- Set up database with developer seeds
- Run tests
- Generate initial RuboCop TODO list
- Compile Frontend Assets
- Emoji tasks
- Update project templates
- Generate route lists
- Show obsolete
- Validate GraphQL queries
- Analyze GraphQL queries
- Update GraphQL documentation and schema definitions
Rake tasks are available for developers and others contributing to GitLab.
Note that if your database user does not have advanced privileges, you must create the database manually before running this command.
bundle exec rake setup
setup task is an alias for
This tasks calls
db:reset to create the database, and calls
db:seed_fu to seed the database.
db:seed but this does nothing.
MASS_INSERT: Create millions of users (2m), projects (5m) and its relations. It’s highly recommended to run the seed with it to catch slow queries while developing. Expect the process to take up to 20 extra minutes.
See also Mass inserting Rails models.
LARGE_PROJECTS: Create large projects (through import) from a predefined set of URLs.
You can seed issues for all or a given project with the
# All projects bin/rake gitlab:seed:issues # A specific project bin/rake "gitlab:seed:issues[group-path/project-path]"
By default, this seeds an average of 2 issues per week for the last 5 weeks per project.
You can seed issues specifically for working with the
Insights charts with the
# All projects bin/rake gitlab:seed:insights:issues # A specific project bin/rake "gitlab:seed:insights:issues[group-path/project-path]"
By default, this seeds an average of 10 issues per week for the last 52 weeks per project. All issues are also randomly labeled with team, type, severity, and priority.
You can seed groups with subgroups that contain milestones/projects/issues
bin/rake "gitlab:seed:group_seed[subgroup_depth, username]"
Group are additionally seeded with epics if GitLab instance has epics feature available.
A lot of different types of metrics are supported in the monitoring dashboard.
To import these metrics, you can run:
bundle exec rake 'gitlab:seed:development_metrics[your_project_id]'
If you’re very sure that you want to wipe the current database and refill
seeds, you can set the
FORCE environment variable to
FORCE=yes bundle exec rake setup
This will skip the action confirmation/safety check, saving you from answering
Since the script would print a lot of information, it could be slowing down
your terminal, and it would generate more than 20G logs if you just redirect
it to a file. If we don’t care about the output, we could just redirect it to
echo 'yes' | bundle exec rake setup > /dev/null
Note that since you can’t see the questions from
stdout, you might just want
echo 'yes' to keep it running. It would still print the errors on
so no worries about missing errors.
There are a few environment flags you can pass to change how projects are seeded
SIZE: defaults to
32. Amount of projects to create.
LARGE_PROJECTS: defaults to false. If set, clones 6 large projects to help with testing.
FORK: defaults to false. If set to
torvalds/linuxfive times. Can also be set to an existing project
full_pathto fork that instead.
In order to run the test you can use the following commands:
bin/rake specto run the RSpec suite
bin/rake spec:unitto run only the unit tests
bin/rake spec:integrationto run only the integration tests
bin/rake spec:systemto run only the system tests
bin/rake spec takes significant time to pass.
Instead of running the full test suite locally, you can save a lot of time by running
a single test or directory related to your changes. After you submit a merge request,
CI runs full test suite for you. Green CI status in the merge request means
full test suite is passed.
You can’t run
rspec . since this tries to run all the
files it can find, also the ones in
You can pass RSpec command line options to the
spec:system tasks. For example,
bin/rake "spec:unit[--tag ~geo --dry-run]".
For an RSpec test, to run a single test file you can run:
To run several tests inside one directory:
bin/rspec spec/requests/api/for the RSpec tests if you want to test API only
If your Merge Request pipeline failed with RSpec test failures, you can run all the failed tests on your machine with the following Rake task:
There are a few caveats for this Rake task:
- You need to be on the same branch on your machine as the source branch of the Merge Request.
- The pipeline must have been completed.
- You may need to wait for the test report to be parsed and retry again.
This Rake task depends on the unit test reports feature, which only gets parsed when it is requested for the first time.
Spring is a Rails application pre-loader. It speeds up development by keeping your application running in the background so you don’t need to boot it every time you run a test, Rake task or migration.
If you want to use it, you must export the
Alternatively you can use the following on each spec run,
bundle exec spring rspec some_spec.rb
One way to generate the initial list is to run the Rake task
bundle exec rake rubocop:todo:generate
To generate TODO list for specific RuboCop rules, pass them comma-seperated as argument to the Rake task:
bundle exec rake 'rubocop:todo:generate[Gitlab/NamespacedClass,Lint/Syntax]' bundle exec rake rubocop:todo:generate\[Gitlab/NamespacedClass,Lint/Syntax\]
Some shells require brackets to be escaped or quoted.
See Resolving RuboCop exceptions on how to proceed from here.
You shouldn’t ever need to compile frontend assets manually in development, but if you ever need to test how the assets get compiled in a production environment you can do so with the following command:
RAILS_ENV=production NODE_ENV=production bundle exec rake gitlab:assets:compile
with all other frontend assets (images, fonts, etc) into
they can be easily inspected.
To update the Emoji aliases file (used for Emoji autocomplete), run the following:
bundle exec rake tanuki_emoji:aliases
To update the Emoji digests file (used for Emoji autocomplete), run the following:
bundle exec rake tanuki_emoji:digests
This updates the file
fixtures/emojis/digests.json based on the currently
To generate a sprite file containing all the Emoji, run:
bundle exec rake tanuki_emoji:sprite
If new emoji are added, the sprite sheet may change size. To compensate for
such changes, first generate the
emoji.png sprite sheet with the above Rake
task, then check the dimensions of the new sprite sheet and update the
SPRITESHEET_HEIGHT constants accordingly.
Starting a project from a template needs this project to be exported. On a up to date main branch run:
gdk start bundle exec rake gitlab:update_project_templates git checkout -b update-project-templates git add vendor/project_templates git commit git push -u origin update-project-templates
Now create a merge request and merge that to main.
To update just a single template instead of all of them, specify the template name
between square brackets. For example, for the
cluster_management template, run:
bundle exec rake gitlab:update_project_templates\[cluster_management\]
To see the full list of API routes, you can run:
bundle exec rake grape:path_helpers
The generated list includes a full list of API endpoints and functional RESTful API verbs.
For the Rails controllers, run:
bundle exec rails routes
Since these take some time to create, it’s often helpful to save the output to a file for quick reference.
To see a list of all obsolete
bundle exec rake db:obsolete_ignored_columns
Feel free to remove their definitions from their
To check the validity of one or more of our front-end GraphQL queries, run:
# Validate all queries bundle exec rake gitlab::graphql:validate # Validate one query bundle exec rake gitlab::graphql:validate[path/to/query.graphql] # Validate a directory bundle exec rake gitlab::graphql:validate[path/to/queries]
This prints out a report with an entry for each query, explaining why each query is invalid if it fails to pass validation.
We strip out
@client fields during validation so it is important to mark
client fields with the
@client directive to avoid false positives.
ANALYZE in SQL, we can run
estimate the of the cost of running a query.
# Analyze all queries bundle exec rake gitlab::graphql:analyze # Analyze one query bundle exec rake gitlab::graphql:analyze[path/to/query.graphql] # Analyze a directory bundle exec rake gitlab::graphql:analyze[path/to/queries]
This prints out a report for each query, including the complexity of the query if it is valid.
The complexity depends on the arguments in some cases, so the reported complexity is a best-effort assessment of the upper bound.
To generate GraphQL documentation based on the GitLab schema, run:
bundle exec rake gitlab:graphql:compile_docs
In its current state, the Rake task:
- Generates output for GraphQL objects.
- Places the output at
This uses some features from
graphql-docs gem like its schema parser and helper methods.
The docs generator code comes from our side giving us more flexibility, like using Haml templates and generating Markdown files.
To edit the content, you may need to edit the following:
- The template. You can edit the template at
tooling/graphql/docs/templates/default.md.haml. The actual renderer is at
- The applicable
descriptionfield in the code, which Updates machine-readable schema files, which is then used by the
raketask described earlier.
@parsed_schema is an instance variable that the
graphql-docs gem expects to have available.
Gitlab::Graphql::Docs::Helper defines the
object method we currently use. This is also where you
should implement any new methods for new types you’d like to display.
To generate GraphQL schema files based on the GitLab schema, run:
bundle exec rake gitlab:graphql:schema:dump
This uses GraphQL Ruby’s built-in Rake tasks to generate files in both IDL and JSON formats.
The following command combines the intent of Update GraphQL documentation and schema definitions and Update machine-readable schema files:
bundle exec rake gitlab:graphql:update_all