test:defs.bzl", "bazel_integration_test")

    name = "sample_test_scenario",
    srcs = "",

    name = "sample",
    bazel_version = "4.2.0",
    test_runner = ":sample_test_scenario",
    workspace_files = integration_test_utils.glob_workspace_files("sample_test") + [
    workspace_path = "sample_test",

This can be enough for a lot of projects, but without the optimizations from go_bazel_test, the average integration test in rules_haskell would take about 5-7 minutes and huge amounts of disk space.

Implementing a test rule for rules_haskell

Considering all of the above and with the specific needs of rules_haskell let’s formulate the requirements for the test rule we’d like to have in rules_haskell.

Creating a test in the form of a nested workspace

rules_bazel_integration_test offers a way to express testcases in form of directories with Bazel workspaces. In contrast go_bazel_test expects the workspace to be specified as a string of a specific format inside a test scenario. I find the former much clearer and easy to read and understand. In addition it provides clear and valid example of rules usage which the ruleset can refer to in its documentation.

Testing multiple Bazel versions

Since rules_haskell is a public library which supports of a variety of Bazel versions it would be very useful to be able to run integration tests using different Bazel versions and distributions. Specifically rules_haskell supports Bazel >= 4.0 and Bazel installed using Nixpkgs.

Picking the right Bazel configuration

rules_haskell demands some configurations from the user depending on the OS or the way the Haskell toolchain is distributed. For our tests we should be able to pick the proper configuration automatically depending on the system this test is ran on.

Reuse the Bazel cache between tests runs

As I’ve mentioned before, we want to use the Bazel cache for rules_haskell tests, in the same style as go_bazel_test. Otherwise every test would require huge amount of time and disk space.

Writing test scenarios in Haskell

It’s not that necessary but besides the fact that rules_haskell is about Haskell and most of its contributors are proficient with Haskell, it has a collection of test scenarios already written in Haskell and waiting to be reimplemented as an integration tests. So it would be very convenient if this new test rule would allow us to reuse these test scenarios.

In order to achieve the first three points we can create a macro on top of bazel_integration_test. Here is an example of how it looks like:


def haskell_bazel_integration_test(

    test_scenario_name = "%s_scenario" % name
        name = test_scenario_name,
        srcs = srcs,
        deps = deps,
        testonly = True,

    for bazel_id, bazel_binary in bazel_binaries:
            name = "%s_%s" % (name, bazel_id),
            test_runner = test_scenario_name,
            bazel_binary = bazel_binary,
            workspace_files = integration_test_utils.glob_workspace_files(workspace_path) + rule_files,
            workspace_path = workspace_path,

The bazel_binaries argument exists because in rules_haskell we need to pass both Bazel’s official binary distributions and a Bazel binary from Nixpkgs. There is bazel_versions in bazel_integration_tests which manages versions of official Bazel’s binary and could be entirely sufficient for many projects, but we need something more flexible to allow arbitrary Bazel distributions. So here we expect bazel_binaries to be a dictionary with keys representing a short descriptive name for a Bazel binary (e.g. bazel_4 if it came from Nixpkgs’ bazel_4 package, or 4.2.1 if it’s binary distribution of a specific version) and values which are labels for the Bazel binaries.

To address the remaining two points we can borrow some ideas from rules_go. We can implement the same approach and create a Haskell library for testing with a similar test setup procedure. It will find a specific place and set up a test workspace in it, while also providing functions to invoke Bazel with the proper configuration. For example they could look something like this:

-- Sets up the workspace and Bazel's outputBaseDir. Returns paths to
-- workspace and to outputBaseDir as a tuple
setupWorkspace :: IO (String, String)

-- Creates a function which generates Bazel commands for a specific
-- workspaceDir and outputBaseDir, picks a bazel config depending on the OS as well
bazelCmd :: String -> String -> IO ([String] -> Process.CreateProcess)

In this case we can rewrite our test scenario like this:

-- Imagine we have a function to assert a predicate on (stdout, stderr) of an arbitrary process
  :: ((String, String) -> Bool)
  -> Process.CreateProcess
  -> IO ()

main :: IO ()
main = do
  (workspaceDir, outputBaseDir) <- setupWorkspace
  bazel <- bazelCmd workspaceDir outputBaseDir
  let p (stdout, _stderr) = lines stdout == ["Hello World!"]
     outputSatisfy p (bazel ["run", "//:sample"])

There is still one unsolved problem from mixing these two approaches. As mentioned above, rules_go’s rule creates a special directory to keep the same absolute path of the test workspace. bazel_integration_test’s rule on the other hand allows us to run different versions of Bazel in this workspace. If you look at the code we wrote you can see we’ve created a separate test target for every pair of test and Bazel version. Bazel doesn’t guarantee any test execution order so without additional changes the test cache will not be reused because although the absolute path of the test workspace is the same, if the Bazel version differs from the previous test, Bazel will reconstruct the cache from scratch.

In order to solve this, we will create a separate directory for every Bazel binary we are using for testing. We need to communicate to the test suite which Bazel version we are going to use for a specific test, so that it can prepare a proper directory for this test. We can use bazel_id - the short name we’ve introduced already - to distinguish the Bazel binaries in test names.

   for bazel_name, bazel_binary in bazel_binaries:
            name = "%s_%s" % (name, bazel_id),
            test_runner = test_scenario_name,
            bazel_binary = bazel_binary,
            workspace_files = integration_test_utils.glob_workspace_files(workspace_path) + rule_files,
            workspace_path = workspace_path,
            env = {"BAZEL_ID": bazel_id},

Now our setupWorkspace function can use the BAZEL_ID environment variable to create a directory, and end up with something like: /home/user/.cache/bazel/_bazel_user/852e945491923423601e3c06e84323e3/bazel_testing/$BAZEL_ID instead of the one created by rules_go.

With all this, we’ve got a rule, which we useg in rules_haskell to create tests to be run with Bazel versions 4.0.0, 4.2.2, 5.0.0, 5.2.0 and also with Bazel binary provided by the bazel_4 package from Nixpkgs. With all the optimizations the average test duration is about 25-30 seconds.


This was a brief story about how we developed an approach to test our rules in rules_haskell. If you want to see the complete implementation you can find it in this PR, and some instructions on how to use it here. I hope you can borrow from our experience to test your rules, and that together we will find a way to have a simple, clean and safe process of developing Bazel rules. Stay tuned for more content for rule writers!

About the author

Ilya Polyakovskiy

If you enjoyed this article, you might be interested in joining the Tweag team.

This article is licensed under a Creative Commons Attribution 4.0 International license.


AboutOpen SourceCareersContact Us

Connect with us

© 2024 Modus Create, LLC

Privacy PolicySitemap