If you have a large Haskell code base, organized in multiple Cabal packages, with many system dependencies, and which takes very long to build, then this post is for you. We describe herein gazelle_cabal, a new tool that generates Haskell rules to build with the Bazel build tool. It saves the maintainer the trouble of writing these rules to begin with, and then keeping them synchronized with the Cabal files whenever they are modified.
Developer teams who want to make a gradual transition to Bazel can continue to specify builds via Cabal files while still using Bazel to build their artifacts.
Why Bazel?
Bazel is known to offer caching for builds of multi-language projects. Once the cache is hot, builds can avoid rebuilding many intermediate artifacts, shortening the overall build times. This reduces the time and the cost of running continuous integration systems and improves developer productivity by decreasing the time it takes to rebuild when switching branches of the project in a versioned control system.
Some support for incremental builds is implemented by most modern build
tools, cabal-install
and stack being no exception. However, the
tools specialized for Haskell have poor support for working with dependencies
written in other languages, and they readily discard old artifacts when
rebuilding them, which entails subsequent rebuilds when reverting changes.
Moving to Bazel is often a major investment for an existing project, though.
The recipes to build each artifact need to be rewritten, and the ways of the
new build system need to be learned. The gazelle_cabal
tool helps with
some of that effort by extending the gazelle tool, which provides
infrastructure to generate and update Bazel configuration files in general.
Generating rules
In the happy path, one configures gazelle_cabal
in a given repo, and then invokes
$ bazel run //:gazelle
The above will generate BUILD.bazel
files next to each Cabal file,
containing the rules necessary to build the various components of the
Cabal package.
If the Cabal file reads
cabal-version: 2.4
name: package-a
version: 0.1.0.0
...
library
...
executable executable-a
...
test-suite test-a
...
benchmark bench-a
...
The BUILD.bazel
file will look like
haskell_library(
name = "package-a",
...
)
haskell_binary(
name = "executable-a",
...
)
haskell_test(
name = "test-a",
...
)
haskell_binary(
name = "bench-a",
...
)
Additionally, one could invoke the following command to declare in
the WORKSPACE
file all of the Haskell dependencies that the Cabal
packages need.
$ bazel run //:gazelle-update-repos
Which generates the following rule in the WORKSPACE
file.
stack_snapshot(
name = "stackage",
components = {
"tasty-discover": [ "lib", "exe:tasty-discover" ],
...
},
packages = [
"base",
"tasty",
"tasty-discover",
"tasty-hunit",
"void",
...
],
)
In this case, the user is expected to add other necessary attributes.
For instance, the stack_snapshot rule requires either
a snapshot
or a local_snapshot
attribute.
Updating rules
Unlike other file generators, gazelle_cabal
and gazelle
extensions
in general don’t overwrite the generated files on subsequent runs.
They rather blend updates to the rules with the contents of the existing files.
This simplifies considerably the customization of the output, which
otherwise would need to be specified with command line flags or
additional configuration files.
As an example, suppose we want to skip building a library on some particular configuration. One way to deal with that in Bazel is to specify a tag.
haskell_library(
name = "package-a",
srcs = ...,
tags = ["skip-ci"],
)
The next time that gazelle_cabal
runs, it may modify other
attributes, but it will know to preserve the tags
attribute
and any other attribute that doesn’t need an update.
Even when attributes need to be updated, some parts of them can
still be preserved. A typical example is the package list in
the WORKSPACE
file.
stack_snapshot(
name = "stackage",
...
packages = [
"aeson", # keep
"base",
"inspection-testing",
"optparse-applicative", # keep
"path", # keep
"path-io", # keep
"tasty",
"tasty-discover",
"tasty-hunit",
"void",
],
snapshot = "lts-18.1",
)
Here, gazelle_cabal
is free to add and remove any packages
in the packages
attribute of the stack_snapshot
rule as
long as they aren’t marked with a #keep
comment. When a
#keep
comment is used, the corresponding package name needs
to be retained in all updates. And this applies to any list
of strings or labels in any attribute managed by the tool.
In the case of stack_snapshot
this is handy to manage
dependency lists, where some packages are required by Cabal
files, and some packages are required by non-managed Haskell
rules in the same repository.
Also, note the snapshot
attribute above, which is required
by the stack_snapshot
rule and gazelle_cabal
leaves
untouched.
Related tools
Long time users of rules_haskell
may feel reminded of
Hazel, which was the tool used to import Stackage dependencies into
Bazel builds before it was replaced by the Cabal rules.
Hazel was similar to gazelle_cabal
in that it parsed Cabal files and
generated haskell_library
or haskell_binary
targets to build these Cabal
packages with Bazel.
However, Hazel was intended for a different use-case. Namely, importing
external dependencies into the project and building them with Bazel.
This meant that it had to be able to fully automatically generate working build
definitions for all required external dependencies.
Many packages are easy to translate, however, some packages make use of advanced Cabal features such as custom setup scripts or configure scripts in ways that can be difficult to translate fully automatically. The Cabal rules avoid these issues by building external dependencies with Cabal, meaning no conversion is required. They are still the recommended way to build external Haskell dependencies.
This Gazelle extension, on the other hand, is intended for Cabal packages situated in your code base, where changes to the Cabal file or code for compatibility are more convenient to make. As mentioned before, Gazelle can also preserve user defined adjustments to generated Bazel rules when needed.
Of course this raises the question, why not just use the Cabal rules for these packages?
Firstly, if using Cabal rules, it would still be up to the user to write on
each rule the list of Haskell dependencies that each package needs to build,
whereas gazelle_cabal
can take care of that.
Also, the regular Haskell rules are better suited for the main code base than the Cabal rules. For example, only regular Haskell rules can be loaded into GHCi by source using haskell_repl. Cabal rules, in contrast, can only be loaded as precompiled libraries.
Regular Haskell rules can also generate finer-grained actions providing
faster incremental builds.
The Cabal rules, on the other hand, generate large monolithic actions
(e.g. generating haddock
documentation together with linking static and
dynamic libraries) and have to do additional work for compatibility between
Bazel and Cabal.
This overhead is not a big issue for third party dependencies that are rarely
changed and most often fetched from cache. However, it is an issue for targets
that are changed frequently.
Closing remarks
This project was possible thanks to the generous funding from
Symbiont and their test bed for the initial
implementation. We made a case of gazelle_cabal
as a tool
to help development teams transitioning to Bazel builds. As the
tool is adopted by other projects, we look forward to receiving
contributions and smoothing the user experience.
About the authors
Facundo is a software engineer supporting development and research projects at Tweag. Prior to joining Tweag, he worked in academia and in industry, on a varied assortment of domains, with an overarching interest in programming languages.
Andreas is a physicist turned software engineer. He leads the Bazel team, and maintains Tweag's open source Bazel rule sets and the capability package. He is passionate about functional programming, and hermetic and reproducible builds. He lives in Zurich and is active in the local Haskell community.
If you enjoyed this article, you might be interested in joining the Tweag team.