Contributions are welcome and are greatly appreciated! Every little bit helps, and credit will always be given.
You can contribute in many ways:
Report bugs through GitHub
If you are reporting a bug, please include:
When you post python stack traces please quote them using markdown blocks.
Look through the GitHub issues for bugs. Anything tagged with “bug” is open to whoever wants to implement it.
Look through the GitHub issues for features. Anything tagged with “feature” or “starter_task” is open to whoever wants to implement it.
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.
The best way to send feedback is to file an issue on GitHub.
If you are proposing a feature:
There is a dedicated tag on stackoverflow. Please use it when asking questions.
Before you submit a pull request from your forked repo, check that it meets these guidelines:
tox and resolve all errors and test failures.from __future__ import will be required in every .py file soon.setup.py denoting any specific restrictions and in requirements.txt pinned to a specific version which ensures that the application build is deterministic.The latest documentation and tutorial are available here.
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.
Before you start changing the docs, you'll want to fork the Superset project on Github. Once that new repository has been created, clone it on your local machine:
git clone git@github.com:your_username/incubator-superset.git
At this point, you may also want to create a Python virtual environment to manage the Python packages you're about to install:
virtualenv superset-dev source superset-dev/bin/activate
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:
cd incubator-superset 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
Once you've made your changes, run this command from the root of the Superset repo to convert the docs into HTML:
python setup.py build_sphinx
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. Go ahead and 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.
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 included in that directory. Instead, you’ll want to add and commit images (and any other static assets) to the superset/assets/images directory. When the docs are being pushed to Apache Superset (incubating), images will be moved 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.
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:apache/incubator-superset.git # [optional] setup a virtual env and activate it virtualenv env source env/bin/activate # install for development pip install -r requirements.txt 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 a dev web server superset runserver -d
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)
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.
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.
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"
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/.
# from the root of the repository, move to where our JS package.json lives cd superset/assets/ # install yarn, a replacement for `npm install` that is faster and more deterministic npm install -g yarn # run yarn to fetch all the dependencies yarn
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.
# Copies a conf file from the frontend to the backend npm run sync-backend # 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
Should you add or upgrade a npm package, which involves changing package.json, you'll need to re-run yarn install and push the newly generated yarn.lock file so we get the reproducible build. More information at (https://yarnpkg.com/blog/2016/11/24/lockfiles-for-all/)
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 py34
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.
We use Mocha, Chai and Enzyme to test Javascript. Tests can be run with:
cd /superset/superset/assets/javascripts npm i npm run test
Lint the project with:
# for python tox -e flake8 # for javascript tox -e eslint
Generate the documentation with:
pip install -r docs/requirements.txt python setup.py build_sphinx
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]
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”.
We use import {t, tn, TCT} from locales; in js, JSX file, locales is in ./superset/assets/javascripts/ directory.
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 (where es is replaced with the language code for your target language):
pybabel init -i superset/translations/messages.pot -d superset/translations -l es
Then it's a matter of running the statement below to gather all strings that need 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, they need to be compiled using this command:
fabmanager babel-compile --target superset/translations/
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. We need to be compiled using this command:
npm install po2json -g
Execute this command to 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). You need to be running the nodejs version, and so if there is a conflict you may need to point directly at /usr/local/bin/po2json rather than just po2json.
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.
Create db migration files for the new models
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.
Here's an example as a Github PR with comments that describe what the different sections of the code do: https://github.com/apache/incubator-superset/pull/3013
Every once in a while we want to compile the documentation and publish it. Here's how to do it.
# install doc dependencies
pip install -r docs/requirements.txt
# build the docs
python setup.py build_sphinx
# copy html files to temp folder
cp -r docs/_build/html/ /tmp/tmp_superset_docs/
# clone the docs repo
cd ~/
git clone https://git-wip-us.apache.org/repos/asf/incubator-superset-site.git
# copy
cp -r /tmp/tmp_superset_docs/ ~/incubator-superset-site.git/
# commit and push to `asf-site` branch
cd ~/incubator-superset-site.git/
git checkout asf-site
git add .
git commit -a -m "New doc version"
git push origin master
We create a branch that goes along each minor release 0.24 and micro releases get corresponding tags as in 0.24.0. Git history should never be altered in release branches. Bug fixes and security-related patches get cherry-picked (usually from master) as in git cherry-pick -x {SHA}.
Following a set of cherries being picked, a release can be pushed to Pypi as follows:
# branching off of master
git checkout -b 0.25
# cherry-picking a SHA
git cherry-pick -x f9d85bd2e1fd9bc233d19c76bed09467522b968a
# repeat with other SHAs, don't forget the -x
# source of thruth for release numbers live in package.json
vi superset/assets/package.json
# hard code release in file, commit to the release branch
git commit -a -m "0.25.0"
# create the release tag in the release branch
git tag 0.25.0
git push apache 0.25 --tags
# check travis to confirm the build succeeded as
# you shouldn't assume that a clean cherry will be clean
# when landing on a new sundae
# compile the JS, and push to pypi
# to run this part you'll need a pypi account and rights on the
# superset package. Committers that want to ship releases
# should have this access.
# You'll also need a `.pypirc` as specified here:
# http://peterdowns.com/posts/first-time-with-pypi.html
./pypi_push.sh
# publish an update to the CHANGELOG.md for the right version range
# looking the latest CHANGELOG entry for the second argument
./gen_changelog.sh 0.22.1 0.25.0
# this will overwrite the CHANGELOG.md with only the version range
# so you'll want to copy paste that on top of the previous CHANGELOG.md
# open a PR against `master`
In the future we'll start publishing release candidates for minor releases only, but typically not for micro release. The process will be similar to the process described above, expect the tags will be formated 0.25.0rc1, 0.25.0rc2, ..., until consensus is reached.
We should also have a Github PR label process to target the proper release, and tooling helping keeping track of all the cherries and target versions.
For Apache releases, the process will be a bit heavier and should get documented here. There will be extra steps for signing the binaries, with a PGP key and providing MD5, Apache voting, as well as publishing to Apache's SVN repository. View the ASF docs for more information.