Contributing

Contributions are welcome and are greatly appreciated! Every little bit helps, and credit will always be given.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs through GitHub

If you are reporting a bug, please include:

  • Your operating system name and version.
  • Any details about your local setup that might be helpful in troubleshooting.
  • Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with “bug” is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with “feature” is open to whoever wants to implement it.

Documentation

Superset could always use better documentation, whether as part of the official Superset docs, in docstrings, docs/*.rst or even on the web as blog posts or articles.

Submit Feedback

The best way to send feedback is to file an issue on GitHub.

If you are proposing a feature:

  • Explain in detail how it would work.
  • Keep the scope as narrow as possible, to make it easier to implement.
  • Remember that this is a volunteer-driven project, and that contributions are welcome :)

Latest Documentation

Latest documentation and tutorial are available here

Setting up a Python development environment

Check the OS dependencies before follows these steps.

# fork the repo on GitHub and then clone it
# alternatively you may want to clone the main repo but that won't work
# so well if you are planning on sending PRs
# git clone git@github.com:airbnb/superset.git

# [optional] setup a virtual env and activate it
virtualenv env
source env/bin/activate

# install for development
python setup.py develop

# Create an admin user
fabmanager create-admin --app superset

# Initialize the database
superset db upgrade

# Create default roles and permissions
superset init

# Load some data to play with
superset load_examples

# start a dev web server
superset runserver -d

Setting up the node / npm javascript environment

superset/assets contains all npm-managed, front end assets. Flask-Appbuilder itself comes bundled with jQuery and bootstrap. While these may be phased out over time, these packages are currently not managed with npm.

Node/npm versions

Make sure you are using recent versions of node and npm. No problems have been found with node>=5.10 and 4.0. > npm>=3.9.

Using npm to generate bundled files

npm

First, npm must be available in your environment. If it is not you can run the following commands (taken from this source)

brew install node --without-npm
echo prefix=~/.npm-packages >> ~/.npmrc
curl -L https://www.npmjs.com/install.sh | sh

The final step is to add ~/.npm-packages/bin to your PATH so commands you install globally are usable. Add something like this to your .bashrc file, then source ~/.bashrc to reflect the change.

export PATH="$HOME/.npm-packages/bin:$PATH"

npm packages

To install third party libraries defined in package.json, run the following within the superset/assets/ directory which will install them in a new node_modules/ folder within assets/.

npm install

To parse and generate bundled files for superset, run either of the following commands. The dev flag will keep the npm script running and re-run it upon any changes within the assets directory.

# Compiles the production / optimized js & css
npm run prod

# Start a web server that manages and updates your assets as you modify them
npm run dev

For every development session you will have to start a flask dev server as well as an npm watcher

superset runserver -d -p 8081
npm run dev

Testing

Python tests can be run with:

./run_tests.sh

We use Mocha, Chai and Enzyme to test Javascript. Tests can be run with:

cd /superset/superset/assets/javascripts
npm i
npm run test

Linting

Lint the project with:

# for python changes
flake8 changes tests
flake8 changes superset

# for javascript
npm run lint

Linting with codeclimate

Codeclimate is a service we use to measure code quality and test coverage. To get codeclimate's report on your branch, ideally before sending your PR, you can setup codeclimate against your Superset fork. After you push to your fork, you should be able to get the report at http://codeclimate.com . Alternatively, if you prefer to work locally, you can install the codeclimate cli tool.

Install the codeclimate cli tool

curl -L https://github.com/docker/machine/releases/download/v0.7.0/docker-machine-`uname -s`-`uname -m` > /usr/local/bin/docker-machine && chmod +x /usr/local/bin/docker-machine 
brew install docker
docker-machine create --driver virtual box default
docker-machine env default
eval "$(docker-machine env default)"
docker pull codeclimate/codeclimate
brew tap codeclimate/formulae
brew install codeclimate

Run the lint command:

docker-machine start
eval "$(docker-machine env default)”
codeclimate analyze

More info can be found here: https://docs.codeclimate.com/docs/open-source-free

API documentation

Generate the documentation with:

cd docs && ./build.sh

CSS Themes

As part of the npm build process, CSS for Superset is compiled from Less, a dynamic stylesheet language.

It's possible to customize or add your own theme to Superset, either by overriding CSS rules or preferably by modifying the Less variables or files in assets/stylesheets/less/.

The variables.less and bootswatch.less files that ship with Superset are derived from Bootswatch and thus extend Bootstrap. Modify variables in these files directly, or swap them out entirely with the equivalent files from other Bootswatch (themes)[https://github.com/thomaspark/bootswatch.git]

Pull Request Guidelines

Before you submit a pull request from your forked repo, check that it meets these guidelines:

  1. The pull request should include tests, either as doctests, unit tests, or both.
  2. If the pull request adds functionality, the docs should be updated as part of the same PR. Doc string are often sufficient, make sure to follow the sphinx compatible standards.
  3. The pull request should work for Python 2.6, 2.7, and ideally python 3.3. from __future__ import will be required in every .py file soon.
  4. Code will be reviewed by re running the unittests, flake8 and syntax should be as rigorous as the core Python project.
  5. Please rebase and resolve all conflicts before submitting.

Translations

We use Babel to translate Superset. The key is to instrument the strings that need translation using from flask_babel import lazy_gettext as _. Once this is imported in a module, all you have to do is to _("Wrap your strings") using the underscore _ “function”.

To enable changing language in your environment, you can simply add the LANGUAGES parameter to your superset_config.py. Having more than one options here will add a language selection dropdown on the right side of the navigation bar.

LANGUAGES = {
    'en': {'flag': 'us', 'name': 'English'},
    'fr': {'flag': 'fr', 'name': 'French'},
    'zh': {'flag': 'cn', 'name': 'Chinese'},
}

As per the [Flask AppBuilder documentation] about translation, to create a new language dictionary, run the following command:

pybabel init -i ./babel/messages.pot -d superset/translations -l es

Then it's a matter of running the statement below to gather all stings that need translation

fabmanager babel-extract --target superset/translations/

You can then translate the strings gathered in files located under superset/translation, where there's one per language. For the translations to take effect, they need to be compiled using this command:

fabmanager babel-compile --target superset/translations/

Adding new datasources

  1. Create Models and Views for the datasource, add them under superset folder, like a new my_models.py with models for cluster, datasources, columns and metrics and my_views.py with clustermodelview and datasourcemodelview.

  2. Create db migration files for the new models

  3. Specify this variable to add the datasource model and from which module it is from in config.py:

    For example:

    ADDITIONAL_MODULE_DS_MAP = {'superset.my_models': ['MyDatasource', 'MyOtherDatasource']}

    This means it'll register MyDatasource and MyOtherDatasource in superset.my_models module in the source registry.