This document explains how to use the Bazel build system on the DAML repository from a users perspective. I.e. assuming the project you are working on has already been ported to Bazel.
This guide does not cover how to port a new project to Bazel. Please refer to the Bazel JVM Porting Guide if you intend to port a JVM project to Bazel.
This section goes through the required steps for a basic but fully functioning setup of the Bazel build system for work on the DAML repository. Additional setup as for the IntelliJ integration is listed in its own section below.
Bazel is incorporated in the dev-env. If the dev-env is setup
correctly and dev-env/bin
is in your $PATH
, then Bazel
should be ready to use.
Once setup is complete, you can build the whole repository with the following command.
bazel build //...
You can run all hermetic tests in the repository with the following command.
bazel test //...
If you are unfamiliar with Bazel it is recommended that you read the official Concepts and Terminology guide. Here we will only provide a brief overview which may serve as a refresher.
In short, the daml
repository is a Bazel workspace. It contains a WORKSPACE
file, which defines external dependencies. The workspace contains several
packages. A package is a directory that contains a BUILD.bazel
or BUILD
file. Each package holds multiple targets. Targets are either files under
the package directory or rules defined in the BUILD.bazel
file. You can
address a target by a label of the form //path/to/package:target
. For
example, //ledger/sandbox:sandbox
. Here sandbox
is a target in the package
ledger/sandbox
. It is defined in the file ledger/sandbox/BUILD.bazel
using da_scala_library
as shown below.
da_scala_library(
name = "sandbox",
srcs = glob(["src/main/scala/**/*.scala"]),
resources =
glob(
["src/main/resources/**/*"],
# Do not include logback.xml into the library: let the user
# of the sandbox-as-a-library decide how to log.
exclude = ["src/main/resources/logback.xml"],
) + [
"//:MVN_VERSION",
],
tags = ["maven_coordinates=com.daml:sandbox:__VERSION__"],
visibility = [
"//visibility:public",
],
runtime_deps = [
"@maven//:ch_qos_logback_logback_classic",
"@maven//:ch_qos_logback_logback_core",
],
deps = compileDependencies,
)
The arguments to da_scala_library
are called attributes. These define the
name of the target, the sources it is compiled from, its dependencies, etc.
Note, that Bazel build rules are hermetic. I.e. only explicitly declared
dependencies will be available during execution. In particular, if a rule
depends on additional data files, then these have to be declared dependencies
as well. For example using the resources
or the data
attributes. The
details depend on the rule in question.
The following rules are commonly used in this repository. For Scala projects
da_scala_library
, da_scala_test_suite
, da_scala_binary
. For Java projects
java_library
, java_test_suite
, java_binary
. For DAML projects daml
.
Labels can point to a specific target, or to a set of targets using a wild-card. The following wild-card patterns are recognized.
- Ellipsis (
//some/package/...
): All rule targets within or underneathsome/package
. - All (
//some/package:all
): All rule targets withinsome/package
. - Star (
//some/package:*
): All rule or file targets withinsome/package
.
So far we have talked about targets defined in the current workspace. Bazel
also has a notion of external workspaces. Targets in external workspaces are
labelled as @workspace_name//path/to/package:target
.
Targets have a visibility attribute that determines which other targets can depend on it. Targets can be
- private (
//visibility:private
) Only targets in the same package can depend on it. - visible to specific packages (
//some/package:__pkg__
) Only targets within//some/package
can depend on it. - visible to sub-packages (
//some/package:__subpackages__
) Only targets within or underneath//some/package
can depend on it. - public (
//visibility:public
) Any target in any package can depend on it.
Visibility should be kept as strict as possible to help maintain a clean dependency graph.
Bazel files are written in a language called Starlark. It is very similar to
Python. However, Starlark programs cannot perform arbitrary input and output,
and build files are not allowed to use control structures (for
, if
, etc.),
or define functions. These restrictions are in place to ensure hermeticity.
Make sure to go through the Bazel setup section and to familiarize yourself with Bazel's core concepts as explained in the sections above, before you proceed to the IntelliJ integration.
If you use the IntelliJ IDE you should install the Bazel integration plugin
provided by Google. Follow the installation
instructions in the official documentation. In short:
Install the plugin from within the IDE (Settings > Plugins > Marketplace
, and
search for 'Bazel'). Multiple Bazel plugins exist, make sure to select the Bazel
plugin referencing ij.bazel.build.
If the correct plugin does not exist in the list, then your IntelliJ version might be too recent, and the Bazel plugin might not have been upgraded to support it, yet. Check for version compatibility on the JetBrains plugin page.
To import a Bazel project into IntelliJ select "Import Bazel Project" in the
welcome dialog, or File > Import Bazel Project
in the editor window. In the
import dialog under "Workspace:" enter the path to the DAML repository root.
The Bazel IntelliJ integration uses a project view file to define the list of directories and targets to make accessible in IntelliJ and to control other aspects of the project. Refer to the official documentation for a detailed description.
Choose the "Generate from BUILD file" option and select the BUILD.bazel
file
of the project that you will be working on. Then, click on "Next".
The following dialog allows you to define the project name, or infer it, and to set the location of the project data directory. It also allows you to modify the default project view file. The default should have the following structure:
directories:
.
# Automatically includes all relevant targets under the 'directories' above
derive_targets_from_directories: true
targets:
# If source code isn't resolving, add additional targets that compile it here
additional_languages:
# Uncomment any additional languages you want supported
# ...
Make sure to add Scala, or other languages that you require, to the
additional_languages
section. The section will be pre-populated with a list
of comments specifying the automatically detected supported languages.
If you'd like to work with all directories, we recommend the following project view configuration, which stops IntelliJ from indexing the Bazel cache, and avoids rebuilding the documentation:
directories:
.
-docs
# Automatically includes all relevant targets under the 'directories' above
derive_targets_from_directories: true
targets:
# If source code isn't resolving, add additional targets that compile it here
additional_languages:
javascript
python
scala
typescript
However, you can also provide an allowed list of directories for a faster experience.
If you wish to define a specific set of targets to work, then you can list
these in the targets
section. This is not usually necessary, as they
will be derived automatically.
If you choose to limit the directories, you might end up with a project view file looking like this:
directories:
ledger/sandbox
# ...
# Automatically includes all relevant targets under the 'directories' above
derive_targets_from_directories: true
targets:
# If source code isn't resolving, add additional targets that compile it here
additional_languages:
scala
Click "Next" once you are ready. You will be able to modify the project view file whenever you like, so don't worry too much.
IntelliJ will now import the project. This process will take a while.
The IntelliJ interface should largely look the same as under SBT. However, the main menu will have an additional entry for Bazel, and a Bazel toolbar is provided for quick access to common tasks.
The most commonly required operations are described below. Refer to the plugin documentation for further information.
If you modified a project BUILD.bazel
file, or the project view file, then
click the "Sync Project with BUILD Files" button in the Bazel toolbar, or the
Sync > Sync Project with BUILD Files
entry in the Bazel menu to synchronize
IntelliJ with those changes.
Click Project > Open Local Project View File
in the Bazel menu to open and
modify the current project view file. You may need to sync the project for your
changes to take effect.
Click Build > Compile Project
in the Bazel menu to build the whole project.
Click Build > Compile "CURRENT FILE"
to compile only the current file.
Click on the drop-down menu in the Bazel tool bar and select the entry Bazel run <your target>
or Bazel test <your target>
. If the executable or test you
wish to run or debug is not in the list then follow instructions on adding a
run configuration below first. Come back here when ready.
The selected entry is a run configuration. Click the green arrow in the Bazel toolbar to run the executable or test. Click the green bug icon to debug the executable or test.
If you wish to add an executable or test to the run configurations, then the simplest and most consistent way is to add the target to the project view file and sync the project.
Otherwise, click on the drop-down menu in the Bazel tool bar and select "Edit
Configurations...". Click the "+" in the upper left corner and select "Bazel
Command" from the list. This will add a new entry to the "Bazel Command"
sub-tree. Fill in the fields in the pane on the right side to define the run
configuration: Give a suitable name, select the Bazel target, and choose the
Bazel command (run
, test
, etc.). If applicable, you can also define Bazel
command-line flags or command-line flags to the executable. Click on "Apply",
or "OK" to add the run configuration.
The "Project" pane contains a tree-view of the folders in the project. The "Compact Middle Packages" feature can cause intermediate folders to disappear, only showing their children in the tree-view. The workaround is to disable the feature by clicking on the gear icon in the "Project" pane and unchecking "Compact Middle Packages". Refer to the issue tracker for details.
IntelliJ allows to rerun only a single failed test-case by the click of a button. Unfortunately, this feature does not work with the Bazel plugin on Scala test-cases. Please refer to the issue tracker for details.
The following sections briefly list Bazel commands for the most common use-cases. Refer to the official Bazel documentation for more detailed information.
-
Build all targets
bazel build //...
-
Build an individual target
bazel build //ledger/sandbox:sandbox
-
Execute all tests
bazel test //...
-
Execute a test suite
bazel test //ledger/sandbox:sandbox-scala-tests
-
Show test output
bazel test //ledger/sandbox:sandbox-scala-tests --test_output=streamed
-
Do not cache test results
bazel test //ledger/sandbox:sandbox-scala-tests --nocache_test_results
-
Execute a specific Scala test-suite class
bazel test //ledger/sandbox:sandbox-scala-tests_test_suite_src_test_suite_scala_com_digitalasset_platform_sandbox_stores_ledger_sql_JdbcLedgerDaoSpec.scala
-
Execute a test with a specific name
bazel test \ //ledger/sandbox:sandbox-scala-tests_test_suite_src_test_suite_scala_com_digitalasset_platform_sandbox_stores_ledger_sql_JdbcLedgerDaoSpec.scala \ --test_arg=-t \ --test_arg="JDBC Ledger DAO should be able to persist and load contracts without external offset"
-
Pass an argument to a test case in a Scala test-suite
bazel test //ledger/sandbox:sandbox-scala-tests_test_suite_src_test_suite_scala_com_digitalasset_platform_sandbox_stores_ledger_sql_JdbcLedgerDaoSpec.scala \ --test_arg=-z \ --test_arg="should return true"
More broadly, for Scala tests you can pass through any of the args outlined in http://www.scalatest.org/user_guide/using_the_runner, separating into two instances of the --test-arg parameter as shown in the two examples above.
-
Run an executable target
bazel run //ledger/sandbox:sandbox-binary
-
Pass arguments to an executable target
bazel run //ledger/sandbox:sandbox-binary -- --help
The Bazel query language is described in detail in the official Bazel
documentation. This section will list a few common
use-cases. Filters like filter
or kind
accept regular expressions. Query
expressions can be combined using set operations like intersect
or union
.
-
List all targets underneath a directory
bazel query //ledger/...
-
List all library targets underneath a directory
bazel query 'kind("library rule", //ledger/...)'
-
List all Scala library targets underneath a directory
bazel query 'kind("scala.*library rule", //ledger/...)'
-
List all test-suites underneath a directory
bazel query 'kind("test_suite", //ledger/...)'
-
List all test-cases underneath a directory
bazel query 'tests(//ledger/...)'
-
List all Java test-cases underneath a directory
bazel query 'kind("java", tests(//ledger/...))'
-
List all Scala library dependencies of a target
bazel query 'kind("scala.*library rule", deps(//ledger/sandbox:sandbox))'
-
Find available 3rd party dependencies
bazel query 'attr(visibility, public, filter(".*scalaz.*", //3rdparty/...))'
Bazel queries can also output dependency graphs between the targets that the query includes. These can then be rendered using Graphviz.
-
Graph all Scala library dependencies of a target
bazel query --noimplicit_deps 'kind(scala_library, deps(//ledger/sandbox:sandbox))' --output graph > graph.in dot -Tpng < graph.in > graph.png
The
--noimplicit_deps
flag excludes dependencies that are not explicitly listed in theBUILD
file, but that are added by Bazel implicitly, e.g. the unused dependency checker added byrules_scala
.
-
List available commands
bazel help
-
Show help on a Bazel command
bazel help build
-
Show details on each option
bazel help build --long
By continuous build we mean the ability to watch the repository for source file
changes and rebuild or rerun targets when any relevant files change. The
dev-env provides the tool ibazel
for that purpose. Similar to Bazel it can be
called with the commands build
, test
, or run
on a specific target. It
will perform the command and determine a list of relevant source files. Then,
it will watch these files for changes and rerun the command on file change. For
example:
ibazel test //ledger/sandbox:sandbox-scala-tests
Note, that this interacts well with Bazel's test result caching (which is activated by default). In the above example the outcome of tests whose sources didn't change will already be cached by Bazel and the tests won't be repeated.
Refer to the project README for more information.
In Bazel terminology, a directory containing a BUILD.bazel
file is
called a "package". Packages contain targets and BUILD.bazel
files
are where targets are defined. Mostly we are concerned in our
BUILD.bazel
files with writing rules to produce specific Haskell
derived files (artifacts) from Haskell source file inputs. Of these,
most are libraries, some are executables and some are tests.
For Haskell, most BUILD.bazel
files begin with a variation on the
following:
load( "//bazel_tools:haskell.bzl",
"da_haskell_library", "da_haskell_executable","da_haskell_test" )
This directive loads from the //bazel_tools
package, the rules
da_haskell_library
for building libraries,
da_haskell_binary
for building executables and
da_haskell_test
for building test-suites. The da_*
rules are DA specific overrides
of the upstream rules_haskell
rules. Their API docs can be found in
//bazel_tools/haskell.bzl
, or by executing the bazel-api-docs
tool
from dev-env
. They mostly behave like the upstream rules, just
adding some defaults, and adding a hackage_deps
attribute (more on
this below) for convenience.
One specific library in the daml-foundations
stack is
daml-ghc-compiler
. Here's a synopsis of its definition.
da_haskell_library(
name = "daml-ghc-compiler",
srcs = glob([
"src/**/*.hs",
]),
src_strip_prefix = "src",
deps = [
"//compiler/daml-lf-ast",
"//compiler/daml-lf-proto",
...
],
hackage_deps = [
"base",
"bytestring",
...
],
visibility = ["//visibility:public"],
)
To build this single target from the root of the DAML repository, the command would be:
bazel build //compiler/damlc/daml-compiler
since the BUILD.bazel
that defines the target is in the
compiler/damlc
sub-folder of the root of the DA
repository and the target name
is damlc
.
Let's break this definition down:
name
: A unique name for the target;srcs
: A list of Haskell source files;src_stip_prefix
: Directory in which the module hierarchy starts;deps
: A list of in-house Haskell or C library dependencies to be linked into the target;hackage_deps
: A list of external Haskell (Hackage) libraries to be linked into the target;visibility
: Define whether depending on this target by others is permissible.
Note the use of the Bazel
glob
function to define the srcs
argument allowing us to avoid having to
enumerate all source files explicitly. The **
part of the shown glob
expression is Bazel syntax for any sub-path. Read more about glob
here.
The deps
argument in the above invocation can be interpreted as
linking the libraries defined by the list of targets provided on the
right hand side (when we say "package" here we mean Haskell package -
i.e. library):
//:ghc-lib
is theghc-lib
package defined in the rootBUILD
file,//compiler/daml-lf-ast
is thedaml-lf-ast
package defined in thedaml-foundations/daml-compiler/BUILD.bazel
file (that is,//compiler/daml-lf-ast
is shorthand for//compiler/daml-lf-ast:daml-lf-ast
)- Similarly,
//nix/third-party/proto3-suite
is the Haskell library//nix/third-party/proto3-suite:proto3-suite
defined in the filenix/third-party/proto3-suite/BUILD.bazel
.
The hackage_deps
argument details those Haskell packages (from
Hackage) that the daml-ghc-compiler
target depends upon. In this case
that is base
, bytestring
and some other packages not
shown. Finally, visibility
is set to public so no errors will result
should another target attempt to link daml-ghc-compiler
. [Note : Public
visibility means that any other target from anywhere can depend on the
target. To keep the dependency graph sane, its a good idea to keep
visibility restrictive. See
here
for more detail.]
Here's the synopsis of the rule for the executable daml-ghc
:
da_haskell_binary (
name = "daml-ghc",
srcs = glob (["src/DA/Cli/**/*.hs", "src/DA/Test/**/*.hs"])
src_strip_prefix = "DA",
main_function = "DA.Cli.GHC.Run.main",
hackage_deps = [ "base", "time", ...],
data = [
"//compiler/damlc/pkg-db"
, ...
],
deps = [
":daml-ghc-compiler"
, "//:ghc-lib"
, "//compiler/daml-lf-ast"
, ...
]
, visibility = ["//visibility:public"]
)
Haskell binaries require a definition of the distinguished function
main
. The main_function
argument allows us to express the
qualified module path to the definition of main
to use.
The data
argument in essence is a list of files needed by the target
at runtime. Consult this
documentation
for more detail. The targets that are given on the right-hand-side
are (long-hand) labels for "file-groups". Here's the one for
daml-stdlib-src
for example.
filegroup(
name = "daml-stdlib-src",
srcs = glob(["daml-stdlib/**"]),
visibility = ["//visibility:public"]
)
Having looked at deps
in the context of haskell_library
there's
not much more to say except note the :daml-ghc-compiler
syntax for the
depedency on daml-ghc-compiler
. That is, targets defined in the same
BUILD.bazel
as the target being defined can be referred to by
preceding their names with :
.
For an example of a test target, we turn to
//libs-haskell/da-hs-base:da-hs-base-tests
:
da_haskell_test(
name = "da-hs-base-tests",
src_strip_prefix = "src-tests",
srcs = glob(["src-tests/**/*.hs"]),
deps = [
":da-hs-base",
],
visibility = ["//visibility:public"],
)
There is nothing new in the above to expound upon here! How might you invoke that single target? Simple as this:
bazel test "//libs-haskell/da-hs-base:da-hs-base-tests"
More comprehensive documentation on the bazel
command can be found
here.
If your work goes beyond simply adding targets to existing
BUILD.bazel
files and involves things like defining toolchains and
external dependencies, then this
document
is for you!
In this section we will provide an overview of how Scala targets are defined in
Bazel in this repository. This should provide enough information for most
everyday development tasks. For more information refer to the Bazel porting
guide for JVM developers (to be written as of now). For a general reference to
BUILD.bazel
file syntax refer to the official
documentation. Note, that BUILD.bazel
and BUILD
are both
valid file names. However, BUILD.bazel
is the preferred spelling. BUILD
is
the older spelling and still to be found in large parts of the documentation.
Bazel targets are defined in BUILD.bazel
files. For example
//ledger-client/ods:ods
is defined in ledger-client/ods/BUILD.bazel
. First,
we import the required rules and macros. For example, the following loads the
da_scala_library
macro defined in //bazel_tools:scala.bzl
, and the daml
rule defined in ledger-client/daml.bzl
. The distinction of rules and macros
is not important here.
load('//bazel_tools:scala.bzl', 'da_scala_library')
load('//rules_daml:daml.bzl', 'daml')
The macro da_scala_library
is a convenience function that defines a Scala
library and sets common compiler flags, plugins, etc. To explain it we will
take an example instance and describe the individual attributes. For details
refer to the rules_scala
project README. For a Java rules
refer to the official Bazel documentation.
da_scala_library(
# Set the target name to 'ods'.
name = 'ods',
# Mark this target as public.
# I.e. targets in other package can depend on it.
visibility = ['//visibility:public'],
# Define the target's source files by globbing.
# The details of file globbing are explained here:
# https://docs.bazel.build/versions/master/be/functions.html#glob
srcs = glob(['src/main/**/*.scala'], exclude = [...]),
# Define the target's resources by globbing.
resources = glob(['src/main/resources/**/*']),
# Define the target's dependencies.
# These will appear in the compile-time classpath.
# And the transient closure of `deps`, `runtime_deps`, and `exports`
# will appear in the runtime classpath.
deps = [
# A third party dependency.
'//3rdparty/jvm/ch/qos/logback:logback_classic',
# A dependency in the same workspace.
'//ledger-client/nanobot-framework',
# A dependency in the same package.
':ods-macro'
...
],
# Define the target's runtime dependencies.
# These will appear only in the runtime classpath.
runtime_deps = [...],
# List of exported targets.
# E.g. if something depends on ':ods', it will also depend on ':ods-macro'.
exports = [':ods-macro'],
# Scalac compiler plugins to use for this target.
# Note, that these have to be specified as JAR targets.
# I.e. you cannot use `//3rdparty/jvm/org/scalameta/paradise_2_12_6` here.
plugins = [
'//external:jar/org/scalameta/paradise_2_12_6',
],
# Scalac compiler options to use for this target.
scalacopts = ['-Xplugin-require:macroparadise'],
# JVM flags to pass to the Scalac compiler.
scalac_jvm_flags = ['-Xmx2G'],
)
Scala executables are defined using da_scala_binary
. It takes most of the
same attributes that da_scala_library
takes. Notable additional attributes
are:
main_class
: Name of the class defining the entry-pointmain()
.jvm_flags
: Flags to pass to the JVM at runtime.data
: Files that are needed at runtime. In order to access such files at runtime you should use the utility library incom.daml.testing.BuildSystemSupport
.
Scala test-suites are defined using da_scala_test_suite
. It takes most of the
same attributes as da_scala_binary
.
Note, that this macro will create one target for every single source file
specified in srcs
. The advantage is that separate test-cases can be addressed
as separate Bazel targets and Bazel's test-result caching can be applied more
beneficially. However, this means that test-suite source files may not depend
on each other.
A single Scala test-cases, potentially consisting of multiple source files, can
be defined using da_scala_test
. It is preferable to always use
da_scala_test_suite
, and define separate testing utility libraries using
da_scala_library
if test-cases depend on utility modules.
Scala benchmarks based on the JMH toolkit can be defined using the
scala_benchmark_jmh
macro provided by rules_scala
. It supports a restricted
subset of the attributes of da_scala_binary
, namely: name
, deps
, srcs
,
scalacopts
, resources
and resource_jars
.
The end result of building the benchmark is a Scala binary of the same name,
which can be executed with bazel run
.
Bazel's builtin Java rules and rules_scala
will automatically generate a fat
JAR suitable for deployment for all your Java and Scala targets. For example,
if you defined a Scala executable target called foo
, then Bazel will generate
the target foo_deploy.jar
next to the regular foo.jar
target. Building the
foo_deploy.jar
target will generate a self-contained fat JAR suitable to be
passed to java -jar
.
DAML package targets are defined using the daml
rule loaded from
//rules_daml:daml.bzl
. To explain it we will take an example instance and
describe the individual attributes.
daml(
name = "it-daml",
# The main DAML file. This file will be passed to damlc.
main_src = "src/it/resources/TestAll.daml",
# Other DAML files that may be imported by the main DAML file.
srcs = glob(["src/it/resources/**/*.daml"]),
# The directory prefix under which to create the DAR tree.
target_dir = "target/scala-2.12/resource_managed/it/dars",
# The group ID.
group = "com.daml.sample",
# The artifact ID.
artifact = "test-all",
# The package version.
version = "0.1",
# The package name.
package = "com.daml.sample",
)
This will compile and package the DAML code into a DAR file under the following
target, where <group-dir>
is the group
attribute with .
replaced by /
.
:<target_dir>/<group-dir>/<artifact>/<version>/<artifact>-<version>.dar,
For example:
:target/scala-2.12/resource_managed/it/dars/com/digitalasset/sample/test-all/0.1/test-all-0.1.dar
POM and SHA files will be stored in the same directory.
Additionally, this will perform Scala code generation and bundle the generated Scala modules into a source JAR available under the following target.
<name>.srcjar
For example:
it-daml.srcjar
The rule daml_binary
is provided to generate executable targets that execute
the DAML sandbox on a given DAR package. For example:
daml_binary(
name = "ping-pong-exec",
dar = ':target/repository/.../PingPong-0.1.dar',
)
Such a target can then be executed as follows, where arguments after --
are
passed to the DAML sandbox.
bazel run //ledger-client/nanobot-sample-app:ping-pong-exec -- --help
External dependencies are these that are not defined and built within the local workspace, but are defined in an external workspace in some way. The most common case are Maven JAR dependencies which are fetched from Artifactory.
We distinguish direct and transitive dependencies. Direct dependencies are
explicitly defined on targets in the local workspace. Most commonly on the
deps
, runtime_deps
, exports
, or plugins
attributes. Transitive
dependencies are introduced implicitly through direct dependencies, most
commonly on another dependency's exports
attribute.
All direct Scala and Java dependencies are listed explicitly in the file
bazel-java-deps.bzl
. Each dependency is defined by its Maven coordinates. The
maven_install
repository rule calls Coursier to perform transitive dependency
resolution and import the required artifacts into the Bazel build.
The resolved versions are pinned in the file maven_install.json
. Execute
bazel run @unpinned_maven//:pin
when you wish to update or add a new
dependency. See rules_jvm_external
for details.
We are using rules_typescript to build typescript projects. It works in conjunction with rules_nodejs to provide access to npm packages.
Please refer to the documentation in the above url for usage.
For an example, please see compiler/daml-extension/BUILD.bazel
.
We use protocol buffers for DAML-LF and the Ledger API. The DAML-LF protocol buffer build rules can be found from //daml-lf/archive/BUILD.bazel. It produces bindings for Java and Haskell (via proto3-suite).
Bazel provides built-in rules for protocol buffer bindings for Java and C++. See the following resources for more information on its usage: Protocol Buffer Rules Blog post: Protocol Buffers in Bazel
The rules for haskell are currently ad-hoc genrules and use the proto3-suite's compile-proto-file program directly. Please refer to //daml-lf/archive/BUILD.bazel for example usage. If you find yourself writing similar rules, please take a moment to write some Starlark to abstract it out and document it here. Note that proto3-suite isn't compatible with protoc, so it is not currently possible to hook it up into the "proto_library" tooling.
Unfortunately, GHC builds are not deterministic. This, coupled with the way Bazel works, may lead to Haskell libraries that have not been changed to be rebuilt. If the library sits at the base of the dependency graph, it may cause a ripple effect that forces you to rebuild most of the workspace without an actual need for it (ghc-lib
is one example of this).
To work around this issue you can clean the local and build cache, making sure you are fetching the GHC build artifacts from remote:
bazel clean --expunge # clean the build cache
rm -r .bazel-cache # clean the local cache
This will also mean that changes made locally will need to be rebuilt, but it's likely that this will still result in a net positive gain on your build time.
If you are still rebuilding after this, you probably also have a poisoned Nix cache. To clear that run through the following steps:
bazel clean --expunge # clean the build cache
rm -r .bazel-cache # clean the local cache
rm dev-env/var/gc-roots/* # Remove dev-env GC roots
rm result* # Remove GC roots you might have from previous nix-build invocations.
nix-store --gc --print-roots # View all garbage collection roots
# Verify that there is nothing from our repo or some Bazel cache.
# If you are not sure ask in #team-daml
nix-store --gc # Run garbage collection
nix-build nix -A tools -A cached --no-out-link # Build the nix derivations (they should be fetched from the cache)
bazel build //... # You should now see things being fetched from the cache
Bazel tries to leverage the remote cache to speed up the build process but this can turn out to work against you if you are working in an environment with low or intermittent connectivity. To disable fetching from the remote cache in such scenario, you can use the --noremote_accept_cached
option.