Working on the Dune Codebase

This section gives guidelines for working on Dune itself. Many of these are general guidelines specific to Dune. However, given that Dune is a large project developed by many different people, it’s important to follow these guidelines in order to keep the project in a good state and pleasant to work on for everybody.

Bootstrapping

In order to build itself, Dune uses a micro dune written as a single boot/duneboot.ml file. This micro build system cannot read dune files and instead has the configuration hard-coded in boot/libs.ml. This latter file is automatically updated during development when we modify the dune files in the repository. boot/duneboot.ml itself is built with a single invocation of ocamlopt or ocamlc via the bootstrap.ml ocaml script.

boot/duneboot.ml builds a dune.exe binary at the root of the source tree and uses this binary to build everything else.

$ make dev takes care of bootstrapping if needed, but if you want to just run the bootstrapping step itself, build the dune.exe target with

make dune.exe

Once you’ve bootstrapped dune, you should be using it to develop dune itself. Here are the most common commands you’ll be running:

# to make sure everything compiles:
$ ./dune.exe build @check
# run all the tests
$ ./dune.exe runtest
# run a particular cram foo.t:
$ ./dune.exe build @foo

Writing Tests

Most of our tests are written as expectation-style tests. While creating such tests, the developer writes some code and then lets the system insert the output produced during the code execution. The system puts it right next to the code in the source file.

Once you write and commit a test, the system checks that the captured output matches the one produced by a fresh code execution. When the two don’t match, the test fails. The system then displays a diff between what was expected and what the code produced.

We write both our unit tests and integration tests in this way. For unit tests, we use the ppx_expect framework, where we introduce tests via let%expect_test, and [%expect ...] nodes capture expectations:

let%expect_test "<test name>" =
   print_string "Hello, world!";
   [%expect {|
     Hello, world!
   |}]

For integration tests, we use a system similar to Cram tests for testing shell commands and their behavior:

$ echo 'Hello, world!'
Hello, world!

$ false
[1]

$ cat <<EOF
> multi
> line
> EOF
multi
line

Guidelines

As with any long running software project, code written by one person will eventually be maintained by another. Just like normal code, it’s important to document tests, especially since test suites are most often composed of many individual tests that must be understood on their own.

A well-written test case should be easily understood. A reader should be able to quickly understand what property the test is checking, how it’s doing it, and how to convince oneself that the test outcome is the right one. A well-written test makes it easier for future maintainers to understand the test and react when the test breaks. Most often, the code will need to be adapted to preserve the existing behavior; however, in some rare cases, the test expectation will need to be updated.

It’s crucial that each test case makes its purpose and logic crystal clear, so future maintainers know how to deal with it.

When writing a test, we generally have a good idea of what we want to test. Sometimes, we want to ensure a newly developed feature behaves as expected. Other times, we want to add a reproduction case for a bug reported by a user to ensure future changes won’t reintroduce the faulty behaviour. Just like when programming, we turn such an idea into code, which is a formal language that a computer can understand. While another person reading this code might be able to follow and understand what the code does step by step, it isn’t clear that they’ll be able to reconstruct the original developer’s idea. Even worse, they might understand the code in a completely different way, which would lead them to update it incorrectly.

Releasing Dune

Dune’s release process relies on dune-release. Make sure you install and understand how this software works before proceeding. Publishing a release consists of two steps:

  • Updating CHANGES.md to reflect the version being published
  • Running $ make opam-release to create the release tarball. Then publish it to GitHub and submit it to opam.

Major & Feature Releases

Given a new version x.y.z, a major release increments x, and a feature release increments y. Such a release must be done from the main branch. Once you publish the release, be sure to publish a release branch named x.y.

Point Releases

Point releases increment the z in x.y.z. Such releases are done from the respective x.y branch of the respective feature release. Once released, be sure to update CHANGES in the main branch.

Adding Stanzas

Adding new stanzas is the most natural way to extend Dune with new features. Therefore, we try to make this as easy as possible. The minimal amount of steps to add a new stanza is:

  • Extend Stanza.t with a new constructor to represent the new stanza
  • Modify Dune_file to parse the Dune language into this constructor
  • Modify the rules to interpret this stanza into rules, usually done in Gen_rules`

Versioning

Dune is incredibly strict with versioning of new features, modifications visible to the user, and changes to existing rules. This means that any added stanza must be guarded behind the version of the Dune language in which it was introduced. For example:

; ( "cram"
  , let+ () = Dune_lang.Syntax.since Stanza.syntax (2, 7)
    and+ t = Cram_stanza.decode in
    [ Cram t ] )

Here, Dune 2.7 introduced the Cram stanza, so the user must enable (lang dune 2.7) in their dune project file to use it.

since isn’t the only primitive for making sure that versions are respected. See Dune_lang.Syntax for other commonly used functions.

Experimental & Independent Extensions

Sometimes, Dune’s versioning policy is too strict. For example, it doesn’t work in the following situations:

  • When most Dune independent extensions only exist inside Dune for development convenience, e.g., build rules for Coq. Such extensions would like to impose their own versioning policy.
  • When experimental features cannot guarantee Dune’s strict backwards compatibility. Such features may dropped or modified at any time.

To handle both of these use cases, Dune allows the definition of new languages (with the same syntax). These languages have their own versioning scheme and their own stanzas (or fields). In Dune itself, Syntax.t represents such languages. Here’s an example of how the Coq syntax is defined:

let coq_syntax =
  Dune_lang.Syntax.create ~name:"coq" ~desc:"the coq extension (experimental)"
   [ ((0, 1), `Since (1, 9)); ((0, 2), `Since (2, 5)) ]

The list provides which versions of the syntax are provided and which version of Dune introduced them.

Such languages must be enabled in the dune project file separately:

(lang dune 3.2)
(using coq 0.2)

If such extensions are experimental, it’s recommended that they pass ~experimental:true, and that their versions are below 1.0.

We also recommend that such extensions introduce stanzas or fields of the form ext_name.stanza_name or ext_name.field_name to clarify which extensions provide a certain feature.

Dune Rules

Creating Rules

A Dune rule consists of 3 components:

  • Dependencies that the rule may read when executed (files, aliases, etc.), described by 'a Action_builder.t values.
  • Targets that the rule produces (files and/or directories), described by 'a Action_builder.With_targets.t' values.
  • Action that Dune must execute (external programs, redirects, etc.). Actions are represented by Action.t values.

Combined, one needs to produce an Action.t Action_builder.With_targets.t value to create a rule. The rule may then be added by Super_context.add_rule or a related function.

To make this maximally convenient, there’s a Command module to make it easier to create actions that run external commands and describe their targets and dependencies simultaneously.

Loading Rules

Dune rules are loaded lazily to improve performance. Here’s a sketch of the algorithm that tries to load the rule that generates some target file t.

  • Get the directory that of t. Call it d.
  • Load all rules in d into a map from targets in that directory to rules that produce it.
  • Look up the rule for t in this map.

To adhere to this loading scheme, we must generate our rules as part of the callback that creates targets in that directory. See the Gen_rules module for how this callback is constructed.

Documentation

User documentation lives in the ./doc directory.

In order to build the user documentation, you must install python-sphinx and sphinx_rtd_theme.

Build the documentation with

$ make doc

For automatically updated builds, you can install sphinx-autobuild, and run

$ make livedoc