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Contributing

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

Table of Contents

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.

When posting Python stack traces, please quote them using Markdown blocks.

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 or starter_task is open to whoever wants to implement it.

Improve 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. See Documentation for more details.

Add Translations

If you are proficient in a non-English language, you can help translate text strings from Superset's UI. You can jump in to the existing language dictionaries at superset/translations/<language_code>/LC_MESSAGES/messages.po, or even create a dictionary for a new language altogether. See Translating for more details.

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 :)

Ask Questions

There is a dedicated apache-superset tag on StackOverflow. Please use it when asking questions.

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. Run tox and resolve all errors and test failures.
  3. 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.
  4. The pull request should work for Python 2.7 and Python 3.6. from __future__ import will be required in every .py file soon.
  5. If the pull request adds a Python dependency include it in setup.py denoting any specific restrictions and run pip-compile to update the requirements.txt file which ensures that the application build is deterministic.
  6. Please rebase and resolve all conflicts before submitting.
  7. Please ensure the necessary checks pass and that code coverage does not decrease.
  8. If you are asked to update your pull request with some changes there's no need to create a new one. Push your changes to the same branch.

Local development

First, fork the repository on GitHub, then clone it. You can clone the main repository directly instead, but you won't be able to send pull requests.

git clone [email protected]:your-username/incubator-superset.git
cd incubator-superset

Documentation

The latest documentation and tutorial are available at https://superset.incubator.apache.org/.

Contributing to the official documentation is relatively easy, once you've setup your environment and done an edit end-to-end. The docs can be found in the docs/ subdirectory of the repository, and are written in the reStructuredText format (.rst). If you've written Markdown before, you'll find the reStructuredText format familiar.

Superset uses Sphinx to convert the rst files in docs/ to the final HTML output users see.

Finally, to make changes to the rst files and build the docs using Sphinx, you'll need to install a handful of dependencies from the repo you cloned:

pip install -r docs/requirements.txt

To get the feel for how to edit and build the docs, let's edit a file, build the docs and see our changes in action. First, you'll want to create a new branch to work on your changes:

git checkout -b changes-to-docs

Now, go ahead and edit one of the files under docs/, say docs/tutorial.rst - change it however you want. Check out the ReStructuredText Primer for a reference on the formatting of the rst files.

Once you've made your changes, run this command to convert the docs into HTML:

make html

You'll see a lot of output as Sphinx handles the conversion. After it's done, the HTML Sphinx generated should be in docs/_build/html. Navigate there and start a simple web server so we can check out the docs in a browser:

cd docs/_build/html
python -m SimpleHTTPServer

This will start a small Python web server listening on port 8000. Point your browser to http://localhost:8000, find the file you edited earlier, and check out your changes!

If you've made a change you'd like to contribute to the actual docs, just commit your code, push your new branch to Github:

git add docs/tutorial.rst
git commit -m 'Awesome new change to tutorial'
git push origin changes-to-docs

Then, open a pull request.

Images

If you're adding new images to the documentation, you'll notice that the images referenced in the rst, e.g.

.. image:: _static/img/tutorial/tutorial_01_sources_database.png

aren't actually stored in that directory. Instead, you should add and commit images (and any other static assets) to the superset/assets/images directory. When the docs are deployed to https://superset.incubator.apache.org/, images are copied from there to the _static/img directory, just like they're referenced in the docs.

For example, the image referenced above actually lives in superset/assets/images/tutorial. Since the image is moved during the documentation build process, the docs reference the image in _static/img/tutorial instead.

API documentation

Generate the API documentation with:

pip install -r docs/requirements.txt
python setup.py build_sphinx

Flask server

Make sure your machine meets the OS dependencies before following these steps.

# Create a virtual environemnt and activate it (recommended)
virtualenv venv
source venv/bin/activate

# Install external dependencies
pip install -r requirements.txt
# Install Superset in editable (development) mode
pip install -e .

# 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 the Flask web server (but see below for frontend asset compilation)
superset runserver -d

Logging to the browser console

This feature is only available on Python 3. When debugging your application, you can have the server logs sent directly to the browser console:

superset runserver -d --console-log

You can log anything to the browser console, including objects:

from superset import app
app.logger.error('An exception occurred!')
app.logger.info(form_data)

Frontend assets

Frontend assets (JavaScript, CSS, and images) must be compiled in order to properly display the web UI. The superset/assets directory contains all NPM-managed front end assets. Note that there are additional frontend assets bundled with Flask-Appbuilder (e.g. jQuery and bootstrap); these are not managed by NPM, and may be phased out in the future.

First, be sure you are using recent versions of NodeJS and npm. Using nvm to manage them is recommended.

Install third-party dependencies listed in package.json:

# From the root of the repository
cd superset/assets

# Install yarn, a replacement for `npm install`
npm install -g yarn

# Install dependencies
yarn install

Finally, to compile frontend assets, run any of the following commands.

# Start a watcher that recompiles your assets as you modify them (reload your browser to see changes)
npm run dev

# Compile the Javascript and CSS in production/optimized mode for official releases
npm run prod

# Copy a conf file from the frontend to the backend
npm run sync-backend

Webpack dev server

Alternatively, you can run the Webpack dev server, which runs on port 9000 and proxies non-asset requests to the Flask server on port 8088. After pointing your browser to it, updates to asset sources will be reflected in-browser without a refresh.

# Run the dev server
npm run dev-server

# Run the dev server on a non-default port
npm run dev-server -- --port=9001

# Run the dev server proxying to a Flask server on a non-default port
npm run dev-server -- --supersetPort=8081

Upgrading NPM packages

After adding or upgrading an NPM package by changing package.json, you must run yarn install, which will regenerate the yarn.lock file. Then, be sure to commit the new yarn.lock so that other users' builds are reproducible. See the Yarn docs for more information.

Testing

All tests are carried out in tox a standardized testing framework mostly for Python (though we also used it for Javascript). All python tests can be run with any of the tox environments, via,

tox -e <environment>

i.e.,

tox -e py27
tox -e py36

Alternatively, you can run all tests in a single file via,

tox -e <environment> -- tests/test_file.py

or for a specific test via,

tox -e <environment> -- tests/test_file.py:TestClassName.test_method_name

Note that the test environment uses a temporary directory for defining the SQLite databases which will be cleared each time before the group of test commands are invoked.

JavaScript testing

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

cd superset/assets/spec
npm install
npm run test

Integration testing

We use Cypress for integration tests. Tests can be run by tox -e cypress. To open Cypress and explore tests first setup and run test server:

export SUPERSET_CONFIG=tests.superset_test_config
superset db upgrade
superset init
superset load_test_users
superset load_examples
superset runserver

Run Cypress tests:

cd /superset/superset/assets
npm run build
npm run cypress run

Linting

Lint the project with:

# for python
tox -e flake8

# for javascript
tox -e eslint

Translating

We use Babel to translate Superset. In Python files, we import the magic _ function using:

from flask_babel import lazy_gettext as _

then wrap our translatable strings with it, e.g. _('Translate me'). During extraction, string literals passed to _ will be added to the generated .po file for each language for later translation. At runtime, the _ function will return the translation of the given string for the current language, or the given string itself if no translation is available.

In JavaScript, the technique is similar: we import t (simple translation), tn (translation containing a number), and TCT (translating entire React Components).

import {t, tn, TCT} from locales;

Enabling language selection

Add the LANGUAGES variable to your superset_config.py. Having more than one option inside will add a language selection dropdown to the UI on the right side of the navigation bar.

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

Extracting new strings for translation

fabmanager babel-extract --target superset/translations --output superset/translations/messages.pot --config superset/translations/babel.cfg -k _ -k __ -k t -k tn -k tct

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:

# In the case of JS translation, we need to convert the PO file into a JSON file, and we need the global download of the npm package po2json.
npm install -g po2json
fabmanager babel-compile --target superset/translations
# Convert the en PO file into a JSON file
po2json -d superset -f jed1.x superset/translations/en/LC_MESSAGES/messages.po superset/translations/en/LC_MESSAGES/messages.json

If you get errors running po2json, you might be running the Ubuntu package with the same name, rather than the NodeJS package (they have a different format for the arguments). If there is a conflict, you may need to update your PATH environment variable or fully qualify the executable path (e.g. /usr/local/bin/po2json instead of po2json).

Creating a new language dictionary

To create a dictionary for a new language, run the following, where LANGUAGE_CODE is replaced with the language code for your target language, e.g. es (see Flask AppBuilder i18n documentation for more details):

pip install -r superset/translations/requirements.txt
pybabel init -i superset/translations/messages.pot -d superset/translations -l LANGUAGE_CODE

Then, extract strings for the new language.

Tips

Adding a new datasource

  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.

Creating a new visualization type

Here's an example as a Github PR with comments that describe what the different sections of the code do: apache#3013

Adding a DB migration

  1. Alter the model you want to change. This example will add a Column Annotations model.

    Example commit

  2. Generate the migration file

    superset db migrate -m 'add_metadata_column_to_annotation_model.py'

    This will generate a file in migrations/version/{SHA}_this_will_be_in_the_migration_filename.py.

    Example commit

  3. Upgrade the DB

    superset db upgrade

    The output should look like this:

    INFO  [alembic.runtime.migration] Context impl SQLiteImpl.
INFO  [alembic.runtime.migration] Will assume transactional DDL.
INFO  [alembic.runtime.migration] Running upgrade 1a1d627ebd8e -> 40a0a483dd12, add_metadata_column_to_annotation_model.py

  4. Add column to view

    Since there is a new column, we need to add it to the AppBuilder Model view.

    Example commit

Merging DB migrations

When two DB migrations collide, you'll get an error message like this one:

alembic.util.exc.CommandError: Multiple head revisions are present for
given argument 'head'; please specify a specific target
revision, '<branchname>@head' to narrow to a specific head,
or 'heads' for all heads`

To fix it:

  1. Get the migration heads

    superset db heads

    This should list two or more migration hashes.

  2. Create a new merge migration

    superset db merge {HASH1} {HASH2}

  3. Upgrade the DB to the new checkpoint

    superset db upgrade