mirror of https://github.com/apache/superset.git
438 lines
15 KiB
Markdown
438 lines
15 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. 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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3. 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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4. Code will be reviewed by re running the unittests, flake8 and syntax
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should be as rigorous as the core Python project.
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5. Please rebase and resolve all conflicts before submitting.
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6. 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 dev-reqs-for-docs.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 -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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## 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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## Testing
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Before running python unit tests, please setup local testing environment:
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```
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pip install -r dev-reqs.txt
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```
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All python tests can be run with:
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./run_tests.sh
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Alternatively, you can run a specific test with:
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./run_specific_test.sh tests.core_tests:CoreTests.test_function_name
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Note that before running specific tests, you have to both setup the local testing environment and run all tests.
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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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flake8
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# for javascript
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npm run lint
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## Linting with codeclimate
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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.
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*Install the codeclimate cli tool*
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```
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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
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brew install docker
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docker-machine create --driver virtual box default
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docker-machine env default
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eval "$(docker-machine env default)"
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docker pull codeclimate/codeclimate
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brew tap codeclimate/formulae
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brew install codeclimate
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```
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*Run the lint command:*
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```
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docker-machine start
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eval "$(docker-machine env default)”
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codeclimate analyze
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```
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More info can be found here: https://docs.codeclimate.com/docs/open-source-free
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## API documentation
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Generate the documentation with:
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cd docs && ./build.sh
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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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.. code::
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# install doc dependencies
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pip install -r dev-reqs-for-docs.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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