mirror of https://github.com/apache/superset.git
508 lines
18 KiB
Markdown
508 lines
18 KiB
Markdown
# Contributing
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Contributions are welcome and are greatly appreciated! Every
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little bit helps, and credit will always be given.
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You can contribute in many ways:
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## Types of Contributions
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### Report Bugs
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Report bugs through GitHub
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If you are reporting a bug, please include:
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- Your operating system name and version.
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- Any details about your local setup that might be helpful in
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troubleshooting.
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- Detailed steps to reproduce the bug.
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When you post python stack traces please quote them using
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[markdown blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks/).
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### Fix Bugs
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Look through the GitHub issues for bugs. Anything tagged with "bug" is
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open to whoever wants to implement it.
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### Implement Features
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Look through the GitHub issues for features. Anything tagged with
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"feature" or "starter_task" is open to whoever wants to implement it.
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### Documentation
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Superset could always use better documentation,
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whether as part of the official Superset docs,
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in docstrings, `docs/*.rst` or even on the web as blog posts or
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articles.
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### Submit Feedback
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The best way to send feedback is to file an issue on GitHub.
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If you are proposing a feature:
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- Explain in detail how it would work.
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- Keep the scope as narrow as possible, to make it easier to
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implement.
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- Remember that this is a volunteer-driven project, and that
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contributions are welcome :)
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### Questions
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There is a dedicated [tag](https://stackoverflow.com/questions/tagged/apache-superset) on [stackoverflow](https://stackoverflow.com/). Please use it when asking questions.
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## Pull Request Guidelines
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Before you submit a pull request from your forked repo, check that it
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meets these guidelines:
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1. The pull request should include tests, either as doctests,
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unit tests, or both.
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2. Run `tox` and resolve all errors and test failures.
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3. If the pull request adds functionality, the docs should be updated
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as part of the same PR. Doc string are often sufficient, make
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sure to follow the sphinx compatible standards.
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4. The pull request should work for Python 2.7, and ideally Python 3.4+.
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``from __future__ import`` will be required in every `.py` file soon.
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5. If the pull request adds a Python dependency include it in `setup.py`
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denoting any specific restrictions and in `requirements.txt` pinned to a
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specific version which ensures that the application build is deterministic.
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6. Please rebase and resolve all conflicts before submitting.
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7. Please ensure the necessary checks pass and that code coverage does not
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decrease.
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8. If you are asked to update your pull request with some changes there's
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no need to create a new one. Push your changes to the same branch.
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## Documentation
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The latest documentation and tutorial are available [here](https://superset.incubator.apache.org/).
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Contributing to the official documentation is relatively easy, once you've setup
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your environment and done an edit end-to-end. The docs can be found in the
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`docs/` subdirectory of the repository, and are written in the
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[reStructuredText format](https://en.wikipedia.org/wiki/ReStructuredText) (.rst).
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If you've written Markdown before, you'll find the reStructuredText format familiar.
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Superset uses [Sphinx](http://www.sphinx-doc.org/en/1.5.1/) to convert the rst files
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in `docs/` to the final HTML output users see.
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Before you start changing the docs, you'll want to
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[fork the Superset project on Github](https://help.github.com/articles/fork-a-repo/).
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Once that new repository has been created, clone it on your local machine:
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git clone git@github.com:your_username/incubator-superset.git
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At this point, you may also want to create a
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[Python virtual environment](http://docs.python-guide.org/en/latest/dev/virtualenvs/)
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to manage the Python packages you're about to install:
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virtualenv superset-dev
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source superset-dev/bin/activate
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Finally, to make changes to the rst files and build the docs using Sphinx,
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you'll need to install a handful of dependencies from the repo you cloned:
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cd incubator-superset
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pip install -r docs/requirements.txt
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To get the feel for how to edit and build the docs, let's edit a file, build
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the docs and see our changes in action. First, you'll want to
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[create a new branch](https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging)
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to work on your changes:
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git checkout -b changes-to-docs
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Now, go ahead and edit one of the files under `docs/`, say `docs/tutorial.rst`
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- change it however you want. Check out the
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[ReStructuredText Primer](http://docutils.sourceforge.net/docs/user/rst/quickstart.html)
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for a reference on the formatting of the rst files.
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Once you've made your changes, run this command from the root of the Superset
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repo to convert the docs into HTML:
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python setup.py build_sphinx
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You'll see a lot of output as Sphinx handles the conversion. After it's done, the
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HTML Sphinx generated should be in `docs/_build/html`. Go ahead and navigate there
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and start a simple web server so we can check out the docs in a browser:
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cd docs/_build/html
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python -m SimpleHTTPServer
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This will start a small Python web server listening on port 8000. Point your
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browser to [http://localhost:8000/](http://localhost:8000/), find the file
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you edited earlier, and check out your changes!
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If you've made a change you'd like to contribute to the actual docs, just commit
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your code, push your new branch to Github:
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git add docs/tutorial.rst
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git commit -m 'Awesome new change to tutorial'
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git push origin changes-to-docs
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Then, [open a pull request](https://help.github.com/articles/about-pull-requests/).
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If you're adding new images to the documentation, you'll notice that the images
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referenced in the rst, e.g.
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.. image:: _static/img/tutorial/tutorial_01_sources_database.png
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aren't actually included in that directory. _Instead_, you'll want to add and commit
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images (and any other static assets) to the _superset/assets/images_ directory.
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When the docs are being pushed to [Apache Superset (incubating)](https://superset.incubator.apache.org/), images
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will be moved from there to the _\_static/img_ directory, just like they're referenced
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in the docs.
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For example, the image referenced above actually lives in
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superset/assets/images/tutorial
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Since the image is moved during the documentation build process, the docs reference the
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image in
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_static/img/tutorial
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instead.
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## Setting up a Python development environment
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Check the [OS dependencies](https://superset.incubator.apache.org/installation.html#os-dependencies) before follows these steps.
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# fork the repo on GitHub and then clone it
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# alternatively you may want to clone the main repo but that won't work
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# so well if you are planning on sending PRs
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# git clone git@github.com:apache/incubator-superset.git
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# [optional] setup a virtual env and activate it
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virtualenv env
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source env/bin/activate
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# install for development
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pip install -r requirements.txt
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pip install -e .
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# Create an admin user
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fabmanager create-admin --app superset
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# Initialize the database
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superset db upgrade
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# Create default roles and permissions
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superset init
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# Load some data to play with
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superset load_examples
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# start a dev web server
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superset runserver -d
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### Logging to the browser console
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When debugging your application, you can have the server logs sent directly to the browser console:
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superset runserver -d --console-log
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You can log anything to the browser console, including objects:
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from superset import app
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app.logger.error('An exception occurred!')
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app.logger.info(form_data)
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## Setting up the node / npm javascript environment
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`superset/assets` contains all npm-managed, front end assets.
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Flask-Appbuilder itself comes bundled with jQuery and bootstrap.
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While these may be phased out over time, these packages are currently not
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managed with npm.
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### Node/npm versions
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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.
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### Using npm to generate bundled files
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#### npm
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First, npm must be available in your environment. If it is not you can run the following commands
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(taken from [this source](https://gist.github.com/DanHerbert/9520689))
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```
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brew install node --without-npm
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echo prefix=~/.npm-packages >> ~/.npmrc
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curl -L https://www.npmjs.com/install.sh | sh
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```
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The final step is to add `~/.npm-packages/bin` to your `PATH` so commands you install globally are usable.
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Add something like this to your `.bashrc` file, then `source ~/.bashrc` to reflect the change.
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```
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export PATH="$HOME/.npm-packages/bin:$PATH"
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```
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#### npm packages
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To install third party libraries defined in `package.json`, run the
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following within the `superset/assets/` directory which will install them in a
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new `node_modules/` folder within `assets/`.
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```bash
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# from the root of the repository, move to where our JS package.json lives
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cd superset/assets/
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# install yarn, a replacement for `npm install` that is faster and more deterministic
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npm install -g yarn
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# run yarn to fetch all the dependencies
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yarn
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```
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To parse and generate bundled files for superset, run either of the
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following commands. The `dev` flag will keep the npm script running and
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re-run it upon any changes within the assets directory.
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```
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# Copies a conf file from the frontend to the backend
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npm run sync-backend
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# Compiles the production / optimized js & css
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npm run prod
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# Start a web server that manages and updates your assets as you modify them
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npm run dev
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```
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For every development session you will have to start a flask dev server
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as well as an npm watcher
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```
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superset runserver -d -p 8081
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npm run dev
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```
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#### Upgrading npm packages
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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/)
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## Testing
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All tests are carried out in [tox](http://tox.readthedocs.io/en/latest/index.html)
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a standardized testing framework mostly for Python (though we also used it for Javascript).
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All python tests can be run with any of the tox [environments](http://tox.readthedocs.io/en/latest/example/basic.html#a-simple-tox-ini-default-environments), via,
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tox -e <environment>
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i.e.,
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tox -e py27
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tox -e py34
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Alternatively, you can run all tests in a single file via,
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tox -e <environment> -- tests/test_file.py
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or for a specific test via,
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tox -e <environment> -- tests/test_file.py:TestClassName.test_method_name
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Note that the test environment uses a temporary directory for defining the
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SQLite databases which will be cleared each time before the group of test
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commands are invoked.
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We use [Mocha](https://mochajs.org/), [Chai](http://chaijs.com/) and [Enzyme](http://airbnb.io/enzyme/) to test Javascript. Tests can be run with:
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cd /superset/superset/assets/javascripts
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npm i
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npm run test
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## Linting
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Lint the project with:
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# for python
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tox -e flake8
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# for javascript
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tox -e eslint
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## API documentation
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Generate the documentation with:
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pip install -r docs/requirements.txt
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python setup.py build_sphinx
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## CSS Themes
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As part of the npm build process, CSS for Superset is compiled from `Less`, a dynamic stylesheet language.
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It's possible to customize or add your own theme to Superset, either by overriding CSS rules or preferably
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by modifying the Less variables or files in `assets/stylesheets/less/`.
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The `variables.less` and `bootswatch.less` files that ship with Superset are derived from
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[Bootswatch](https://bootswatch.com) and thus extend Bootstrap. Modify variables in these files directly, or
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swap them out entirely with the equivalent files from other Bootswatch (themes)[https://github.com/thomaspark/bootswatch.git]
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## Translations
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We use [Babel](http://babel.pocoo.org/en/latest/) to translate Superset. The
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key is to instrument the strings that need translation using
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`from flask_babel import lazy_gettext as _`. Once this is imported in
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a module, all you have to do is to `_("Wrap your strings")` using the
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underscore `_` "function".
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We use `import {t, tn, TCT} from locales;` in js, JSX file, locales is in `./superset/assets/javascripts/` directory.
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To enable changing language in your environment, you can simply add the
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`LANGUAGES` parameter to your `superset_config.py`. Having more than one
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options here will add a language selection dropdown on the right side of the
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navigation bar.
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LANGUAGES = {
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'en': {'flag': 'us', 'name': 'English'},
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'fr': {'flag': 'fr', 'name': 'French'},
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'zh': {'flag': 'cn', 'name': 'Chinese'},
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}
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As per the [Flask AppBuilder documentation] about translation, to create a
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new language dictionary, run the following command (where `es` is replaced with
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the language code for your target language):
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pybabel init -i superset/translations/messages.pot -d superset/translations -l es
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Then it's a matter of running the statement below to gather all strings that
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need translation
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fabmanager babel-extract --target superset/translations/ --output superset/translations/messages.pot --config superset/translations/babel.cfg -k _ -k __ -k t -k tn -k tct
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You can then translate the strings gathered in files located under
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`superset/translation`, where there's one per language. For the translations
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to take effect, they need to be compiled using this command:
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fabmanager babel-compile --target superset/translations/
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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.
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We need to be compiled using this command:
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npm install po2json -g
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Execute this command to convert the en PO file into a json file:
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po2json -d superset -f jed1.x superset/translations/en/LC_MESSAGES/messages.po superset/translations/en/LC_MESSAGES/messages.json
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If you get errors running `po2json`, you might be running the ubuntu package with the same
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name rather than the nodejs package (they have a different format for the arguments). You
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need to be running the nodejs version, and so if there is a conflict you may need to point
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directly at `/usr/local/bin/po2json` rather than just `po2json`.
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## Adding new datasources
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1. Create Models and Views for the datasource, add them under superset folder, like a new my_models.py
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with models for cluster, datasources, columns and metrics and my_views.py with clustermodelview
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and datasourcemodelview.
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2. Create db migration files for the new models
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3. Specify this variable to add the datasource model and from which module it is from in config.py:
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For example:
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`ADDITIONAL_MODULE_DS_MAP = {'superset.my_models': ['MyDatasource', 'MyOtherDatasource']}`
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This means it'll register MyDatasource and MyOtherDatasource in superset.my_models module in the source registry.
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## Creating a new visualization type
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Here's an example as a Github PR with comments that describe what the
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different sections of the code do:
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https://github.com/apache/incubator-superset/pull/3013
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## Refresh documentation website
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Every once in a while we want to compile the documentation and publish it.
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Here's how to do it.
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```
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# install doc dependencies
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pip install -r docs/requirements.txt
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# build the docs
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python setup.py build_sphinx
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# copy html files to temp folder
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cp -r docs/_build/html/ /tmp/tmp_superset_docs/
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# clone the docs repo
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cd ~/
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git clone https://git-wip-us.apache.org/repos/asf/incubator-superset-site.git
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# copy
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cp -r /tmp/tmp_superset_docs/ ~/incubator-superset-site.git/
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# commit and push to `asf-site` branch
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cd ~/incubator-superset-site.git/
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git checkout asf-site
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git add .
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git commit -a -m "New doc version"
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git push origin master
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```
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## Publishing a Pypi release
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We create a branch that goes along each minor release `0.24`
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and micro releases get corresponding tags as in `0.24.0`. Git history should
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never be altered in release branches.
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Bug fixes and security-related patches get cherry-picked
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(usually from master) as in `git cherry-pick -x {SHA}`.
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Following a set of cherries being picked, a release can be pushed to
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Pypi as follows:
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```
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# branching off of master
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git checkout -b 0.25
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# cherry-picking a SHA
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git cherry-pick -x f9d85bd2e1fd9bc233d19c76bed09467522b968a
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# repeat with other SHAs, don't forget the -x
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# source of thruth for release numbers live in package.json
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vi superset/assets/package.json
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# hard code release in file, commit to the release branch
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git commit -a -m "0.25.0"
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# create the release tag in the release branch
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git tag 0.25.0
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git push apache 0.25 --tags
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# check travis to confirm the build succeeded as
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# you shouldn't assume that a clean cherry will be clean
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# when landing on a new sundae
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# compile the JS, and push to pypi
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# to run this part you'll need a pypi account and rights on the
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# superset package. Committers that want to ship releases
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# should have this access.
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# You'll also need a `.pypirc` as specified here:
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# http://peterdowns.com/posts/first-time-with-pypi.html
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./pypi_push.sh
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# publish an update to the CHANGELOG.md for the right version range
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# looking the latest CHANGELOG entry for the second argument
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./gen_changelog.sh 0.22.1 0.25.0
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# this will overwrite the CHANGELOG.md with only the version range
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# so you'll want to copy paste that on top of the previous CHANGELOG.md
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# open a PR against `master`
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```
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In the future we'll start publishing release candidates for minor releases
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only, but typically not for micro release.
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The process will be similar to the process described above, expect the
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tags will be formated `0.25.0rc1`, `0.25.0rc2`, ..., until consensus
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is reached.
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We should also have a Github PR label process to target the proper
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release, and tooling helping keeping track of all the cherries and
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target versions.
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For Apache releases, the process will be a bit heavier and should get
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documented here. There will be extra steps for signing the binaries,
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with a PGP key and providing MD5, Apache voting, as well as
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publishing to Apache's SVN repository. View the ASF docs for more
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information.
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