LAVA development

LAVA development

Pre-requisites to start with development

LAVA is written in Python, so you will need to know (or be willing to learn) the language. Likewise, the web interface is a Django application so you will need to use and debug Django if you need to modify the web interface. All LAVA software is maintained in git, as are many of the support scripts, test definitions and job submissions. Some familiarity with Debian is going to be useful, helper scripts are available when preparing packages based on your modifications.

LAVA is complex and works to solve complex problems. This has implications for how LAVA is developed, tested, deployed and used.

Other elements involved in LAVA development

The Django backend used with LAVA is PostgreSQL and some postgres-specific support is used. The LAVA UI has some use of Javascript and CSS. LAVA V1 also uses XML-RPC and the LAVA documentation is written with RST.

In addition, test jobs and device support can involve use of U-Boot, ADB, QEMU, Grub, SSH and a variety of other systems and tools to access devices and debug test jobs.

Developer workflows


LAVA is developed using Debian packaging to ensure that daemons and system-wide configuration is correctly updated with changes in the codebase. There is no support for pypi or python virtual environments or installing directly from a git directory. python-setuptools is used but only with sdist to create the tarballs to be used for the Debian packaging, not for install. Some dependencies of LAVA are not available with pypi, for example python-guestfs.

Developers can update the installed code on their own systems manually (by copying files into the system paths) and/or use symlinks where appropriate but changes need to be tested in a system which is deployed using the Developer package build before being proposed for review. All changes must also pass all the unit tests, unless those tests are already allowed to be skipped using unittest decorators.

Mixing the use of python code in /usr/local/lib and /usr/lib on a single system is known to cause spurious errors and will only waste your development time. Be very careful when copying files and when using symlinks. If in doubt, remove /usr/local/lib/python* and ~/.local/lib/python* then build a local developer package and install it.

If your change introduces a dependency on a new python module, always ensure that this module is available in Debian by searching the Debian package lists. If the module exists but is not in the current stable release of Debian, it can be backported but be aware that this will delay testing and acceptance of your change. It is expressly not acceptable to add a dependency on a python module which is only available using pypi or pip install. Introducing such a module to Debian can involve a large amount of work - talk to us before spending time on code which relies on such modules or which relies on newer versions of the modules than are currently available in Debian testing.

See also

Quick fixes and testing and testing_refactoring_code

Naming conventions and LAVA V1 architecture

Certain terms used in LAVA V1 have specific meanings, please be consistent in the use of the following terms:

The physical hardware sitting in a rack or on a desk.
A database object in LAVA which stores configuration, information and status relating to a single board. The device information can be represented in export formats like YAML for use when the database is not accessible.

A database object which collates similar devices into a group for purposes of scheduling. Devices of a single type are often the same vendor model but not all boards of the same model will necessarily be of the same device-type.

The dispatcher software relates to the lava-dispatcher source package in git and in Debian. The dispatcher software for LAVA V1 must be installed alongside the server with extra configuration and a machine like this is also called a dispatcher or a remote worker.

A singleton process which is solely responsible for assigning a device to a test job. The scheduler is common to LAVA V1 and LAVA V2 and performs checks on submission restrictions, device availability, device tags and schema compliance.

See also

device tag

The server software relates to the lava-server source package in git and in Debian. It includes components from LAVA V1 and LAVA V2 covering the UI and the scheduler daemon.
test job
A database object which is created for each submission and retains the logs and pipeline information generated when the test job executed on the device.

Updating online documentation

LAVA online documentation is written with RST format. You can use the command below to generate html format files.:

$ cd lava-server/
$ make -C doc/v1 html
$ iceweasel doc/v1/_build/html/index.html
(or whatever browser you prefer)

We welcome contributions to improve the documentation. If you are considering adding new features to LAVA or changing current behaviour, ensure that the changes include updates for the documentation.

Contributing Upstream

The best way to protect your investment on LAVA is to contribute your changes back. This way you don’t have to maintain the changes you need by yourself, and you don’t run the risk of LAVA changed in a way that is incompatible with your changes.

Upstream uses Debian, see Developing LAVA on Debian or Ubuntu for more information.

Community contributions

Contributing via your distribution

You are welcome to use the bug tracker of your chosen distribution. The maintainer for the packages in that distribution should Register with Linaro as a Community contributor with Linaro (or already be part of Linaro) to be able to forward bug reports and patches into the upstream LAVA systems.

Register with Linaro as a Community contributor

If you, or anyone on your team, would like to register with Linaro directly, this will allow you to file an upstream bug, submit code for review by the LAVA team, etc. Register at the following url:

If you are considering large changes, it is best to register and also to subscribe to the lava_devel mailing list and talk to us on IRC:

Contributing via GitHub

You can use GitHub to fork the LAVA packages and make pull requests.

It is worth sending an email to the lava_devel mailing list, so that someone can migrate the pull request to a review.

Patch Submissions and workflow

This is a short guide on how to send your patches to LAVA. The LAVA team uses the gerrit code review system to review changes.

If you do not already have a Linaro account, you will first need to Register with Linaro as a Community contributor.

So the first step will be logging in to gerrit and uploading you SSH public key there.

Obtaining the repository

There are two main components to LAVA, lava-server and lava-dispatcher.

git clone
cd lava-server

git clone
cd lava-dispatcher

There is also lava-tool which is gaining more support for operations involving the V2 design:

git clone
cd lava-tool

Setting up git-review

git review -s

Create a topic branch

We recommend never working off the master branch (unless you are a git expert and really know what you are doing). You should create a topic branch for each logically distinct change you work on.

Before you start, make sure your master branch is up to date:

git checkout master
git pull

Now create your topic branch off master:

git checkout -b my-change master

Run the unit tests

Extra dependencies are required to run the tests. On Debian based distributions, you can install lava-dev. (If you only need to run the lava-dispatcher unit tests, you can just install pep8 and python-testscenarios.)

To run the tests, use the ci-run script:

$ ./ci-run

Functional testing

Unit tests cannot replicate all tests required on LAVA code, some tests will need to be run with real devices under test. On Debian based distributions, see Developer package build. See Writing a LAVA test definition for information on writing LAVA test jobs to test particular device functionality.

Make your changes

  • Follow PEP8 style for Python code.
  • Make one commit per logical change.
  • Use one topic branch for each logical change.
  • Include unit tests in the commit of the change being tested.
  • Write good commit messages. Useful reads on that topic:

Re-run the unit tests

Make sure that your changes do not cause any failures in the unit tests:

$ ./ci-run

Wherever possible, always add new unit tests for new code.

Send your commits for review

From each topic branch, just run:

git review

If you have multiple commits in that topic branch, git review will warn you. It’s OK to send multiple commits from the same branch, but note that 1) commits are review and approved individually and 2) later commits will depend on earlier commits, so if a later commit is approved and the one before it is not, the later commit will not be merged until the earlier one is approved.

Submitting a new version of a change

When reviewers make comments on your change, you should amend the original commit to address the comments, and not submit a new change addressing the comments while leaving the original one untouched.

Locally, you can make a separate commit addressing the reviewer comments, it’s not a problem. But before you resubmit your branch for review, you have to rebase your changes against master to end up with a single, enhanced commit. For example:

$ git branch
* my-feature
$ git show-branch master my-feature
! [master] Last commit on master
 ! [my-feature] address revier comments
 + [my-feature] address reviewer comments
 + [my-feature^] New feature or bug fix
-- [master] Last commit on master
$ git rebase -i master

git rebase -i will open your $EDITOR and present you with something like this:

pick xxxxxxx New feature or bug fix
pick yyyyyyy address reviewer comments

You want the last commit to be combined with the first and keep the first commit message, so you change pick to fixup ending up with somehting like this:

pick xxxxxxx New feature or bug fix
fixup yyyyyyy address reviewer comments

If you also want to edit the commit message of the first commit to mention something else, change pick to reword and you will have the chance to do that. Just remember to keep the Change-Id unchanged.

NOTE: if you want to abort the rebase, just delete everything, save the file as empty and exit the $EDITOR.

Now save the file and exit your $EDITOR.

In the end, your original commit will be updated with the changes:

$ git show-branch master my-feature
! [master] Last commit on master
 ! [my-feature] New feature or bug fix
 + [my-feature] New feature or bug fix
-- [master] Last commit on master

Note that the “New feature or bug fix” commit is now not the same as before since it was modified, so it will have a new hash (zzzzzzz instead of the original xxxxxxx). But as long as the commit message still contains the same Change-Id, gerrit will know it is a new version of a previously submitted change.

Handling your local branches

After placing a few reviews, there will be a number of local branches. To keep the list of local branches under control, the local branches can be easily deleted after the merge. Note: git will warn if the branch has not already been merged when used with the lower case -d option. This is a useful check that you are deleting a merged branch and not an unmerged one, so work with git to help your workflow.

$ git checkout bugfix
$ git rebase master
$ git checkout master
$ git branch -d bugfix

If the final command fails, check the status of the review of the branch. If you are completely sure the branch should still be deleted or if the review of this branch was abandoned, use the -D option instead of -d and repeat the command.

Reviewing changes in clean branches

If you haven’t got a clone handy on the instance to be used for the review, prepare a clone as usual.

Gerrit provides a number of ways to apply the changes to be reviewed, so set up a test branch as usual - always ensuring that the master branch of the clone is up to date before creating the review branch.

$ git checkout master
$ git pull
$ git checkout -b review-111

To pull in the changes in the review already marked for commit in your local branch, use the pull link in the patch set of the review you want to run.

Alternatively, to pull in the changes as plain patches, use the patch` link and pipe that to patch -p1. In this full example, the second patch set of review 159 is applied to the review-159 branch as a patch set.

$ git checkout master
$ git pull
$ git checkout -b review-159
$ git fetch refs/changes/59/159/2 && git format-patch -1 --stdout FETCH_HEAD | patch -p1
$ git status

Handle the local branch as normal. If the reviewed change needs modification and a new patch set is added, revert the local change and apply the new patch set.

Other considerations

All developers are encouraged to write code with futuristic changes in mind, so that it is easy to do a technology upgrade, which includes watching for errors and warnings generated by dependency packages as well as upgrading and migrating to newer APIs as a normal part of development.

Database migrations

LAVA recommends Debian Jessie but also supports Ubuntu Trusty which has an older version of python-django.

Database migrations on Debian Jessie and later are managed within django. Support for python-django-south has been dropped. Only django migration types should be included in any reviews which involve a database migration.

Once modified, the updated file needs to be copied into the system location for the relevant extension, e.g. lava_scheduler_app. This is a step which needs to be done by the developer - developer packages cannot be installed cleanly and unit tests will likely fail until the migration has been created and applied.

On Debian Jessie and later:

$ sudo lava-server manage makemigrations lava_scheduler_app

The migration file will be created in /usr/lib/python2.7/dist-packages/lava_scheduler_app/migrations/ (which is why sudo is required) and will need to be copied into your git working copy and added to the review.

The migration is applied using:

$ sudo lava-server manage migrate lava_scheduler_app

See django docs for more information.

Python 3.x

There is no pressure or expectation on delivering python 3.x code. LAVA is a long way from being able to use python 3.x support, particularly in lava-server, due to the lack of python 3.x migrations in dependencies. However it is good to take python 3.x support into account, when writing new code, so that it makes it easy during the move anytime in the future.

Developers can run unit tests against python 3.x for all LAVA components from time to time and keep a check on how we can support python 3.x without breaking compatibility with python 2.x


Pylint is a tool that checks for errors in Python code, tries to enforce a coding standard and looks for bad code smells. We encourage developers to run LAVA code through pylint and fix warnings or errors shown by pylint to maintain a good score. For more information about code smells, refer to Martin Fowler’s refactoring book. LAVA developers stick on to PEP 008 (aka Guido’s style guide) across all the LAVA component code.

To simplify the pylint output, some warnings are recommended to be disabled:

$ pylint -d line-too-long -d missing-docstring

NOTE: Docstrings should still be added wherever a docstring would be useful.

In order to check for PEP 008 compliance the following command is recommended:

$ pep8 --ignore E501

pep8 can be installed in debian based systems as follows:

$ apt-get install pep8


LAVA has set of unit tests which the developers can run on a regular basis for each change they make in order to check for regressions if any. Most of the LAVA components such as lava-server, lava-dispatcher, lava-tool have unit tests.

Extra dependencies are required to run the tests. On Debian based distributions, you can install lava-dev. (If you only need to run the lava-dispatcher unit tests, you can just install pep8 and python-testscenarios.)

To run the tests, use the ci-run / ci-build scripts:

$ ./ci-run

LAVA database model visualization

LAVA database models can be visualized with the help of django_extensions along with tools such as pydot. In debian based systems install the following packages to get the visualization of LAVA database models:

$ apt-get install python-django-extensions python-pydot

Once the above packages are installed successfully, use the following command to get the visualization of lava-server models in PNG format:

$ sudo lava-server manage graph_models --pydot -a -g -o lava-server-model.png

More documentation about graph models is available in

Other useful features from django_extensions are as follows:

  • shell_plus - similar to the built-in “shell” but autoloads all


  • validate_templates - check templates for rendering errors

    $ sudo lava-server manage validate_templates

  • runscript - run arbitrary scripts inside lava-server environment

    $ sudo lava-server manage runscript fix_user_names –script-args=all

Developer access to django shell

Default configurations use a side-effect of the logging behaviour to restrict access to the lava-server manage operations which typical Django apps expose through the interface. This is because lava-server manage shell provides read-write access to the database, so the command requires sudo.

On developer machines, this can be unnecessary. Set the location of the django log to a new location to allow easier access to the management commands to simplify debugging and to be able to run a Django Python Console inside a development environment. In /etc/lava-server/settings.conf add:

"DJANGO_LOGFILE": "/tmp/django.log"


settings.conf is JSON syntax, so ensure that the previous line ends with a comma and that the resulting file validates as JSON. Use JSONLINT

The new location needs to be writable by the lavaserver user (for use by localhost) and by the developer user (but would typically be writeable by anyone).