docs: reorganize the CONTRIBUTING section (#28220)

Co-authored-by: Sam Firke <sfirke@users.noreply.github.com>
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---
title: Contributing to Superset
hide_title: true
sidebar_position: 1
version: 1
---
## Contributing to Superset
Superset is an [Apache Software foundation](https://www.apache.org/theapacheway/index.html) project.
The core contributors (or committers) to Superset communicate primarily in the following channels (
which can be joined by anyone):
- [Mailing list](https://lists.apache.org/list.html?dev@superset.apache.org)
- [Apache Superset Slack community](http://bit.ly/join-superset-slack)
- [GitHub issues](https://github.com/apache/superset/issues)
- [GitHub pull requests](https://github.com/apache/superset/pulls)
- [GitHub discussions](https://github.com/apache/superset/discussions)
- [Superset Community Calendar](https://superset.apache.org/community)
More references:
- [Comprehensive Tutorial for Contributing Code to Apache Superset](https://preset.io/blog/tutorial-contributing-code-to-apache-superset/)
- [CONTRIBUTING Guide on GitHub](https://github.com/apache/superset/blob/master/CONTRIBUTING.md)
- [Superset Wiki (code guidelines and additional resources)](https://github.com/apache/superset/wiki)

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---
title: Contributing to Superset
sidebar_position: 1
version: 1
---
# Contributing to Superset
Superset is an [Apache Software foundation](https://www.apache.org/theapacheway/index.html) project.
The core contributors (or committers) to Superset communicate primarily in the following channels (
which can be joined by anyone):
- [Mailing list](https://lists.apache.org/list.html?dev@superset.apache.org)
- [Apache Superset Slack community](http://bit.ly/join-superset-slack)
- [GitHub issues](https://github.com/apache/superset/issues)
- [GitHub pull requests](https://github.com/apache/superset/pulls)
- [GitHub discussions](https://github.com/apache/superset/discussions)
- [Superset Community Calendar](https://superset.apache.org/community)
More references:
- [Comprehensive Tutorial for Contributing Code to Apache Superset](https://preset.io/blog/tutorial-contributing-code-to-apache-superset/)
- [Superset Wiki (code guidelines and additional resources)](https://github.com/apache/superset/wiki)
## Orientation
Here's a list of repositories that contain Superset-related packages:
- [apache/superset](https://github.com/apache/superset)
is the main repository containing the `apache-superset` Python package
distributed on
[pypi](https://pypi.org/project/apache-superset/). This repository
also includes Superset's main TypeScript/JavaScript bundles and react apps under
the [superset-frontend](https://github.com/apache/superset/tree/master/superset-frontend)
folder.
- [github.com/apache-superset](https://github.com/apache-superset) is the
GitHub organization under which we manage Superset-related
small tools, forks and Superset-related experimental ideas.
## Types of Contributions
### Report Bug
The best way to report a bug is to file an issue on GitHub. Please include:
- Your operating system name and version.
- Superset version.
- Detailed steps to reproduce the bug.
- Any details about your local setup that might be helpful in troubleshooting.
When posting Python stack traces, please quote them using
[Markdown blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks/).
_Please note that feature requests opened as GitHub Issues will be moved to Discussions._
### Submit Ideas or Feature Requests
The best way is to start an ["Ideas" Discussion thread](https://github.com/apache/superset/discussions/categories/ideas) on GitHub:
- 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 your contributions are as welcome as anyone's :)
To propose large features or major changes to codebase, and help usher in those changes, please create a **Superset Improvement Proposal (SIP)**. See template from [SIP-0](https://github.com/apache/superset/issues/5602)
### Fix Bugs
Look through the GitHub issues. Issues tagged with `#bug` are
open to whoever wants to implement them.
### Implement Features
Look through the GitHub issues. Issues tagged with
`#feature` are open to whoever wants to implement them.
### 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](#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 into 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](#translating) for more details.
### Ask Questions
There is a dedicated [`apache-superset` tag](https://stackoverflow.com/questions/tagged/apache-superset) on [StackOverflow](https://stackoverflow.com/). Please use it when asking questions.
## Types of Contributors
Following the project governance model of the Apache Software Foundation (ASF), Apache Superset has a specific set of contributor roles:
### PMC Member
A Project Management Committee (PMC) member is a person who has been elected by the PMC to help manage the project. PMC members are responsible for the overall health of the project, including community development, release management, and project governance. PMC members are also responsible for the technical direction of the project.
For more information about Apache Project PMCs, please refer to https://www.apache.org/foundation/governance/pmcs.html
### Committer
A committer is a person who has been elected by the PMC to have write access (commit access) to the code repository. They can modify the code, documentation, and website and accept contributions from others.
The official list of committers and PMC members can be found [here](https://projects.apache.org/committee.html?superset).
### Contributor
A contributor is a person who has contributed to the project in any way, including but not limited to code, tests, documentation, issues, and discussions.
> You can also review the Superset project's guidelines for PMC member promotion here: https://github.com/apache/superset/wiki/Guidelines-for-promoting-Superset-Committers-to-the-Superset-PMC
### Security Team
The security team is a selected subset of PMC members, committers and non-committers who are responsible for handling security issues.
New members of the security team are selected by the PMC members in a vote. You can request to be added to the team by sending a message to private@superset.apache.org. However, the team should be small and focused on solving security issues, so the requests will be evaluated on a case-by-case basis and the team size will be kept relatively small, limited to only actively security-focused contributors.
This security team must follow the [ASF vulnerability handling process](https://apache.org/security/committers.html#asf-project-security-for-committers).
Each new security issue is tracked as a JIRA ticket on the [ASF's JIRA Superset security project](https://issues.apache.org/jira/secure/RapidBoard.jspa?rapidView=588&projectKey=SUPERSETSEC)
Security team members must:
- Have an [ICLA](https://www.apache.org/licenses/contributor-agreements.html) signed with Apache Software Foundation.
- Not reveal information about pending and unfixed security issues to anyone (including their employers) unless specifically authorised by the security team members, e.g., if the security team agrees that diagnosing and solving an issue requires the involvement of external experts.
A release manager, the contributor overseeing the release of a specific version of Apache Superset, is by default a member of the security team. However, they are not expected to be active in assessing, discussing, and fixing security issues.
Security team members should also follow these general expectations:
- Actively participate in assessing, discussing, fixing, and releasing security issues in Superset.
- Avoid discussing security fixes in public forums. Pull request (PR) descriptions should not contain any information about security issues. The corresponding JIRA ticket should contain a link to the PR.
- Security team members who contribute to a fix may be listed as remediation developers in the CVE report, along with their job affiliation (if they choose to include it).

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---
title: Conventions and Typing
hide_title: true
sidebar_position: 7
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---
## Conventions
### Python
Parameters in the `config.py` (which are accessible via the Flask app.config dictionary) are assumed to always be defined and thus should be accessed directly via,
```python
blueprints = app.config["BLUEPRINTS"]
```
rather than,
```python
blueprints = app.config.get("BLUEPRINTS")
```
or similar as the later will cause typing issues. The former is of type `List[Callable]` whereas the later is of type `Optional[List[Callable]]`.
## Typing
### Python
To ensure clarity, consistency, all readability, _all_ new functions should use
[type hints](https://docs.python.org/3/library/typing.html) and include a
docstring.
Note per [PEP-484](https://www.python.org/dev/peps/pep-0484/#exceptions) no
syntax for listing explicitly raised exceptions is proposed and thus the
recommendation is to put this information in a docstring, i.e.,
```python
import math
from typing import Union
def sqrt(x: Union[float, int]) -> Union[float, int]:
"""
Return the square root of x.
:param x: A number
:returns: The square root of the given number
:raises ValueError: If the number is negative
"""
return math.sqrt(x)
```
### TypeScript
TypeScript is fully supported and is the recommended language for writing all new frontend components. When modifying existing functions/components, migrating to TypeScript is appreciated, but not required. Examples of migrating functions/components to TypeScript can be found in [#9162](https://github.com/apache/superset/pull/9162) and [#9180](https://github.com/apache/superset/pull/9180).

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---
title: Creating Visualization Plugins
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---
## Creating Visualization Plugins
Visualizations in Superset are implemented in JavaScript or TypeScript. Superset
comes preinstalled with several visualizations types (hereafter "viz plugins") that
can be found under the `superset-frontend/plugins` directory. Viz plugins are added to
the application in the `superset-frontend/src/visualizations/presets/MainPreset.js`.
The Superset project is always happy to review proposals for new high quality viz
plugins. However, for highly custom viz types it is recommended to maintain a fork
of Superset, and add the custom built viz plugins by hand.
**Note:** Additional community-generated resources about creating and deploying custom visualization plugins can be found on the [Superset Wiki](https://github.com/apache/superset/wiki/Community-Resource-Library#creating-custom-data-visualizations)
### Prerequisites
In order to create a new viz plugin, you need the following:
- Run MacOS or Linux (Windows is not officially supported, but may work)
- Node.js 16
- npm 7 or 8
A general familiarity with [React](https://reactjs.org/) and the npm/Node system is
also recommended.
### Creating a simple Hello World viz plugin
To get started, you need the Superset Yeoman Generator. It is recommended to use the
version of the template that ships with the version of Superset you are using. This
can be installed by doing the following:
```bash
npm i -g yo
cd superset-frontend/packages/generator-superset
npm i
npm link
```
After this you can proceed to create your viz plugin. Create a new directory for your
viz plugin with the prefix `superset-plugin-chart` and run the Yeoman generator:
```bash
mkdir /tmp/superset-plugin-chart-hello-world
cd /tmp/superset-plugin-chart-hello-world
```
Initialize the viz plugin:
```bash
yo @superset-ui/superset
```
After that the generator will ask a few questions (the defaults should be fine):
```
$ yo @superset-ui/superset
_-----_ ╭──────────────────────────╮
| | │ Welcome to the │
|--(o)--| │ generator-superset │
`---------´ │ generator! │
( _´U`_ ) ╰──────────────────────────╯
/___A___\ /
| ~ |
__'.___.'__
´ ` |° ´ Y `
? Package name: superset-plugin-chart-hello-world
? Description: Hello World
? What type of chart would you like? Time-series chart
create package.json
create .gitignore
create babel.config.js
create jest.config.js
create README.md
create tsconfig.json
create src/index.ts
create src/plugin/buildQuery.ts
create src/plugin/controlPanel.ts
create src/plugin/index.ts
create src/plugin/transformProps.ts
create src/types.ts
create src/SupersetPluginChartHelloWorld.tsx
create test/index.test.ts
create test/__mocks__/mockExportString.js
create test/plugin/buildQuery.test.ts
create test/plugin/transformProps.test.ts
create types/external.d.ts
create src/images/thumbnail.png
```
To build the viz plugin, run the following commands:
```
npm i --force
npm run build
```
Alternatively, to run the viz plugin in development mode (=rebuilding whenever changes
are made), start the dev server with the following command:
```
npm run dev
```
To add the package to Superset, go to the `superset-frontend` subdirectory in your
Superset source folder run
```bash
npm i -S /tmp/superset-plugin-chart-hello-world
```
If you publish your package to npm, you can naturally install directly from there, too.
After this edit the `superset-frontend/src/visualizations/presets/MainPreset.js`
and make the following changes:
```js
import { SupersetPluginChartHelloWorld } from 'superset-plugin-chart-hello-world';
```
to import the viz plugin and later add the following to the array that's passed to the
`plugins` property:
```js
new SupersetPluginChartHelloWorld().configure({ key: 'ext-hello-world' }),
```
After that the viz plugin should show up when you run Superset, e.g. the development
server:
```bash
npm run dev-server
```

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---
title: Setting up a Development Environment
sidebar_position: 3
version: 1
---
# Setting up a Development Envrionment
The documentation in this section is a bit of a patchwork of knowledge representing the
multitude of ways that exist to run Superset (`docker-compose`, just "docker", on "metal", using
a Makefile).
:::note
Now we have evolved to recommend and support `docker-compose` more actively as the main way
to run Superset for development and preserve your sanity. **Most people should stick to
the first few sections - ("Fork & Clone", "docker-compose" and "Installing Dev Tools")**
:::
## Fork and Clone
First, [fork the repository on GitHub](https://help.github.com/articles/about-forks/),
then clone it.
Second, you can clone the main repository directly, but you won't be able to send pull requests.
```bash
git clone git@github.com:your-username/superset.git
cd superset
```
## docker-compose (recommended!)
Setting things up to squeeze an "hello world" into any part of Superset should be as simple as
```bash
docker-compose up
```
Note that:
- this will pull/build docker images and run a cluster of services, including:
- A Superset **Flask web server**, mounting the local python repo/code
- A Superset **Celery worker**, also mounting the local python repo/code
- A Superset **Node service**, mounting, compiling and bundling the JS/TS assets
- A Superset **Node websocket service** to power the async backend
- **Postgres** as the metadata database and to store example datasets, charts and dashboards whic
should be populated upon startup
- **Redis** as the message queue for our async backend and caching backend
- It'll load up examples into the database upon first startup
- all other details and pointers available in
[docker-compose.yml](https://github.com/apache/superset/blob/master/docker-compose.yml)
- The local repository is mounted withing the services, meaning updating
the code on the host will be reflected in the docker images
- Superset is served at localhost:8088/
- You can login with admin/admin
:::caution
Since `docker-compose` is primarily designed to run a set of containers on **a single host**
and can't credibly support **high availability** as a result, we do not support nor recommend
using our `docker-compose` constructs to support production-type use-cases. For single host
environments, we recommend using [minikube](https://minikube.sigs.k8s.io/docs/start/) along
our [installing on k8s](https://superset.apache.org/docs/installation/running-on-kubernetes)
documentation.
configured to be secure.
:::
## Installing Development Tools
:::note
While docker-compose simplifies a lot of the setup, there are still
many things you'll want to set up locally to power your IDE, and things like
**commit hooks**, **linters**, and **test-runners**. Note that you can do these
things inside docker images with commands like `docker-compose exec superset_app bash` for
instance, but many people like to run that tooling from their host.
:::
### Python environment
Assuming you already have a way to setup your python environments
like `pyenv`, `virtualenv` or something else, all you should have to
do is to install our dev, pinned python requirements bundle
```bash
pip install -r requirements/development.txt
```
### Git Hooks
Superset uses Git pre-commit hooks courtesy of [pre-commit](https://pre-commit.com/).
To install run the following:
```bash
pre-commit install
```
A series of checks will now run when you make a git commit.
## Alternatives to docker-compose
:::caution
This part of the documentation is a patchwork of information related to setting up
development environments without `docker-compose` and are documented/supported to varying
degrees. It's been difficult to maintain this wide array of methods and insure they're
functioning across environments.
:::
### Flask server
#### OS Dependencies
Make sure your machine meets the [OS dependencies](https://superset.apache.org/docs/installation/pypi#os-dependencies) before following these steps.
You also need to install MySQL or [MariaDB](https://mariadb.com/downloads).
Ensure that you are using Python version 3.9, 3.10 or 3.11, then proceed with:
```bash
# Create a virtual environment and activate it (recommended)
python3 -m venv venv # setup a python3 virtualenv
source venv/bin/activate
# Install external dependencies
pip install -r requirements/development.txt
# Install Superset in editable (development) mode
pip install -e .
# Initialize the database
superset db upgrade
# Create an admin user in your metadata database (use `admin` as username to be able to load the examples)
superset fab create-admin
# Create default roles and permissions
superset init
# Load some data to play with.
# Note: you MUST have previously created an admin user with the username `admin` for this command to work.
superset load-examples
# Start the Flask dev web server from inside your virtualenv.
# Note that your page may not have CSS at this point.
# See instructions below how to build the front-end assets.
superset run -p 8088 --with-threads --reload --debugger --debug
```
Or you can install via our Makefile
```bash
# Create a virtual environment and activate it (recommended)
$ python3 -m venv venv # setup a python3 virtualenv
$ source venv/bin/activate
# install pip packages + pre-commit
$ make install
# Install superset pip packages and setup env only
$ make superset
# Setup pre-commit only
$ make pre-commit
```
**Note: the FLASK_APP env var should not need to be set, as it's currently controlled
via `.flaskenv`, however if needed, it should be set to `superset.app:create_app()`**
If you have made changes to the FAB-managed templates, which are not built the same way as the newer, React-powered front-end assets, you need to start the app without the `--with-threads` argument like so:
`superset run -p 8088 --reload --debugger --debug`
#### Dependencies
If you add a new requirement or update an existing requirement (per the `install_requires` section in `setup.py`) you must recompile (freeze) the Python dependencies to ensure that for CI, testing, etc. the build is deterministic. This can be achieved via,
```bash
$ python3 -m venv venv
$ source venv/bin/activate
$ python3 -m pip install -r requirements/development.txt
$ pip-compile-multi --no-upgrade
```
When upgrading the version number of a single package, you should run `pip-compile-multi` with the `-P` flag:
```bash
$ pip-compile-multi -P my-package
```
To bring all dependencies up to date as per the restrictions defined in `setup.py` and `requirements/*.in`, run pip-compile-multi` without any flags:
```bash
$ pip-compile-multi
```
This should be done periodically, but it is recommended to do thorough manual testing of the application to ensure no breaking changes have been introduced that aren't caught by the unit and integration tests.
#### 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 using the [ConsoleLog](https://github.com/betodealmeida/consolelog) package. You need to mutate the app, by adding the following to your `config.py` or `superset_config.py`:
```python
from console_log import ConsoleLog
def FLASK_APP_MUTATOR(app):
app.wsgi_app = ConsoleLog(app.wsgi_app, app.logger)
```
Then make sure you run your WSGI server using the right worker type:
```bash
gunicorn "superset.app:create_app()" -k "geventwebsocket.gunicorn.workers.GeventWebSocketWorker" -b 127.0.0.1:8088 --reload
```
You can log anything to the browser console, including objects:
```python
from superset import app
app.logger.error('An exception occurred!')
app.logger.info(form_data)
```
### Frontend
Frontend assets (TypeScript, JavaScript, CSS, and images) must be compiled in order to properly display the web UI. The `superset-frontend` directory contains all NPM-managed frontend assets. Note that for some legacy pages 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.
#### Prerequisite
##### nvm and node
First, be sure you are using the following versions of Node.js and npm:
- `Node.js`: Version 18
- `npm`: Version 10
We recommend using [nvm](https://github.com/nvm-sh/nvm) to manage your node environment:
```bash
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.37.0/install.sh | bash
incase it shows '-bash: nvm: command not found'
export NVM_DIR="$HOME/.nvm"
[ -s "$NVM_DIR/nvm.sh" ] && \. "$NVM_DIR/nvm.sh" # This loads nvm
[ -s "$NVM_DIR/bash_completion" ] && \. "$NVM_DIR/bash_completion" # This loads nvm bash_completion
cd superset-frontend
nvm install --lts
nvm use --lts
```
Or if you use the default macOS starting with Catalina shell `zsh`, try:
```zsh
sh -c "$(curl -fsSL https://raw.githubusercontent.com/nvm-sh/nvm/v0.37.0/install.sh)"
```
For those interested, you may also try out [avn](https://github.com/nvm-sh/nvm#deeper-shell-integration) to automatically switch to the node version that is required to run Superset frontend.
#### Install dependencies
Install third-party dependencies listed in `package.json` via:
```bash
# From the root of the repository
cd superset-frontend
# Install dependencies from `package-lock.json`
npm ci
```
Note that Superset uses [Scarf](https://docs.scarf.sh) to capture telemetry/analytics about versions being installed, including the `scarf-js` npm package and an analytics pixel. As noted elsewhere in this documentation, Scarf gathers aggregated stats for the sake of security/release strategy, and does not capture/retain PII. [You can read here](https://docs.scarf.sh/package-analytics/) about the `scarf-js` package, and various means to opt out of it, but you can opt out of the npm package _and_ the pixel by setting the `SCARF_ANALYTICS` envinronment variable to `false` or opt out of the pixel by adding this setting in `superset-frontent/package.json`:
```json
// your-package/package.json
{
// ...
"scarfSettings": {
"enabled": false
}
// ...
}
```
#### Build assets
There are three types of assets you can build:
1. `npm run build`: the production assets, CSS/JSS minified and optimized
2. `npm run dev-server`: local development assets, with sourcemaps and hot refresh support
3. `npm run build-instrumented`: instrumented application code for collecting code coverage from Cypress tests
If while using the above commands you encounter an error related to the limit of file watchers:
```bash
Error: ENOSPC: System limit for number of file watchers reached
```
The error is thrown because the number of files monitored by the system has reached the limit.
You can address this this error by increasing the number of inotify watchers.
The current value of max watches can be checked with:
```bash
cat /proc/sys/fs/inotify/max_user_watches
```
Edit the file /etc/sysctl.conf to increase this value.
The value needs to be decided based on the system memory [(see this StackOverflow answer for more context)](https://stackoverflow.com/questions/535768/what-is-a-reasonable-amount-of-inotify-watches-with-linux).
Open the file in editor and add a line at the bottom specifying the max watches values.
```bash
fs.inotify.max_user_watches=524288
```
Save the file and exit editor.
To confirm that the change succeeded, run the following command to load the updated value of max_user_watches from sysctl.conf:
```bash
sudo sysctl -p
```
#### Webpack dev server
The dev server by default starts at `http://localhost:9000` and proxies the backend requests to `http://localhost:8088`.
So a typical development workflow is the following:
1. [run Superset locally](#flask-server) using Flask, on port `8088` — but don't access it directly,<br/>
```bash
# Install Superset and dependencies, plus load your virtual environment first, as detailed above.
superset run -p 8088 --with-threads --reload --debugger --debug
```
2. in parallel, run the Webpack dev server locally on port `9000`,<br/>
```bash
npm run dev-server
```
3. access `http://localhost:9000` (the Webpack server, _not_ Flask) in your web browser. This will use the hot-reloading front-end assets from the Webpack development server while redirecting back-end queries to Flask/Superset: your changes on Superset codebase — either front or back-end — will then be reflected live in the browser.
It's possible to change the Webpack server settings:
```bash
# Start the dev server at http://localhost:9000
npm run dev-server
# Run the dev server on a non-default port
npm run dev-server -- --port=9001
# Proxy backend requests to a Flask server running on a non-default port
npm run dev-server -- --env=--supersetPort=8081
# Proxy to a remote backend but serve local assets
npm run dev-server -- --env=--superset=https://superset-dev.example.com
```
The `--superset=` option is useful in case you want to debug a production issue or have to setup Superset behind a firewall. It allows you to run Flask server in another environment while keep assets building locally for the best developer experience.
#### Other npm commands
Alternatively, there are other NPM commands you may find useful:
1. `npm run build-dev`: build assets in development mode.
2. `npm run dev`: built dev assets in watch mode, will automatically rebuild when a file changes
#### Docker (docker compose)
See docs [here](https://superset.apache.org/docs/installation/docker-compose)
#### Updating NPM packages
Use npm in the prescribed way, making sure that
`superset-frontend/package-lock.json` is updated according to `npm`-prescribed
best practices.
#### Feature flags
Superset supports a server-wide feature flag system, which eases the incremental development of features. To add a new feature flag, simply modify `superset_config.py` with something like the following:
```python
FEATURE_FLAGS = {
'SCOPED_FILTER': True,
}
```
If you want to use the same flag in the client code, also add it to the FeatureFlag TypeScript enum in [@superset-ui/core](https://github.com/apache/superset/blob/master/superset-frontend/packages/superset-ui-core/src/utils/featureFlags.ts). For example,
```typescript
export enum FeatureFlag {
SCOPED_FILTER = "SCOPED_FILTER",
}
```
`superset/config.py` contains `DEFAULT_FEATURE_FLAGS` which will be overwritten by
those specified under FEATURE_FLAGS in `superset_config.py`. For example, `DEFAULT_FEATURE_FLAGS = { 'FOO': True, 'BAR': False }` in `superset/config.py` and `FEATURE_FLAGS = { 'BAR': True, 'BAZ': True }` in `superset_config.py` will result
in combined feature flags of `{ 'FOO': True, 'BAR': True, 'BAZ': True }`.
The current status of the usability of each flag (stable vs testing, etc) can be found in `RESOURCES/FEATURE_FLAGS.md`.
## Git Hooks
Superset uses Git pre-commit hooks courtesy of [pre-commit](https://pre-commit.com/). To install run the following:
```bash
pip3 install -r requirements/development.txt
pre-commit install
```
A series of checks will now run when you make a git commit.
Alternatively it is possible to run pre-commit via tox:
```bash
tox -e pre-commit
```
Or by running pre-commit manually:
```bash
pre-commit run --all-files
```
## Linting
### Python
We use [Pylint](https://pylint.org/) for linting which can be invoked via:
```bash
# for python
tox -e pylint
```
In terms of best practices please avoid blanket disabling of Pylint messages globally (via `.pylintrc`) or top-level within the file header, albeit there being a few exceptions. Disabling should occur inline as it prevents masking issues and provides context as to why said message is disabled.
Additionally, the Python code is auto-formatted using [Black](https://github.com/python/black) which
is configured as a pre-commit hook. There are also numerous [editor integrations](https://black.readthedocs.io/en/stable/integrations/editors.html)
### TypeScript
```bash
cd superset-frontend
npm ci
# run eslint checks
npm run eslint -- .
# run tsc (typescript) checks
npm run type
```
If using the eslint extension with vscode, put the following in your workspace `settings.json` file:
```json
"eslint.workingDirectories": [
"superset-frontend"
]
```
## Testing
### Python Testing
All python tests are carried out in [tox](https://tox.readthedocs.io/en/latest/index.html)
a standardized testing framework.
All python tests can be run with any of the tox [environments](https://tox.readthedocs.io/en/latest/example/basic.html#a-simple-tox-ini-default-environments), via,
```bash
tox -e <environment>
```
For example,
```bash
tox -e py38
```
Alternatively, you can run all tests in a single file via,
```bash
tox -e <environment> -- tests/test_file.py
```
or for a specific test via,
```bash
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.
There is also a utility script included in the Superset codebase to run python integration tests. The [readme can be
found here](https://github.com/apache/superset/tree/master/scripts/tests)
To run all integration tests for example, run this script from the root directory:
```bash
scripts/tests/run.sh
```
You can run unit tests found in './tests/unit_tests' for example with pytest. It is a simple way to run an isolated test that doesn't need any database setup
```bash
pytest ./link_to_test.py
```
### Frontend Testing
We use [Jest](https://jestjs.io/) and [Enzyme](https://airbnb.io/enzyme/) to test TypeScript/JavaScript. Tests can be run with:
```bash
cd superset-frontend
npm run test
```
To run a single test file:
```bash
npm run test -- path/to/file.js
```
### Integration Testing
We use [Cypress](https://www.cypress.io/) for integration tests. Tests can be run by `tox -e cypress`. To open Cypress and explore tests first setup and run test server:
```bash
export SUPERSET_CONFIG=tests.integration_tests.superset_test_config
export SUPERSET_TESTENV=true
export CYPRESS_BASE_URL="http://localhost:8081"
superset db upgrade
superset load_test_users
superset load-examples --load-test-data
superset init
superset run --port 8081
```
Run Cypress tests:
```bash
cd superset-frontend
npm run build-instrumented
cd cypress-base
npm install
# run tests via headless Chrome browser (requires Chrome 64+)
npm run cypress-run-chrome
# run tests from a specific file
npm run cypress-run-chrome -- --spec cypress/e2e/explore/link.test.ts
# run specific file with video capture
npm run cypress-run-chrome -- --spec cypress/e2e/dashboard/index.test.js --config video=true
# to open the cypress ui
npm run cypress-debug
# to point cypress to a url other than the default (http://localhost:8088) set the environment variable before running the script
# e.g., CYPRESS_BASE_URL="http://localhost:9000"
CYPRESS_BASE_URL=<your url> npm run cypress open
```
See [`superset-frontend/cypress_build.sh`](https://github.com/apache/superset/blob/master/superset-frontend/cypress_build.sh).
As an alternative you can use docker compose environment for testing:
Make sure you have added below line to your /etc/hosts file:
`127.0.0.1 db`
If you already have launched Docker environment please use the following command to assure a fresh database instance:
`docker compose down -v`
Launch environment:
`CYPRESS_CONFIG=true docker compose up`
It will serve backend and frontend on port 8088.
Run Cypress tests:
```bash
cd cypress-base
npm install
npm run cypress open
```
### Debugging Server App
#### Local
For debugging locally using VSCode, you can configure a launch configuration file .vscode/launch.json such as
```json
{
"version": "0.2.0",
"configurations": [
{
"name": "Python: Flask",
"type": "python",
"request": "launch",
"module": "flask",
"env": {
"FLASK_APP": "superset",
"SUPERSET_ENV": "development"
},
"args": ["run", "-p 8088", "--with-threads", "--reload", "--debugger"],
"jinja": true,
"justMyCode": true
}
]
}
```
#### Raw Docker (without docker-compose)
Follow these instructions to debug the Flask app running inside a docker container. Note that
this will run a barebones Superset web server,
First add the following to the ./docker-compose.yaml file
```diff
superset:
env_file: docker/.env
image: *superset-image
container_name: superset_app
command: ["/app/docker/docker-bootstrap.sh", "app"]
restart: unless-stopped
+ cap_add:
+ - SYS_PTRACE
ports:
- 8088:8088
+ - 5678:5678
user: "root"
depends_on: *superset-depends-on
volumes: *superset-volumes
environment:
CYPRESS_CONFIG: "${CYPRESS_CONFIG}"
```
Start Superset as usual
```bash
docker compose up
```
Install the required libraries and packages to the docker container
Enter the superset_app container
```bash
docker exec -it superset_app /bin/bash
root@39ce8cf9d6ab:/app#
```
Run the following commands inside the container
```bash
apt update
apt install -y gdb
apt install -y net-tools
pip install debugpy
```
Find the PID for the Flask process. Make sure to use the first PID. The Flask app will re-spawn a sub-process every time you change any of the python code. So it's important to use the first PID.
```bash
ps -ef
UID PID PPID C STIME TTY TIME CMD
root 1 0 0 14:09 ? 00:00:00 bash /app/docker/docker-bootstrap.sh app
root 6 1 4 14:09 ? 00:00:04 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
root 10 6 7 14:09 ? 00:00:07 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
```
Inject debugpy into the running Flask process. In this case PID 6.
```bash
python3 -m debugpy --listen 0.0.0.0:5678 --pid 6
```
Verify that debugpy is listening on port 5678
```bash
netstat -tunap
Active Internet connections (servers and established)
Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name
tcp 0 0 0.0.0.0:5678 0.0.0.0:* LISTEN 462/python
tcp 0 0 0.0.0.0:8088 0.0.0.0:* LISTEN 6/python
```
You are now ready to attach a debugger to the process. Using VSCode you can configure a launch configuration file .vscode/launch.json like so.
```json
{
"version": "0.2.0",
"configurations": [
{
"name": "Attach to Superset App in Docker Container",
"type": "python",
"request": "attach",
"connect": {
"host": "127.0.0.1",
"port": 5678
},
"pathMappings": [
{
"localRoot": "${workspaceFolder}",
"remoteRoot": "/app"
}
]
}
]
}
```
VSCode will not stop on breakpoints right away. We've attached to PID 6 however it does not yet know of any sub-processes. In order to "wake up" the debugger you need to modify a python file. This will trigger Flask to reload the code and create a new sub-process. This new sub-process will be detected by VSCode and breakpoints will be activated.
### Debugging Server App in Kubernetes Environment
To debug Flask running in POD inside kubernetes cluster. You'll need to make sure the pod runs as root and is granted the SYS_TRACE capability.These settings should not be used in production environments.
```
securityContext:
capabilities:
add: ["SYS_PTRACE"]
```
See (set capabilities for a container)[https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#set-capabilities-for-a-container] for more details.
Once the pod is running as root and has the SYS_PTRACE capability it will be able to debug the Flask app.
You can follow the same instructions as in the docker-compose. Enter the pod and install the required library and packages; gdb, netstat and debugpy.
Often in a Kubernetes environment nodes are not addressable from outside the cluster. VSCode will thus be unable to remotely connect to port 5678 on a Kubernetes node. In order to do this you need to create a tunnel that port forwards 5678 to your local machine.
```
kubectl port-forward pod/superset-<some random id> 5678:5678
```
You can now launch your VSCode debugger with the same config as above. VSCode will connect to to 127.0.0.1:5678 which is forwarded by kubectl to your remote kubernetes POD.
### Storybook
Superset includes a [Storybook](https://storybook.js.org/) to preview the layout/styling of various Superset components, and variations thereof. To open and view the Storybook:
```bash
cd superset-frontend
npm run storybook
```
When contributing new React components to Superset, please try to add a Story alongside the component's `jsx/tsx` file.
## Translating
We use [Flask-Babel](https://python-babel.github.io/flask-babel/) to translate Superset.
In Python files, we import the magic `_` function using:
```python
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 TypeScript/JavaScript, the technique is similar:
we import `t` (simple translation), `tn` (translation containing a number).
```javascript
import { t, tn } from "@superset-ui/translation";
```
### 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.
```python
LANGUAGES = {
'en': {'flag': 'us', 'name': 'English'},
'fr': {'flag': 'fr', 'name': 'French'},
'zh': {'flag': 'cn', 'name': 'Chinese'},
}
```
### Updating language files
```bash
./scripts/babel_update.sh
```
This script will
1. update the template file `superset/translations/messages.pot` with current application strings.
2. update language files with the new extracted strings.
You can then translate the strings gathered in files located under
`superset/translation`, where there's one per language. You can use [Poedit](https://poedit.net/features)
to translate the `po` file more conveniently.
There are some [tutorials in the wiki](https://wiki.lxde.org/en/Translate_*.po_files_with_Poedit).
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.
```bash
npm install -g po2json
```
To convert all PO files to formatted JSON files you can use the `po2json.sh` script.
```bash
./scripts/po2json.sh
```
If you get errors running `po2json`, you might be running the Ubuntu package with the same
name, rather than the Node.js 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`).
If you get a lot of `[null,***]` in `messages.json`, just delete all the `null,`.
For example, `"year":["年"]` is correct while `"year":[null,"年"]`is incorrect.
For the translations to take effect we need to compile translation catalogs into binary MO files.
```bash
pybabel compile -d superset/translations
```
### 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](https://flask-appbuilder.readthedocs.io/en/latest/i18n.html) for more details):
```bash
pip install -r superset/translations/requirements.txt
pybabel init -i superset/translations/messages.pot -d superset/translations -l LANGUAGE_CODE
```
Then, [Updating language files](#updating-language-files).
## 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.
1. Create DB migration files for the new models
1. Specify this variable to add the datasource model and from which module it is from in config.py:
For example:
```python
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.
### Visualization Plugins
The topic of authoring new plugins, whether you'd like to contribute
it back or not has been well documented in the
[the documentation](https://superset.apache.org/docs/contributing/creating-viz-plugins), and in [this blog post](https://preset.io/blog/building-custom-viz-plugins-in-superset-v2).
To contribute a plugin to Superset, your plugin must meet the following criteria:
- The plugin should be applicable to the community at large, not a particularly specialized use case
- The plugin should be written with TypeScript
- The plugin should contain sufficient unit/e2e tests
- The plugin should use appropriate namespacing, e.g. a folder name of `plugin-chart-whatever` and a package name of `@superset-ui/plugin-chart-whatever`
- The plugin should use them variables via Emotion, as passed in by the ThemeProvider
- The plugin should provide adequate error handling (no data returned, malformed data, invalid controls, etc.)
- The plugin should contain documentation in the form of a populated `README.md` file
- The plugin should have a meaningful and unique icon
- Above all else, the plugin should come with a _commitment to maintenance_ from the original author(s)
Submissions will be considered for submission (or removal) on a case-by-case basis.
### Adding a DB migration
1. Alter the model you want to change. This example will add a `Column` Annotations model.
[Example commit](https://github.com/apache/superset/commit/6c25f549384d7c2fc288451222e50493a7b14104)
1. Generate the migration file
```bash
superset db migrate -m 'add_metadata_column_to_annotation_model'
```
This will generate a file in `migrations/version/{SHA}_this_will_be_in_the_migration_filename.py`.
[Example commit](https://github.com/apache/superset/commit/d3e83b0fd572c9d6c1297543d415a332858e262)
1. Upgrade the DB
```bash
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
```
1. Add column to view
Since there is a new column, we need to add it to the AppBuilder Model view.
[Example commit](https://github.com/apache/superset/pull/5745/commits/6220966e2a0a0cf3e6d87925491f8920fe8a3458)
1. Test the migration's `down` method
```bash
superset db downgrade
```
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 downgrade 40a0a483dd12 -> 1a1d627ebd8e, add_metadata_column_to_annotation_model.py
```
### Merging DB migrations
When two DB migrations collide, you'll get an error message like this one:
```text
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
```bash
superset db heads
```
This should list two or more migration hashes. E.g.
```bash
1412ec1e5a7b (head)
67da9ef1ef9c (head)
```
2. Pick one of them as the parent revision, open the script for the other revision
and update `Revises` and `down_revision` to the new parent revision. E.g.:
```diff
--- a/67da9ef1ef9c_add_hide_left_bar_to_tabstate.py
+++ b/67da9ef1ef9c_add_hide_left_bar_to_tabstate.py
@@ -17,14 +17,14 @@
"""add hide_left_bar to tabstate
Revision ID: 67da9ef1ef9c
-Revises: c501b7c653a3
+Revises: 1412ec1e5a7b
Create Date: 2021-02-22 11:22:10.156942
"""
# revision identifiers, used by Alembic.
revision = "67da9ef1ef9c"
-down_revision = "c501b7c653a3"
+down_revision = "1412ec1e5a7b"
import sqlalchemy as sa
from alembic import op
```
Alternatively you may also run `superset db merge` to create a migration script
just for merging the heads.
```bash
superset db merge {HASH1} {HASH2}
```
3. Upgrade the DB to the new checkpoint
```bash
superset db upgrade
```

View File

@ -0,0 +1,258 @@
---
title: Guidelines
sidebar_position: 2
version: 1
---
## Pull Request Guidelines
A philosophy we would like to strongly encourage is
> Before creating a PR, create an issue.
The purpose is to separate problem from possible solutions.
**Bug fixes:** If youre only fixing a small bug, its fine to submit a pull request right away but we highly recommend to file an issue detailing what youre fixing. This is helpful in case we dont accept that specific fix but want to keep track of the issue. Please keep in mind that the project maintainers reserve the rights to accept or reject incoming PRs, so it is better to separate the issue and the code to fix it from each other. In some cases, project maintainers may request you to create a separate issue from PR before proceeding.
**Refactor:** For small refactors, it can be a standalone PR itself detailing what you are refactoring and why. If there are concerns, project maintainers may request you to create a `#SIP` for the PR before proceeding.
**Feature/Large changes:** If you intend to change the public API, or make any non-trivial changes to the implementation, we require you to file a new issue as `#SIP` (Superset Improvement Proposal). This lets us reach an agreement on your proposal before you put significant effort into it. You are welcome to submit a PR along with the SIP (sometimes necessary for demonstration), but we will not review/merge the code until the SIP is approved.
In general, small PRs are always easier to review than large PRs. The best practice is to break your work into smaller independent PRs and refer to the same issue. This will greatly reduce turnaround time.
If you wish to share your work which is not ready to merge yet, create a [Draft PR](https://github.blog/2019-02-14-introducing-draft-pull-requests/). This will enable maintainers and the CI runner to prioritize mature PR's.
Finally, never submit a PR that will put master branch in broken state. If the PR is part of multiple PRs to complete a large feature and cannot work on its own, you can create a feature branch and merge all related PRs into the feature branch before creating a PR from feature branch to master.
### Protocol
#### Authoring
- Fill in all sections of the PR template.
- Title the PR with one of the following semantic prefixes (inspired by [Karma](http://karma-runner.github.io/0.10/dev/git-commit-msg.html])):
- `feat` (new feature)
- `fix` (bug fix)
- `docs` (changes to the documentation)
- `style` (formatting, missing semi colons, etc; no application logic change)
- `refactor` (refactoring code)
- `test` (adding missing tests, refactoring tests; no application logic change)
- `chore` (updating tasks etc; no application logic change)
- `perf` (performance-related change)
- `build` (build tooling, Docker configuration change)
- `ci` (test runner, GitHub Actions workflow changes)
- `other` (changes that don't correspond to the above -- should be rare!)
- Examples:
- `feat: export charts as ZIP files`
- `perf(api): improve API info performance`
- `fix(chart-api): cached-indicator always shows value is cached`
- Add prefix `[WIP]` to title if not ready for review (WIP = work-in-progress). We recommend creating a PR with `[WIP]` first and remove it once you have passed CI test and read through your code changes at least once.
- If you believe your PR contributes a potentially breaking change, put a `!` after the semantic prefix but before the colon in the PR title, like so: `feat!: Added foo functionality to bar`
- **Screenshots/GIFs:** Changes to user interface require before/after screenshots, or GIF for interactions
- Recommended capture tools ([Kap](https://getkap.co/), [LICEcap](https://www.cockos.com/licecap/), [Skitch](https://download.cnet.com/Skitch/3000-13455_4-189876.html))
- If no screenshot is provided, the committers will mark the PR with `need:screenshot` label and will not review until screenshot is provided.
- **Dependencies:** Be careful about adding new dependency and avoid unnecessary dependencies.
- For Python, include it in `pyproject.toml` denoting any specific restrictions and
in `requirements.txt` pinned to a specific version which ensures that the application
build is deterministic.
- For TypeScript/JavaScript, include new libraries in `package.json`
- **Tests:** The pull request should include tests, either as doctests, unit tests, or both. Make sure to resolve all errors and test failures. See [Testing](#testing) for how to run tests.
- **Documentation:** If the pull request adds functionality, the docs should be updated as part of the same PR.
- **CI:** Reviewers will not review the code until all CI tests are passed. Sometimes there can be flaky tests. You can close and open PR to re-run CI test. Please report if the issue persists. After the CI fix has been deployed to `master`, please rebase your PR.
- **Code coverage:** Please ensure that code coverage does not decrease.
- Remove `[WIP]` when ready for review. Please note that it may be merged soon after approved so please make sure the PR is ready to merge and do not expect more time for post-approval edits.
- If the PR was not ready for review and inactive for > 30 days, we will close it due to inactivity. The author is welcome to re-open and update.
#### Reviewing
- Use constructive tone when writing reviews.
- If there are changes required, state clearly what needs to be done before the PR can be approved.
- 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.
- The committers reserve the right to reject any PR and in some cases may request the author to file an issue.
#### Test Environments
- Members of the Apache GitHub org can launch an ephemeral test environment directly on a pull request by creating a comment containing (only) the command `/testenv up`.
- Note that org membership must be public in order for this validation to function properly.
- Feature flags may be set for a test environment by specifying the flag name (prefixed with `FEATURE_`) and value after the command.
- Format: `/testenv up FEATURE_<feature flag name>=true|false`
- Example: `/testenv up FEATURE_DASHBOARD_NATIVE_FILTERS=true`
- Multiple feature flags may be set in single command, separated by whitespace
- A comment will be created by the workflow script with the address and login information for the ephemeral environment.
- Test environments may be created once the Docker build CI workflow for the PR has completed successfully.
- Test environments do not currently update automatically when new commits are added to a pull request.
- Test environments do not currently support async workers, though this is planned.
- Running test environments will be shutdown upon closing the pull request.
#### Merging
- At least one approval is required for merging a PR.
- PR is usually left open for at least 24 hours before merging.
- After the PR is merged, [close the corresponding issue(s)](https://help.github.com/articles/closing-issues-using-keywords/).
#### Post-merge Responsibility
- Project maintainers may contact the PR author if new issues are introduced by the PR.
- Project maintainers may revert your changes if a critical issue is found, such as breaking master branch CI.
## Managing Issues and PRs
To handle issues and PRs that are coming in, committers read issues/PRs and flag them with labels to categorize and help contributors spot where to take actions, as contributors usually have different expertises.
Triaging goals
- **For issues:** Categorize, screen issues, flag required actions from authors.
- **For PRs:** Categorize, flag required actions from authors. If PR is ready for review, flag required actions from reviewers.
First, add **Category labels (a.k.a. hash labels)**. Every issue/PR must have one hash label (except spam entry). Labels that begin with `#` defines issue/PR type:
| Label | for Issue | for PR |
| --------------- | ----------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------- |
| `#bug` | Bug report | Bug fix |
| `#code-quality` | Describe problem with code, architecture or productivity | Refactor, tests, tooling |
| `#feature` | New feature request | New feature implementation |
| `#refine` | Propose improvement such as adjusting padding or refining UI style, excluding new features, bug fixes, and refactoring. | Implementation of improvement such as adjusting padding or refining UI style, excluding new features, bug fixes, and refactoring. |
| `#doc` | Documentation | Documentation |
| `#question` | Troubleshooting: Installation, Running locally, Ask how to do something. Can be changed to `#bug` later. | N/A |
| `#SIP` | Superset Improvement Proposal | N/A |
| `#ASF` | Tasks related to Apache Software Foundation policy | Tasks related to Apache Software Foundation policy |
Then add other types of labels as appropriate.
- **Descriptive labels (a.k.a. dot labels):** These labels that begin with `.` describe the details of the issue/PR, such as `.ui`, `.js`, `.install`, `.backend`, etc. Each issue/PR can have zero or more dot labels.
- **Need labels:** These labels have pattern `need:xxx`, which describe the work required to progress, such as `need:rebase`, `need:update`, `need:screenshot`.
- **Risk labels:** These labels have pattern `risk:xxx`, which describe the potential risk on adopting the work, such as `risk:db-migration`. The intention was to better understand the impact and create awareness for PRs that need more rigorous testing.
- **Status labels:** These labels describe the status (`abandoned`, `wontfix`, `cant-reproduce`, etc.) Issue/PRs that are rejected or closed without completion should have one or more status labels.
- **Version labels:** These have the pattern `vx.x` such as `v0.28`. Version labels on issues describe the version the bug was reported on. Version labels on PR describe the first release that will include the PR.
Committers may also update title to reflect the issue/PR content if the author-provided title is not descriptive enough.
If the PR passes CI tests and does not have any `need:` labels, it is ready for review, add label `review` and/or `design-review`.
If an issue/PR has been inactive for >=30 days, it will be closed. If it does not have any status label, add `inactive`.
When creating a PR, if you're aiming to have it included in a specific release, please tag it with the version label. For example, to have a PR considered for inclusion in Superset 1.1 use the label `v1.1`.
## Revert Guidelines
Reverting changes that are causing issues in the master branch is a normal and expected part of the development process. In an open source community, the ramifications of a change cannot always be fully understood. With that in mind, here are some considerations to keep in mind when considering a revert:
- **Availability of the PR author:** If the original PR author or the engineer who merged the code is highly available and can provide a fix in a reasonable time frame, this would counter-indicate reverting.
- **Severity of the issue:** How severe is the problem on master? Is it keeping the project from moving forward? Is there user impact? What percentage of users will experience a problem?
- **Size of the change being reverted:** Reverting a single small PR is a much lower-risk proposition than reverting a massive, multi-PR change.
- **Age of the change being reverted:** Reverting a recently-merged PR will be more acceptable than reverting an older PR. A bug discovered in an older PR is unlikely to be causing widespread serious issues.
- **Risk inherent in reverting:** Will the reversion break critical functionality? Is the medicine more dangerous than the disease?
- **Difficulty of crafting a fix:** In the case of issues with a clear solution, it may be preferable to implement and merge a fix rather than a revert.
Should you decide that reverting is desirable, it is the responsibility of the Contributor performing the revert to:
- **Contact the interested parties:** The PR's author and the engineer who merged the work should both be contacted and informed of the revert.
- **Provide concise reproduction steps:** Ensure that the issue can be clearly understood and duplicated by the original author of the PR.
- **Put the revert through code review:** The revert must be approved by another committer.
## Design Guidelines
### Capitalization guidelines
#### Sentence case
Use sentence-case capitalization for everything in the UI (except these \*\*).
Sentence case is predominantly lowercase. Capitalize only the initial character of the first word, and other words that require capitalization, like:
- **Proper nouns.** Objects in the product _are not_ considered proper nouns e.g. dashboards, charts, saved queries etc. Proprietary feature names eg. SQL Lab, Preset Manager _are_ considered proper nouns
- **Acronyms** (e.g. CSS, HTML)
- When referring to **UI labels that are themselves capitalized** from sentence case (e.g. page titles - Dashboards page, Charts page, Saved queries page, etc.)
- User input that is reflected in the UI. E.g. a user-named a dashboard tab
**Sentence case vs. Title case:**
Title case: "A Dog Takes a Walk in Paris"
Sentence case: "A dog takes a walk in Paris"
**Why sentence case?**
- Its generally accepted as the quickest to read
- Its the easiest form to distinguish between common and proper nouns
#### How to refer to UI elements
When writing about a UI element, use the same capitalization as used in the UI.
For example, if an input field is labeled “Name” then you refer to this as the “Name input field”. Similarly, if a button has the label “Save” in it, then it is correct to refer to the “Save button”.
Where a product page is titled “Settings”, you refer to this in writing as follows:
“Edit your personal information on the Settings page”.
Often a product page will have the same title as the objects it contains. In this case, refer to the page as it appears in the UI, and the objects as common nouns:
- Upload a dashboard on the Dashboards page
- Go to Dashboards
- View dashboard
- View all dashboards
- Upload CSS templates on the CSS templates page
- Queries that you save will appear on the Saved queries page
- Create custom queries in SQL Lab then create dashboards
#### \*\*Exceptions to sentence case:
- Input labels, buttons and UI tabs are all caps
- User input values (e.g. column names, SQL Lab tab names) should be in their original case
## Programming Language Conventions
### Python
Parameters in the `config.py` (which are accessible via the Flask app.config dictionary) are
assumed to always be defined and thus should be accessed directly via,
```python
blueprints = app.config["BLUEPRINTS"]
```
rather than,
```python
blueprints = app.config.get("BLUEPRINTS")
```
or similar as the later will cause typing issues. The former is of type `List[Callable]`
whereas the later is of type `Optional[List[Callable]]`.
#### Typing / Types Hints
To ensure clarity, consistency, all readability, _all_ new functions should use
[type hints](https://docs.python.org/3/library/typing.html) and include a
docstring.
Note per [PEP-484](https://www.python.org/dev/peps/pep-0484/#exceptions) no
syntax for listing explicitly raised exceptions is proposed and thus the
recommendation is to put this information in a docstring, i.e.,
```python
import math
from typing import Union
def sqrt(x: Union[float, int]) -> Union[float, int]:
"""
Return the square root of x.
:param x: A number
:returns: The square root of the given number
:raises ValueError: If the number is negative
"""
return math.sqrt(x)
```
### TypeScript
TypeScript is fully supported and is the recommended language for writing all new frontend
components. When modifying existing functions/components, migrating to TypeScript is
appreciated, but not required. Examples of migrating functions/components to TypeScript can be
found in [#9162](https://github.com/apache/superset/pull/9162) and [#9180](https://github.com/apache/superset/pull/9180).

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title: Pre-commit Hooks and Linting
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## Git Hooks
Superset uses Git pre-commit hooks courtesy of [pre-commit](https://pre-commit.com/). To install run the following:
```bash
pip3 install -r requirements/development.txt
pre-commit install
```
A series of checks will now run when you make a git commit.
Alternatively it is possible to run pre-commit via tox:
```bash
tox -e pre-commit
```
Or by running pre-commit manually:
```bash
pre-commit run --all-files
```
## Linting
### Python
We use [Pylint](https://pylint.org/) for linting which can be invoked via:
```bash
# for python
tox -e pylint
```
In terms of best practices please avoid blanket disabling of Pylint messages globally (via `.pylintrc`) or top-level within the file header, albeit there being a few exceptions. Disabling should occur inline as it prevents masking issues and provides context as to why said message is disabled.
Additionally, the Python code is auto-formatted using [Black](https://github.com/python/black) which
is configured as a pre-commit hook. There are also numerous [editor integrations](https://black.readthedocs.io/en/stable/integrations/editors.html)
### TypeScript
```bash
cd superset-frontend
npm ci
# run eslint checks
npm run eslint -- .
# run tsc (typescript) checks
npm run type
```
If using the eslint extension with vscode, put the following in your workspace `settings.json` file:
```json
"eslint.workingDirectories": [
"superset-frontend"
]
```

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title: Development How-tos
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# Development How-tos
## Contributing to Documentation
The latest documentation and tutorial are available at https://superset.apache.org/.
The documentation site is built using [Docusaurus 2](https://docusaurus.io/), a modern
static website generator, the source for which resides in `./docs`.
### Local Development
To set up a local development environment with hot reloading for the documentation site:
```shell
cd docs
yarn install # Installs NPM dependencies
yarn start # Starts development server at http://localhost:3000
```
### Build
To create and serve a production build of the documentation site:
```shell
yarn build
yarn serve
```
### Deployment
Commits to `master` trigger a rebuild and redeploy of the documentation site. Submit pull requests that modify the documentation with the `docs:` prefix.
## Creating Visualization Plugins
Visualizations in Superset are implemented in JavaScript or TypeScript. Superset
comes preinstalled with several visualizations types (hereafter "viz plugins") that
can be found under the `superset-frontend/plugins` directory. Viz plugins are added to
the application in the `superset-frontend/src/visualizations/presets/MainPreset.js`.
The Superset project is always happy to review proposals for new high quality viz
plugins. However, for highly custom viz types it is recommended to maintain a fork
of Superset, and add the custom built viz plugins by hand.
**Note:** Additional community-generated resources about creating and deploying custom visualization plugins can be found on the [Superset Wiki](https://github.com/apache/superset/wiki/Community-Resource-Library#creating-custom-data-visualizations)
### Prerequisites
In order to create a new viz plugin, you need the following:
- Run MacOS or Linux (Windows is not officially supported, but may work)
- Node.js 16
- npm 7 or 8
A general familiarity with [React](https://reactjs.org/) and the npm/Node system is
also recommended.
### Creating a simple Hello World viz plugin
To get started, you need the Superset Yeoman Generator. It is recommended to use the
version of the template that ships with the version of Superset you are using. This
can be installed by doing the following:
```bash
npm i -g yo
cd superset-frontend/packages/generator-superset
npm i
npm link
```
After this you can proceed to create your viz plugin. Create a new directory for your
viz plugin with the prefix `superset-plugin-chart` and run the Yeoman generator:
```bash
mkdir /tmp/superset-plugin-chart-hello-world
cd /tmp/superset-plugin-chart-hello-world
```
Initialize the viz plugin:
```bash
yo @superset-ui/superset
```
After that the generator will ask a few questions (the defaults should be fine):
```
$ yo @superset-ui/superset
_-----_ ╭──────────────────────────╮
| | │ Welcome to the │
|--(o)--| │ generator-superset │
`---------´ │ generator! │
( _´U`_ ) ╰──────────────────────────╯
/___A___\ /
| ~ |
__'.___.'__
´ ` |° ´ Y `
? Package name: superset-plugin-chart-hello-world
? Description: Hello World
? What type of chart would you like? Time-series chart
create package.json
create .gitignore
create babel.config.js
create jest.config.js
create README.md
create tsconfig.json
create src/index.ts
create src/plugin/buildQuery.ts
create src/plugin/controlPanel.ts
create src/plugin/index.ts
create src/plugin/transformProps.ts
create src/types.ts
create src/SupersetPluginChartHelloWorld.tsx
create test/index.test.ts
create test/__mocks__/mockExportString.js
create test/plugin/buildQuery.test.ts
create test/plugin/transformProps.test.ts
create types/external.d.ts
create src/images/thumbnail.png
```
To build the viz plugin, run the following commands:
```
npm i --force
npm run build
```
Alternatively, to run the viz plugin in development mode (=rebuilding whenever changes
are made), start the dev server with the following command:
```
npm run dev
```
To add the package to Superset, go to the `superset-frontend` subdirectory in your
Superset source folder run
```bash
npm i -S /tmp/superset-plugin-chart-hello-world
```
If you publish your package to npm, you can naturally install directly from there, too.
After this edit the `superset-frontend/src/visualizations/presets/MainPreset.js`
and make the following changes:
```js
import { SupersetPluginChartHelloWorld } from 'superset-plugin-chart-hello-world';
```
to import the viz plugin and later add the following to the array that's passed to the
`plugins` property:
```js
new SupersetPluginChartHelloWorld().configure({ key: 'ext-hello-world' }),
```
After that the viz plugin should show up when you run Superset, e.g. the development
server:
```bash
npm run dev-server
```
## Testing
### Python Testing
All python tests are carried out in [tox](https://tox.readthedocs.io/en/latest/index.html)
a standardized testing framework.
All python tests can be run with any of the tox [environments](https://tox.readthedocs.io/en/latest/example/basic.html#a-simple-tox-ini-default-environments), via,
```bash
tox -e <environment>
```
For example,
```bash
tox -e py38
```
Alternatively, you can run all tests in a single file via,
```bash
tox -e <environment> -- tests/test_file.py
```
or for a specific test via,
```bash
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.
There is also a utility script included in the Superset codebase to run python integration tests. The [readme can be
found here](https://github.com/apache/superset/tree/master/scripts/tests)
To run all integration tests for example, run this script from the root directory:
```bash
scripts/tests/run.sh
```
You can run unit tests found in './tests/unit_tests' for example with pytest. It is a simple way to run an isolated test that doesn't need any database setup
```bash
pytest ./link_to_test.py
```
#### Testing with local Presto connections
If you happen to change db engine spec for Presto/Trino, you can run a local Presto cluster with Docker:
```bash
docker run -p 15433:15433 starburstdata/presto:350-e.6
```
Then update `SUPERSET__SQLALCHEMY_EXAMPLES_URI` to point to local Presto cluster:
```bash
export SUPERSET__SQLALCHEMY_EXAMPLES_URI=presto://localhost:15433/memory/default
```
### Frontend Testing
We use [Jest](https://jestjs.io/) and [Enzyme](https://airbnb.io/enzyme/) to test TypeScript/JavaScript. Tests can be run with:
```bash
cd superset-frontend
npm run test
```
To run a single test file:
```bash
npm run test -- path/to/file.js
```
### e2e Integration Testing
We use [Cypress](https://www.cypress.io/) for end-to-end integration
tests. One easy option to get started quickly is to leverage `tox` to
run the whole suite in an isolated environment.
```bash
tox -e cypress
```
Alternatively, you can go lower level and set things up in your
development environment by following these steps:
First set up a python/flask backend:
```bash
export SUPERSET_CONFIG=tests.integration_tests.superset_test_config
export SUPERSET_TESTENV=true
export CYPRESS_BASE_URL="http://localhost:8081"
superset db upgrade
superset load_test_users
superset init
superset load-examples --load-test-data
superset run --port 8081
```
In another terminal, prepare the frontend and run Cypress tests:
```bash
cd superset-frontend
npm run build-instrumented
cd cypress-base
npm install
# run tests via headless Chrome browser (requires Chrome 64+)
npm run cypress-run-chrome
# run tests from a specific file
npm run cypress-run-chrome -- --spec cypress/e2e/explore/link.test.ts
# run specific file with video capture
npm run cypress-run-chrome -- --spec cypress/e2e/dashboard/index.test.js --config video=true
# to open the cypress ui
npm run cypress-debug
# to point cypress to a url other than the default (http://localhost:8088) set the environment variable before running the script
# e.g., CYPRESS_BASE_URL="http://localhost:9000"
CYPRESS_BASE_URL=<your url> npm run cypress open
```
See [`superset-frontend/cypress_build.sh`](https://github.com/apache/superset/blob/master/superset-frontend/cypress_build.sh).
As an alternative you can use docker compose environment for testing:
Make sure you have added below line to your /etc/hosts file:
`127.0.0.1 db`
If you already have launched Docker environment please use the following command to assure a fresh database instance:
`docker compose down -v`
Launch environment:
`CYPRESS_CONFIG=true docker compose up`
It will serve backend and frontend on port 8088.
Run Cypress tests:
```bash
cd cypress-base
npm install
npm run cypress open
```
### Debugging Server App
Follow these instructions to debug the Flask app running inside a docker container.
First add the following to the ./docker-compose.yaml file
```diff
superset:
env_file: docker/.env
image: *superset-image
container_name: superset_app
command: ["/app/docker/docker-bootstrap.sh", "app"]
restart: unless-stopped
+ cap_add:
+ - SYS_PTRACE
ports:
- 8088:8088
+ - 5678:5678
user: "root"
depends_on: *superset-depends-on
volumes: *superset-volumes
environment:
CYPRESS_CONFIG: "${CYPRESS_CONFIG}"
```
Start Superset as usual
```bash
docker compose up
```
Install the required libraries and packages to the docker container
Enter the superset_app container
```bash
docker exec -it superset_app /bin/bash
root@39ce8cf9d6ab:/app#
```
Run the following commands inside the container
```bash
apt update
apt install -y gdb
apt install -y net-tools
pip install debugpy
```
Find the PID for the Flask process. Make sure to use the first PID. The Flask app will re-spawn a sub-process every time you change any of the python code. So it's important to use the first PID.
```bash
ps -ef
UID PID PPID C STIME TTY TIME CMD
root 1 0 0 14:09 ? 00:00:00 bash /app/docker/docker-bootstrap.sh app
root 6 1 4 14:09 ? 00:00:04 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
root 10 6 7 14:09 ? 00:00:07 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
```
Inject debugpy into the running Flask process. In this case PID 6.
```bash
python3 -m debugpy --listen 0.0.0.0:5678 --pid 6
```
Verify that debugpy is listening on port 5678
```bash
netstat -tunap
Active Internet connections (servers and established)
Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name
tcp 0 0 0.0.0.0:5678 0.0.0.0:* LISTEN 462/python
tcp 0 0 0.0.0.0:8088 0.0.0.0:* LISTEN 6/python
```
You are now ready to attach a debugger to the process. Using VSCode you can configure a launch configuration file .vscode/launch.json like so.
```
{
"version": "0.2.0",
"configurations": [
{
"name": "Attach to Superset App in Docker Container",
"type": "python",
"request": "attach",
"connect": {
"host": "127.0.0.1",
"port": 5678
},
"pathMappings": [
{
"localRoot": "${workspaceFolder}",
"remoteRoot": "/app"
}
]
},
]
}
```
VSCode will not stop on breakpoints right away. We've attached to PID 6 however it does not yet know of any sub-processes. In order to "wakeup" the debugger you need to modify a python file. This will trigger Flask to reload the code and create a new sub-process. This new sub-process will be detected by VSCode and breakpoints will be activated.
### Debugging Server App in Kubernetes Environment
To debug Flask running in POD inside kubernetes cluster. You'll need to make sure the pod runs as root and is granted the SYS_TRACE capability.These settings should not be used in production environments.
```
securityContext:
capabilities:
add: ["SYS_PTRACE"]
```
See (set capabilities for a container)[https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#set-capabilities-for-a-container] for more details.
Once the pod is running as root and has the SYS_PTRACE capability it will be able to debug the Flask app.
You can follow the same instructions as in the docker-compose. Enter the pod and install the required library and packages; gdb, netstat and debugpy.
Often in a Kubernetes environment nodes are not addressable from outside the cluster. VSCode will thus be unable to remotely connect to port 5678 on a Kubernetes node. In order to do this you need to create a tunnel that port forwards 5678 to your local machine.
```
kubectl port-forward pod/superset-<some random id> 5678:5678
```
You can now launch your VSCode debugger with the same config as above. VSCode will connect to to 127.0.0.1:5678 which is forwarded by kubectl to your remote kubernetes POD.
### Storybook
Superset includes a [Storybook](https://storybook.js.org/) to preview the layout/styling of various Superset components, and variations thereof. To open and view the Storybook:
```bash
cd superset-frontend
npm run storybook
```
When contributing new React components to Superset, please try to add a Story alongside the component's `jsx/tsx` file.
## Contribute Translations
We use [Flask-Babel](https://python-babel.github.io/flask-babel/) to translate Superset.
In Python files, we use the following
[translation functions](https://python-babel.github.io/flask-babel/#using-translations)
from `Flask-Babel`:
- `gettext` and `lazy_gettext` (usually aliased to `_`): for translating singular
strings.
- `ngettext`: for translating strings that might become plural.
```python
from flask_babel import lazy_gettext as _
```
then wrap the 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 TypeScript/JavaScript, the technique is similar:
we import `t` (simple translation), `tn` (translation containing a number).
```javascript
import { t, tn } from "@superset-ui/translation";
```
### 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.
```python
LANGUAGES = {
'en': {'flag': 'us', 'name': 'English'},
'fr': {'flag': 'fr', 'name': 'French'},
'zh': {'flag': 'cn', 'name': 'Chinese'},
}
```
### Creating a new language dictionary
First check if the language code for your target language already exists. Check if the
[two letter ISO 639-1 code](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes)
for your target language already exists in the `superset/translations` directory:
```bash
ls superset/translations | grep -E "^[a-z]{2}\/"
```
If your language already has a preexisting translation, skip to the next section
The following languages are already supported by Flask AppBuilder, and will make it
easier to translate the application to your target language:
[Flask AppBuilder i18n documentation](https://flask-appbuilder.readthedocs.io/en/latest/i18n.html)
To create a dictionary for a new language, first make sure the necessary dependencies are installed:
```bash
pip install -r superset/translations/requirements.txt
```
Then run the following, where `LANGUAGE_CODE` is replaced with the language code for your target
language:
```bash
pybabel init -i superset/translations/messages.pot -d superset/translations -l LANGUAGE_CODE
```
For instance, to add a translation for Finnish (language code `fi`), run the following:
```bash
pybabel init -i superset/translations/messages.pot -d superset/translations -l fi
```
### Extracting new strings for translation
This step needs to be done every time application strings change. This happens fairly
frequently, so if you want to ensure that your translation has good coverage, this
step needs to be run fairly frequently and the updated strings merged to the upstream
codebase via PRs. To update the template file `superset/translations/messages.pot`
with current application strings, run the following command:
```bash
pybabel extract -F superset/translations/babel.cfg -o superset/translations/messages.pot -k _ -k __ -k t -k tn -k tct .
```
Do not forget to update this file with the appropriate license information.
### Updating language files
Run the following command to update the language files with the new extracted strings.
```bash
pybabel update -i superset/translations/messages.pot -d superset/translations --ignore-obsolete
```
You can then translate the strings gathered in files located under
`superset/translation`, where there's one folder per language. You can use [Poedit](https://poedit.net/features)
to translate the `po` file more conveniently.
Here is [a tutorial](https://web.archive.org/web/20220517065036/https://wiki.lxde.org/en/Translate_*.po_files_with_Poedit).
To perform the translation on MacOS, you can install `poedit` via Homebrew:
```bash
brew install poedit
```
After this, just start the `poedit` application and open the `messages.po` file. In the
case of the Finnish translation, this would be `superset/translations/fi/LC_MESSAGES/messages.po`.
### Applying translations
To make the translations available on the frontend, we need to convert the PO file into
a JSON file. To do this, we need to globally install the npm package `po2json`.
```bash
npm install -g po2json
```
To convert all PO files to formatted JSON files you can use the `po2json.sh` script.
```bash
./scripts/po2json.sh
```
If you get errors running `po2json`, you might be running the Ubuntu package with the same
name, rather than the Node.js 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`).
If you get a lot of `[null,***]` in `messages.json`, just delete all the `null,`.
For example, `"year":["年"]` is correct while `"year":[null,"年"]`is incorrect.
Finally, for the translations to take effect we need to compile translation catalogs into
binary MO files.
```bash
pybabel compile -d superset/translations
```
## Linting
### Python
We use [Pylint](https://pylint.org/) for linting which can be invoked via:
```bash
# for python
tox -e pylint
```
In terms of best practices please avoid blanket disabling of Pylint messages globally (via `.pylintrc`) or top-level within the file header, albeit there being a few exceptions. Disabling should occur inline as it prevents masking issues and provides context as to why said message is disabled.
Additionally, the Python code is auto-formatted using [Black](https://github.com/python/black) which
is configured as a pre-commit hook. There are also numerous [editor integrations](https://black.readthedocs.io/en/stable/integrations/editors.html)
### TypeScript
```bash
cd superset-frontend
npm ci
# run eslint checks
npm run eslint -- .
# run tsc (typescript) checks
npm run type
```
If using the eslint extension with vscode, put the following in your workspace `settings.json` file:
```json
"eslint.workingDirectories": [
"superset-frontend"
]
```

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@ -1,112 +0,0 @@
---
title: Running a Local Flask Backend
hide_title: true
sidebar_position: 5
version: 1
---
### Flask server
#### OS Dependencies
Make sure your machine meets the [OS dependencies](/docs/installation/pypi#os-dependencies) before following these steps.
You also need to install MySQL or [MariaDB](https://mariadb.com/downloads).
Ensure that you are using Python version 3.10 or 3.11, then proceed with:
```bash
# Create a virtual environment and activate it (recommended)
python3 -m venv venv # setup a python3 virtualenv
source venv/bin/activate
# Install external dependencies
pip install -r requirements/development.txt
# Install Superset in editable (development) mode
pip install -e .
# Initialize the database
# Note: For generating a SECRET_KEY if you haven't done already, you can use the command:
# echo "SECRET_KEY='$(openssl rand -base64 42)'" | tee -a superset_config.py
superset db upgrade
# Create an admin user in your metadata database (use `admin` as username to be able to load the examples)
superset fab create-admin
# Create default roles and permissions
superset init
# Load some data to play with.
# Note: you MUST have previously created an admin user with the username `admin` for this command to work.
superset load-examples
# Start the Flask dev web server from inside your virtualenv.
# Note that your page may not have CSS at this point.
superset run -p 8088 --with-threads --reload --debugger --debug
```
Or you can install via our Makefile
```bash
# Create a virtual environment and activate it (recommended)
python3 -m venv venv # setup a python3 virtualenv
source venv/bin/activate
# install pip packages + pre-commit
make install
# Install superset pip packages and setup env only
make superset
# Setup pre-commit only
make pre-commit
```
**Note: the FLASK_APP env var should not need to be set, as it's currently controlled
via `.flaskenv`, however if needed, it should be set to `superset.app:create_app()`**
If you have made changes to the FAB-managed templates, which are not built the same way as the newer, React-powered front-end assets, you need to start the app without the `--with-threads` argument like so:
`superset run -p 8088 --reload --debugger --debug`
#### Dependencies
If you add a new requirement or update an existing requirement (per the
`requirements` section in `pyproject.toml`) you must recompile (freeze) the
Python dependencies to ensure that for CI, testing, etc. the build is deterministic.
This can be achieved via,
```bash
$ python3 -m venv venv
$ source venv/bin/activate
$ python3 -m pip install -r requirements/development.txt
$ pip-compile-multi --no-upgrade
```
#### 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 using the [ConsoleLog](https://github.com/betodealmeida/consolelog) package. You need to mutate the app, by adding the following to your `config.py` or `superset_config.py`:
```python
from console_log import ConsoleLog
def FLASK_APP_MUTATOR(app):
app.wsgi_app = ConsoleLog(app.wsgi_app, app.logger)
```
Then make sure you run your WSGI server using the right worker type:
```bash
SUPERSET_ENV=development gunicorn "superset.app:create_app()" -k "geventwebsocket.gunicorn.workers.GeventWebSocketWorker" -b 127.0.0.1:8088 --reload
```
You can log anything to the browser console, including objects:
```python
from superset import app
app.logger.error('An exception occurred!')
app.logger.info(form_data)
```
### Frontend Assets
See [Building Frontend Assets Locally](https://github.com/apache/superset/blob/master/CONTRIBUTING.md#frontend)

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---
sidebar_position: 6
version: 1
---
# Misc.
## Reporting a Security Vulnerability
Please report security vulnerabilities to private@superset.apache.org.
In the event a community member discovers a security flaw in Superset, it is important to follow the [Apache Security Guidelines](https://www.apache.org/security/committers.html) and release a fix as quickly as possible before public disclosure. Reporting security vulnerabilities through the usual GitHub Issues channel is not ideal as it will publicize the flaw before a fix can be applied.
### SQL Lab Async
It's possible to configure a local database to operate in `async` mode,
to work on `async` related features.
To do this, you'll need to:
- Add an additional database entry. We recommend you copy the connection
string from the database labeled `main`, and then enable `SQL Lab` and the
features you want to use. Don't forget to check the `Async` box
- Configure a results backend, here's a local `FileSystemCache` example,
not recommended for production,
but perfect for testing (stores cache in `/tmp`)
```python
from flask_caching.backends.filesystemcache import FileSystemCache
RESULTS_BACKEND = FileSystemCache('/tmp/sqllab')
```
- Start up a celery worker
```shell script
celery --app=superset.tasks.celery_app:app worker -O fair
```
Note that:
- for changes that affect the worker logic, you'll have to
restart the `celery worker` process for the changes to be reflected.
- The message queue used is a `sqlite` database using the `SQLAlchemy`
experimental broker. Ok for testing, but not recommended in production
- In some cases, you may want to create a context that is more aligned
to your production environment, and use the similar broker as well as
results backend configuration
### Async Chart Queries
It's possible to configure database queries for charts to operate in `async` mode. This is especially useful for dashboards with many charts that may otherwise be affected by browser connection limits. To enable async queries for dashboards and Explore, the following dependencies are required:
- Redis 5.0+ (the feature utilizes [Redis Streams](https://redis.io/topics/streams-intro))
- Cache backends enabled via the `CACHE_CONFIG` and `DATA_CACHE_CONFIG` config settings
- Celery workers configured and running to process async tasks

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---
title: Pull Request Guidelines
hide_title: true
sidebar_position: 3
version: 1
---
## Pull Request Guidelines
A philosophy we would like to strongly encourage is
> Before creating a PR, create an issue.
The purpose is to separate problem from possible solutions.
**Bug fixes:** If youre only fixing a small bug, its fine to submit a pull request right away but we highly recommend to file an issue detailing what youre fixing. This is helpful in case we dont accept that specific fix but want to keep track of the issue. Please keep in mind that the project maintainers reserve the rights to accept or reject incoming PRs, so it is better to separate the issue and the code to fix it from each other. In some cases, project maintainers may request you to create a separate issue from PR before proceeding.
**Refactor:** For small refactors, it can be a standalone PR itself detailing what you are refactoring and why. If there are concerns, project maintainers may request you to create a `#SIP` for the PR before proceeding.
**Feature/Large changes:** If you intend to change the public API, or make any non-trivial changes to the implementation, we require you to file a new issue as `#SIP` (Superset Improvement Proposal). This lets us reach an agreement on your proposal before you put significant effort into it. You are welcome to submit a PR along with the SIP (sometimes necessary for demonstration), but we will not review/merge the code until the SIP is approved.
In general, small PRs are always easier to review than large PRs. The best practice is to break your work into smaller independent PRs and refer to the same issue. This will greatly reduce turnaround time.
If you wish to share your work which is not ready to merge yet, create a [Draft PR](https://github.blog/2019-02-14-introducing-draft-pull-requests/). This will enable maintainers and the CI runner to prioritize mature PR's.
Finally, never submit a PR that will put master branch in broken state. If the PR is part of multiple PRs to complete a large feature and cannot work on its own, you can create a feature branch and merge all related PRs into the feature branch before creating a PR from feature branch to master.
### Protocol
#### Authoring
- Fill in all sections of the PR template.
- Title the PR with one of the following semantic prefixes (inspired by [Karma](http://karma-runner.github.io/0.10/dev/git-commit-msg.html])):
- `feat` (new feature)
- `fix` (bug fix)
- `docs` (changes to the documentation)
- `style` (formatting, missing semi colons, etc; no application logic change)
- `refactor` (refactoring code)
- `test` (adding missing tests, refactoring tests; no application logic change)
- `chore` (updating tasks etc; no application logic change)
- `perf` (performance-related change)
- `build` (build tooling, Docker configuration change)
- `ci` (test runner, GitHub Actions workflow changes)
- `other` (changes that don't correspond to the above -- should be rare!)
- Examples:
- `feat: export charts as ZIP files`
- `perf(api): improve API info performance`
- `fix(chart-api): cached-indicator always shows value is cached`
- Add prefix `[WIP]` to title if not ready for review (WIP = work-in-progress). We recommend creating a PR with `[WIP]` first and remove it once you have passed CI test and read through your code changes at least once.
- If you believe your PR contributes a potentially breaking change, put a `!` after the semantic prefix but before the colon in the PR title, like so: `feat!: Added foo functionality to bar`
- **Screenshots/GIFs:** Changes to user interface require before/after screenshots, or GIF for interactions
- Recommended capture tools ([Kap](https://getkap.co/), [LICEcap](https://www.cockos.com/licecap/), [Skitch](https://download.cnet.com/Skitch/3000-13455_4-189876.html))
- If no screenshot is provided, the committers will mark the PR with `need:screenshot` label and will not review until screenshot is provided.
- **Dependencies:** Be careful about adding new dependency and avoid unnecessary dependencies.
- For Python, include it in `pyproject.toml` denoting any specific restrictions and
in `requirements.txt` pinned to a specific version which ensures that the application
build is deterministic.
- For TypeScript/JavaScript, include new libraries in `package.json`
- **Tests:** The pull request should include tests, either as doctests, unit tests, or both. Make sure to resolve all errors and test failures. See [Testing](#testing) for how to run tests.
- **Documentation:** If the pull request adds functionality, the docs should be updated as part of the same PR.
- **CI:** Reviewers will not review the code until all CI tests are passed. Sometimes there can be flaky tests. You can close and open PR to re-run CI test. Please report if the issue persists. After the CI fix has been deployed to `master`, please rebase your PR.
- **Code coverage:** Please ensure that code coverage does not decrease.
- Remove `[WIP]` when ready for review. Please note that it may be merged soon after approved so please make sure the PR is ready to merge and do not expect more time for post-approval edits.
- If the PR was not ready for review and inactive for > 30 days, we will close it due to inactivity. The author is welcome to re-open and update.
#### Reviewing
- Use constructive tone when writing reviews.
- If there are changes required, state clearly what needs to be done before the PR can be approved.
- 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.
- The committers reserve the right to reject any PR and in some cases may request the author to file an issue.
#### Test Environments
- Members of the Apache GitHub org can launch an ephemeral test environment directly on a pull request by creating a comment containing (only) the command `/testenv up`.
- Note that org membership must be public in order for this validation to function properly.
- Feature flags may be set for a test environment by specifying the flag name (prefixed with `FEATURE_`) and value after the command.
- Format: `/testenv up FEATURE_<feature flag name>=true|false`
- Example: `/testenv up FEATURE_DASHBOARD_NATIVE_FILTERS=true`
- Multiple feature flags may be set in single command, separated by whitespace
- A comment will be created by the workflow script with the address and login information for the ephemeral environment.
- Test environments may be created once the Docker build CI workflow for the PR has completed successfully.
- Test environments do not currently update automatically when new commits are added to a pull request.
- Test environments do not currently support async workers, though this is planned.
- Running test environments will be shutdown upon closing the pull request.
#### Merging
- At least one approval is required for merging a PR.
- PR is usually left open for at least 24 hours before merging.
- After the PR is merged, [close the corresponding issue(s)](https://help.github.com/articles/closing-issues-using-keywords/).
#### Post-merge Responsibility
- Project maintainers may contact the PR author if new issues are introduced by the PR.
- Project maintainers may revert your changes if a critical issue is found, such as breaking master branch CI.

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@ -1,6 +1,13 @@
---
sidebar_position: 5
version: 1
---
import InteractiveSVG from '../../src/components/InteractiveERDSVG';
# Entity-Relationship Diagram
# Resources
## Entity-Relationship Diagram
Here is our interactive ERD:

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@ -1,54 +0,0 @@
---
title: Style Guide
hide_title: true
sidebar_position: 4
version: 1
---
## Design Guidelines
### Capitalization guidelines
#### Sentence case
Use sentence-case capitalization for everything in the UI (except these \*\*).
Sentence case is predominantly lowercase. Capitalize only the initial character of the first word, and other words that require capitalization, like:
- **Proper nouns.** Objects in the product _are not_ considered proper nouns e.g. dashboards, charts, saved queries etc. Proprietary feature names eg. SQL Lab, Preset Manager _are_ considered proper nouns
- **Acronyms** (e.g. CSS, HTML)
- When referring to **UI labels that are themselves capitalized** from sentence case (e.g. page titles - Dashboards page, Charts page, Saved queries page, etc.)
- User input that is reflected in the UI. E.g. a user-named a dashboard tab
**Sentence case vs. Title case:**
Title case: "A Dog Takes a Walk in Paris"
Sentence case: "A dog takes a walk in Paris"
**Why sentence case?**
- Its generally accepted as the quickest to read
- Its the easiest form to distinguish between common and proper nouns
#### How to refer to UI elements
When writing about a UI element, use the same capitalization as used in the UI.
For example, if an input field is labeled “Name” then you refer to this as the “Name input field”. Similarly, if a button has the label “Save” in it, then it is correct to refer to the “Save button”.
Where a product page is titled “Settings”, you refer to this in writing as follows:
“Edit your personal information on the Settings page”.
Often a product page will have the same title as the objects it contains. In this case, refer to the page as it appears in the UI, and the objects as common nouns:
- Upload a dashboard on the Dashboards page
- Go to Dashboards
- View dashboard
- View all dashboards
- Upload CSS templates on the CSS templates page
- Queries that you save will appear on the Saved queries page
- Create custom queries in SQL Lab then create dashboards
#### \*\*Exceptions to sentence case:
- Input labels, buttons and UI tabs are all caps
- User input values (e.g. column names, SQL Lab tab names) should be in their original case

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@ -1,299 +0,0 @@
---
title: Testing
hide_title: true
sidebar_position: 8
version: 1
---
## Testing
### Python Testing
All python tests are carried out in [tox](https://tox.readthedocs.io/en/latest/index.html)
a standardized testing framework.
All python tests can be run with any of the tox [environments](https://tox.readthedocs.io/en/latest/example/basic.html#a-simple-tox-ini-default-environments), via,
```bash
tox -e <environment>
```
For example,
```bash
tox -e py38
```
Alternatively, you can run all tests in a single file via,
```bash
tox -e <environment> -- tests/test_file.py
```
or for a specific test via,
```bash
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.
There is also a utility script included in the Superset codebase to run python integration tests. The [readme can be
found here](https://github.com/apache/superset/tree/master/scripts/tests)
To run all integration tests for example, run this script from the root directory:
```bash
scripts/tests/run.sh
```
You can run unit tests found in './tests/unit_tests' for example with pytest. It is a simple way to run an isolated test that doesn't need any database setup
```bash
pytest ./link_to_test.py
```
#### Testing with local Presto connections
If you happen to change db engine spec for Presto/Trino, you can run a local Presto cluster with Docker:
```bash
docker run -p 15433:15433 starburstdata/presto:350-e.6
```
Then update `SUPERSET__SQLALCHEMY_EXAMPLES_URI` to point to local Presto cluster:
```bash
export SUPERSET__SQLALCHEMY_EXAMPLES_URI=presto://localhost:15433/memory/default
```
### Frontend Testing
We use [Jest](https://jestjs.io/) and [Enzyme](https://airbnb.io/enzyme/) to test TypeScript/JavaScript. Tests can be run with:
```bash
cd superset-frontend
npm run test
```
To run a single test file:
```bash
npm run test -- path/to/file.js
```
### e2e Integration Testing
We use [Cypress](https://www.cypress.io/) for end-to-end integration
tests. One easy option to get started quickly is to leverage `tox` to
run the whole suite in an isolated environment.
```bash
tox -e cypress
```
Alternatively, you can go lower level and set things up in your
development environment by following these steps:
First set up a python/flask backend:
```bash
export SUPERSET_CONFIG=tests.integration_tests.superset_test_config
export SUPERSET_TESTENV=true
export CYPRESS_BASE_URL="http://localhost:8081"
superset db upgrade
superset load_test_users
superset init
superset load-examples --load-test-data
superset run --port 8081
```
In another terminal, prepare the frontend and run Cypress tests:
```bash
cd superset-frontend
npm run build-instrumented
cd cypress-base
npm install
# run tests via headless Chrome browser (requires Chrome 64+)
npm run cypress-run-chrome
# run tests from a specific file
npm run cypress-run-chrome -- --spec cypress/e2e/explore/link.test.ts
# run specific file with video capture
npm run cypress-run-chrome -- --spec cypress/e2e/dashboard/index.test.js --config video=true
# to open the cypress ui
npm run cypress-debug
# to point cypress to a url other than the default (http://localhost:8088) set the environment variable before running the script
# e.g., CYPRESS_BASE_URL="http://localhost:9000"
CYPRESS_BASE_URL=<your url> npm run cypress open
```
See [`superset-frontend/cypress_build.sh`](https://github.com/apache/superset/blob/master/superset-frontend/cypress_build.sh).
As an alternative you can use docker compose environment for testing:
Make sure you have added below line to your /etc/hosts file:
`127.0.0.1 db`
If you already have launched Docker environment please use the following command to assure a fresh database instance:
`docker compose down -v`
Launch environment:
`CYPRESS_CONFIG=true docker compose up`
It will serve backend and frontend on port 8088.
Run Cypress tests:
```bash
cd cypress-base
npm install
npm run cypress open
```
### Debugging Server App
Follow these instructions to debug the Flask app running inside a docker container.
First add the following to the ./docker-compose.yaml file
```diff
superset:
env_file: docker/.env
image: *superset-image
container_name: superset_app
command: ["/app/docker/docker-bootstrap.sh", "app"]
restart: unless-stopped
+ cap_add:
+ - SYS_PTRACE
ports:
- 8088:8088
+ - 5678:5678
user: "root"
depends_on: *superset-depends-on
volumes: *superset-volumes
environment:
CYPRESS_CONFIG: "${CYPRESS_CONFIG}"
```
Start Superset as usual
```bash
docker compose up
```
Install the required libraries and packages to the docker container
Enter the superset_app container
```bash
docker exec -it superset_app /bin/bash
root@39ce8cf9d6ab:/app#
```
Run the following commands inside the container
```bash
apt update
apt install -y gdb
apt install -y net-tools
pip install debugpy
```
Find the PID for the Flask process. Make sure to use the first PID. The Flask app will re-spawn a sub-process every time you change any of the python code. So it's important to use the first PID.
```bash
ps -ef
UID PID PPID C STIME TTY TIME CMD
root 1 0 0 14:09 ? 00:00:00 bash /app/docker/docker-bootstrap.sh app
root 6 1 4 14:09 ? 00:00:04 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
root 10 6 7 14:09 ? 00:00:07 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
```
Inject debugpy into the running Flask process. In this case PID 6.
```bash
python3 -m debugpy --listen 0.0.0.0:5678 --pid 6
```
Verify that debugpy is listening on port 5678
```bash
netstat -tunap
Active Internet connections (servers and established)
Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name
tcp 0 0 0.0.0.0:5678 0.0.0.0:* LISTEN 462/python
tcp 0 0 0.0.0.0:8088 0.0.0.0:* LISTEN 6/python
```
You are now ready to attach a debugger to the process. Using VSCode you can configure a launch configuration file .vscode/launch.json like so.
```
{
"version": "0.2.0",
"configurations": [
{
"name": "Attach to Superset App in Docker Container",
"type": "python",
"request": "attach",
"connect": {
"host": "127.0.0.1",
"port": 5678
},
"pathMappings": [
{
"localRoot": "${workspaceFolder}",
"remoteRoot": "/app"
}
]
},
]
}
```
VSCode will not stop on breakpoints right away. We've attached to PID 6 however it does not yet know of any sub-processes. In order to "wakeup" the debugger you need to modify a python file. This will trigger Flask to reload the code and create a new sub-process. This new sub-process will be detected by VSCode and breakpoints will be activated.
### Debugging Server App in Kubernetes Environment
To debug Flask running in POD inside kubernetes cluster. You'll need to make sure the pod runs as root and is granted the SYS_TRACE capability.These settings should not be used in production environments.
```
securityContext:
capabilities:
add: ["SYS_PTRACE"]
```
See (set capabilities for a container)[https://kubernetes.io/docs/tasks/configure-pod-container/security-context/#set-capabilities-for-a-container] for more details.
Once the pod is running as root and has the SYS_PTRACE capability it will be able to debug the Flask app.
You can follow the same instructions as in the docker-compose. Enter the pod and install the required library and packages; gdb, netstat and debugpy.
Often in a Kubernetes environment nodes are not addressable from outside the cluster. VSCode will thus be unable to remotely connect to port 5678 on a Kubernetes node. In order to do this you need to create a tunnel that port forwards 5678 to your local machine.
```
kubectl port-forward pod/superset-<some random id> 5678:5678
```
You can now launch your VSCode debugger with the same config as above. VSCode will connect to to 127.0.0.1:5678 which is forwarded by kubectl to your remote kubernetes POD.
### Storybook
Superset includes a [Storybook](https://storybook.js.org/) to preview the layout/styling of various Superset components, and variations thereof. To open and view the Storybook:
```bash
cd superset-frontend
npm run storybook
```
When contributing new React components to Superset, please try to add a Story alongside the component's `jsx/tsx` file.

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---
title: Translating
hide_title: true
sidebar_position: 9
version: 1
---
## Translating
We use [Flask-Babel](https://python-babel.github.io/flask-babel/) to translate Superset.
In Python files, we use the following
[translation functions](https://python-babel.github.io/flask-babel/#using-translations)
from `Flask-Babel`:
- `gettext` and `lazy_gettext` (usually aliased to `_`): for translating singular
strings.
- `ngettext`: for translating strings that might become plural.
```python
from flask_babel import lazy_gettext as _
```
then wrap the 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 TypeScript/JavaScript, the technique is similar:
we import `t` (simple translation), `tn` (translation containing a number).
```javascript
import { t, tn } from "@superset-ui/translation";
```
### 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.
```python
LANGUAGES = {
'en': {'flag': 'us', 'name': 'English'},
'fr': {'flag': 'fr', 'name': 'French'},
'zh': {'flag': 'cn', 'name': 'Chinese'},
}
```
### Creating a new language dictionary
First check if the language code for your target language already exists. Check if the
[two letter ISO 639-1 code](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes)
for your target language already exists in the `superset/translations` directory:
```bash
ls superset/translations | grep -E "^[a-z]{2}\/"
```
If your language already has a preexisting translation, skip to the next section
The following languages are already supported by Flask AppBuilder, and will make it
easier to translate the application to your target language:
[Flask AppBuilder i18n documentation](https://flask-appbuilder.readthedocs.io/en/latest/i18n.html)
To create a dictionary for a new language, first make sure the necessary dependencies are installed:
```bash
pip install -r superset/translations/requirements.txt
```
Then run the following, where `LANGUAGE_CODE` is replaced with the language code for your target
language:
```bash
pybabel init -i superset/translations/messages.pot -d superset/translations -l LANGUAGE_CODE
```
For instance, to add a translation for Finnish (language code `fi`), run the following:
```bash
pybabel init -i superset/translations/messages.pot -d superset/translations -l fi
```
### Extracting new strings for translation
This step needs to be done every time application strings change. This happens fairly
frequently, so if you want to ensure that your translation has good coverage, this
step needs to be run fairly frequently and the updated strings merged to the upstream
codebase via PRs. To update the template file `superset/translations/messages.pot`
with current application strings, run the following command:
```bash
pybabel extract -F superset/translations/babel.cfg -o superset/translations/messages.pot -k _ -k __ -k t -k tn -k tct .
```
Do not forget to update this file with the appropriate license information.
### Updating language files
Run the following command to update the language files with the new extracted strings.
```bash
pybabel update -i superset/translations/messages.pot -d superset/translations --ignore-obsolete
```
You can then translate the strings gathered in files located under
`superset/translation`, where there's one folder per language. You can use [Poedit](https://poedit.net/features)
to translate the `po` file more conveniently.
Here is [a tutorial](https://web.archive.org/web/20220517065036/https://wiki.lxde.org/en/Translate_*.po_files_with_Poedit).
To perform the translation on MacOS, you can install `poedit` via Homebrew:
```bash
brew install poedit
```
After this, just start the `poedit` application and open the `messages.po` file. In the
case of the Finnish translation, this would be `superset/translations/fi/LC_MESSAGES/messages.po`.
### Applying translations
To make the translations available on the frontend, we need to convert the PO file into
a JSON file. To do this, we need to globally install the npm package `po2json`.
```bash
npm install -g po2json
```
To convert all PO files to formatted JSON files you can use the `po2json.sh` script.
```bash
./scripts/po2json.sh
```
If you get errors running `po2json`, you might be running the Ubuntu package with the same
name, rather than the Node.js 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`).
If you get a lot of `[null,***]` in `messages.json`, just delete all the `null,`.
For example, `"year":["年"]` is correct while `"year":[null,"年"]`is incorrect.
Finally, for the translations to take effect we need to compile translation catalogs into
binary MO files.
```bash
pybabel compile -d superset/translations
```

View File

@ -1,62 +0,0 @@
---
title: Types of Contributions
hide_title: true
sidebar_position: 2
version: 1
---
## Types of Contributions
### Report Bug
The best way to report a bug is to file an issue on GitHub. Please include:
- Your operating system name and version.
- Superset version.
- Detailed steps to reproduce the bug.
- Any details about your local setup that might be helpful in troubleshooting.
When posting Python stack traces, please quote them using
[Markdown blocks](https://help.github.com/articles/creating-and-highlighting-code-blocks/).
_Please note that feature requests opened as GitHub Issues will be moved to Discussions._
### Submit Ideas or Feature Requests
The best way is to start an ["Ideas" Discussion thread](https://github.com/apache/superset/discussions/categories/ideas) on GitHub:
- 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 your contributions are as welcome as anyone's :)
To propose large features or major changes to codebase, and help usher in those changes, please create a **Superset Improvement Proposal (SIP)**. See template from [SIP-0](https://github.com/apache/superset/issues/5602)
### Fix Bugs
Look through the GitHub issues. Issues tagged with `#bug` are
open to whoever wants to implement them.
### Implement Features
Look through the GitHub issues. Issues tagged with
`#feature` 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](#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 into 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](#translating) for more details.
### Ask Questions
There is a dedicated [`apache-superset` tag](https://stackoverflow.com/questions/tagged/apache-superset) on [StackOverflow](https://stackoverflow.com/). Please use it when asking questions.

View File

@ -1,13 +1,11 @@
---
title: Frequently Asked Questions
hide_title: true
sidebar_position: 9
---
## Frequently Asked Questions
# FAQ
### How big of a dataset can Superset handle?
## How big of a dataset can Superset handle?
Superset can work with even gigantic databases! Superset acts as a thin layer above your underlying
databases or data engines, which do all the processing. Superset simply visualizes the results of
@ -17,7 +15,7 @@ The key to achieving acceptable performance in Superset is whether your database
and return results at a speed that is acceptable to your users. If you experience slow performance with
Superset, benchmark and tune your data warehouse.
### What are the computing specifications required to run Superset?
## What are the computing specifications required to run Superset?
The specs of your Superset installation depend on how many users you have and what their activity is, not
on the size of your data. Superset admins in the community have reported 8GB RAM, 2vCPUs as adequate to
@ -31,7 +29,7 @@ Superset's application metadata does not require a very large database to store
the log file grows over time.
### Can I join / query multiple tables at one time?
## Can I join / query multiple tables at one time?
Not in the Explore or Visualization UI. A Superset SQLAlchemy datasource can only be a single table
or a view.
@ -52,19 +50,19 @@ the result to users interacting with Superset.
However, if you are using SQL Lab, there is no such limitation. You can write SQL queries to join
multiple tables as long as your database account has access to the tables.
### How do I create my own visualization?
## How do I create my own visualization?
We recommend reading the instructions in
[Creating Visualization Plugins](/docs/contributing/creating-viz-plugins).
[Creating Visualization Plugins](/docs/contributing/howtos#creating-visualization-plugins).
### Can I upload and visualize CSV data?
## Can I upload and visualize CSV data?
Absolutely! Read the instructions [here](/docs/using-superset/exploring-data) to learn
how to enable and use CSV upload.
### Why are my queries timing out?
## Why are my queries timing out?
There are many reasons may cause long query timing out.
There are many possible causes for why a long-running query might time out.
For running long query from Sql Lab, by default Superset allows it run as long as 6 hours before it
being killed by celery. If you want to increase the time for running query, you can specify the
@ -86,7 +84,7 @@ timeout settings in **superset_config.py**:
SUPERSET_WEBSERVER_TIMEOUT = 60
```
### Why is the map not visible in the geospatial visualization?
## Why is the map not visible in the geospatial visualization?
You need to register a free account at [Mapbox.com](https://www.mapbox.com), obtain an API key, and add it
to **.env** at the key MAPBOX_API_KEY:
@ -95,7 +93,7 @@ to **.env** at the key MAPBOX_API_KEY:
MAPBOX_API_KEY = "longstringofalphanumer1c"
```
### How to limit the timed refresh on a dashboard?
## How to limit the timed refresh on a dashboard?
By default, the dashboard timed refresh feature allows you to automatically re-query every slice on
a dashboard according to a set schedule. Sometimes, however, you wont want all of the slices to be
@ -148,7 +146,7 @@ SQLALCHEMY_DATABASE_URI = 'sqlite:////new/location/superset.db?check_same_thread
You can read more about customizing Superset using the configuration file
[here](/docs/configuration/configuring-superset).
### What if the table schema changed?
## What if the table schema changed?
Table schemas evolve, and Superset needs to reflect that. Its pretty common in the life cycle of a
dashboard to want to add a new dimension or metric. To get Superset to discover your new columns,
@ -157,7 +155,7 @@ whose schema has changed, and hit **Sync columns from source** from the **Column
Behind the scene, the new columns will get merged. Following this, you may want to re-edit the
table afterwards to configure the Columns tab, check the appropriate boxes and save again.
### What database engine can I use as a backend for Superset?
## What database engine can I use as a backend for Superset?
To clarify, the database backend is an OLTP database used by Superset to store its internal
information like your list of users and dashboard definitions. While Superset supports a
@ -170,12 +168,12 @@ may work but isnt tested. It has been reported that [Microsoft SQL Server do
work as a Superset backend](https://github.com/apache/superset/issues/18961). Column-store,
non-OLTP databases are not designed for this type of workload.
### How can I configure OAuth authentication and authorization?
## How can I configure OAuth authentication and authorization?
You can take a look at this Flask-AppBuilder
[configuration example](https://github.com/dpgaspar/Flask-AppBuilder/blob/master/examples/oauth/config.py).
### Is there a way to force the dashboard to use specific colors?
## Is there a way to force the dashboard to use specific colors?
It is possible on a per-dashboard basis by providing a mapping of labels to colors in the JSON
Metadata attribute using the `label_colors` key.
@ -189,7 +187,7 @@ Metadata attribute using the `label_colors` key.
}
```
### Does Superset work with [insert database engine here]?
## Does Superset work with [insert database engine here]?
The [Connecting to Databases section](/docs/databases/installing-database-drivers) provides the best
overview for supported databases. Database engines not listed on that page may work too. We rely on
@ -224,7 +222,7 @@ are typical in basic SQL:
- apply HAVING-type filters
- be schema-aware, expose columns and types
### Does Superset offer a public API?
## Does Superset offer a public API?
Yes, a public REST API, and the surface of that API formal is expanding steadily. You can read more about this API and
interact with it using Swagger [here](/docs/api).
@ -248,20 +246,20 @@ guarantees and are not recommended but may fit your use case temporarily:
- using the internal FAB ModelView API (to be deprecated in Superset)
- altering the source code in your fork
### How can I see usage statistics (e.g., monthly active users)?
## How can I see usage statistics (e.g., monthly active users)?
This functionality is not included with Superset, but you can extract and analyze Superset's application
metadata to see what actions have occurred. By default, user activities are logged in the `logs` table
in Superset's metadata database. One company has published a write-up of [how they analyzed Superset
usage, including example queries](https://engineering.hometogo.com/monitor-superset-usage-via-superset-c7f9fba79525).
### What Does Hours Offset in the Edit Dataset view do?
## What Does Hours Offset in the Edit Dataset view do?
In the Edit Dataset view, you can specify a time offset. This field lets you configure the
number of hours to be added or subtracted from the time column.
This can be used, for example, to convert UTC time to local time.
### Does Superset collect any telemetry data?
## Does Superset collect any telemetry data?
Superset uses [Scarf](https://about.scarf.sh/) by default to collect basic telemetry data upon installing and/or running Superset. This data helps the maintainers of Superset better understand which versions of Superset are being used, in order to prioritize patch/minor releases and security fixes.
We use the [Scarf Gateway](https://docs.scarf.sh/gateway/) to sit in front of container registries, the [scarf-js](https://about.scarf.sh/package-sdks) package to track `npm` installations, and a Scarf pixel to gather anonymous analytics on Superset page views.
@ -269,7 +267,7 @@ Scarf purges PII and provides aggregated statistics. Superset users can easily o
Superset maintainers can also opt out of telemetry data collection by setting the `SCARF_ANALYTICS` environment variable to `false` in the Superset container (or anywhere Superset/webpack are run).
Additional opt-out instructions for Docker users are available on the [Docker Installation](/docs/installation/docker-compose) page.
### Does Superset have an archive panel or trash bin from which a user can recover deleted assets?
## Does Superset have an archive panel or trash bin from which a user can recover deleted assets?
No. Currently, there is no way to recover a deleted Superset dashboard/chart/dataset/database from the UI. However, there is an [ongoing discussion](https://github.com/apache/superset/discussions/18386) about implementing such a feature.

View File

@ -18,7 +18,6 @@ docker compose down
Then, update the folder that mirrors the `superset` repo through git:
```bash
cd superset/
git pull origin master
```

View File

@ -1,6 +1,5 @@
---
title: CVEs fixed by release
hide_title: true
sidebar_position: 2
---

View File

@ -1,6 +1,5 @@
---
title: Security Configurations
hide_title: true
sidebar_position: 1
---

View File

@ -1,145 +0,0 @@
---
title: Chart Parameters Reference
hide_title: true
sidebar_position: 4
version: 1
---
## Chart Parameters
Chart parameters are stored as a JSON encoded string in the `slices.params` column and are often referenced throughout the code as form-data. Currently the form-data is neither versioned nor typed as thus is somewhat free-formed. Note in the future there may be merit in using something like [JSON Schema](https://json-schema.org/) to both annotate and validate the JSON object in addition to using a Mypy `TypedDict` (introduced in Python 3.8) for typing the form-data in the backend. This section serves as a potential primer for that work.
The following tables provide a non-exhaustive list of the various fields which can be present in the JSON object grouped by the Explorer pane sections. These values were obtained by extracting the distinct fields from a legacy deployment consisting of tens of thousands of charts and thus some fields may be missing whilst others may be deprecated.
Note not all fields are correctly categorized. The fields vary based on visualization type and may appear in different sections depending on the type. Verified deprecated columns may indicate a missing migration and/or prior migrations which were unsuccessful and thus future work may be required to clean up the form-data.
### Datasource & Chart Type
| Field | Type | Notes |
| ----------------- | -------- | ------------------------------------ |
| `database_name` | _string_ | _Deprecated?_ |
| `datasource` | _string_ | `<datasource_id>__<datasource_type>` |
| `datasource_id` | _string_ | _Deprecated?_ See `datasource` |
| `datasource_name` | _string_ | _Deprecated?_ |
| `datasource_type` | _string_ | _Deprecated?_ See `datasource` |
| `viz_type` | _string_ | The **Visualization Type** widget |
### Time
| Field | Type | Notes |
| ------------------ | -------- | ------------------------------------- |
| `granularity_sqla` | _string_ | The SQLA **Time Column** widget |
| `time_grain_sqla` | _string_ | The SQLA **Time Grain** widget |
| `time_range` | _string_ | The **Time range** widget |
### GROUP BY
| Field | Type | Notes |
| ------------------------- | --------------- | ----------------- |
| `metrics` | _array(string)_ | See Query section |
| `order_asc` | - | See Query section |
| `row_limit` | - | See Query section |
| `timeseries_limit_metric` | - | See Query section |
### NOT GROUPED BY
| Field | Type | Notes |
| --------------- | --------------- | ----------------------- |
| `order_by_cols` | _array(string)_ | The **Ordering** widget |
| `row_limit` | - | See Query section |
### Y Axis 1
| Field | Type | Notes |
| --------------- | ---- | -------------------------------------------------- |
| `metric` | - | The **Left Axis Metric** widget. See Query section |
| `y_axis_format` | - | See Y Axis section |
### Y Axis 2
| Field | Type | Notes |
| ---------- | ---- | --------------------------------------------------- |
| `metric_2` | - | The **Right Axis Metric** widget. See Query section |
### Query
| Field | Type | Notes |
| ------------------------------------------------------------------------------------------------------ | ------------------------------------------------- | ------------------------------------------------- |
| `adhoc_filters` | _array(object)_ | The **Filters** widget |
| `extra_filters` | _array(object)_ | Another pathway to the **Filters** widget.<br/>It is generally used to pass dashboard filter parameters to a chart.<br/>It can be used for appending additional filters to a chart that has been saved with its own filters on an ad-hoc basis if the chart is being used as a standalone widget.<br/><br/>For implementation examples see : [utils test.py](https://github.com/apache/superset/blob/66a4c94a1ed542e69fe6399bab4c01d4540486cf/tests/utils_tests.py#L181)<br/>For insight into how superset processes the contents of this parameter see: [exploreUtils/index.js](https://github.com/apache/superset/blob/93c7f5bb446ec6895d7702835f3157426955d5a9/superset-frontend/src/explore/exploreUtils/index.js#L159) |
| `columns` | _array(string)_ | The **Breakdowns** widget |
| `groupby` | _array(string)_ | The **Group by** or **Series** widget |
| `limit` | _number_ | The **Series Limit** widget |
| `metric`<br/>`metric_2`<br/>`metrics`<br/>`percent_metrics`<br/>`secondary_metric`<br/>`size`<br/>`x`<br/>`y` | _string_,_object_,_array(string)_,_array(object)_ | The metric(s) depending on the visualization type |
| `order_asc` | _boolean_ | The **Sort Descending** widget |
| `row_limit` | _number_ | The **Row limit** widget |
| `timeseries_limit_metric` | _object_ | The **Sort By** widget |
The `metric` (or equivalent) and `timeseries_limit_metric` fields are all composed of either metric names or the JSON representation of the `AdhocMetric` TypeScript type. The `adhoc_filters` is composed of the JSON represent of the `AdhocFilter` TypeScript type (which can comprise of columns or metrics depending on whether it is a WHERE or HAVING clause). The `all_columns`, `all_columns_x`, `columns`, `groupby`, and `order_by_cols` fields all represent column names.
### Chart Options
| Field | Type | Notes |
| -------------- | --------- | --------------------------- |
| `color_picker` | _object_ | The **Fixed Color** widget |
| `label_colors` | _object_ | The **Color Scheme** widget |
| `normalized` | _boolean_ | The **Normalized** widget |
### Y Axis
| Field | Type | Notes |
| ---------------- | -------- | ---------------------------- |
| `y_axis_2_label` | _N/A_ | _Deprecated?_ |
| `y_axis_format` | _string_ | The **Y Axis Format** widget |
| `y_axis_zero` | _N/A_ | _Deprecated?_ |
Note the `y_axis_format` is defined under various section for some charts.
### Other
| Field | Type | Notes |
| -------------- | -------- | ----- |
| `color_scheme` | _string_ | |
### Unclassified
| Field | Type | Notes |
| ----------------------------- | ----- | ----- |
| `add_to_dash` | _N/A_ | |
| `code` | _N/A_ | |
| `collapsed_fieldsets` | _N/A_ | |
| `comparison type` | _N/A_ | |
| `country_fieldtype` | _N/A_ | |
| `default_filters` | _N/A_ | |
| `entity` | _N/A_ | |
| `expanded_slices` | _N/A_ | |
| `filter_immune_slice_fields` | _N/A_ | |
| `filter_immune_slices` | _N/A_ | |
| `flt_col_0` | _N/A_ | |
| `flt_col_1` | _N/A_ | |
| `flt_eq_0` | _N/A_ | |
| `flt_eq_1` | _N/A_ | |
| `flt_op_0` | _N/A_ | |
| `flt_op_1` | _N/A_ | |
| `goto_dash` | _N/A_ | |
| `import_time` | _N/A_ | |
| `label` | _N/A_ | |
| `linear_color_scheme` | _N/A_ | |
| `new_dashboard_name` | _N/A_ | |
| `new_slice_name` | _N/A_ | |
| `num_period_compare` | _N/A_ | |
| `period_ratio_type` | _N/A_ | |
| `perm` | _N/A_ | |
| `rdo_save` | _N/A_ | |
| `refresh_frequency` | _N/A_ | |
| `remote_id` | _N/A_ | |
| `resample_fillmethod` | _N/A_ | |
| `resample_how` | _N/A_ | |
| `rose_area_proportion` | _N/A_ | |
| `save_to_dashboard_id` | _N/A_ | |
| `schema` | _N/A_ | |
| `series` | _N/A_ | |
| `show_bubbles` | _N/A_ | |
| `slice_name` | _N/A_ | |
| `timed_refresh_immune_slices` | _N/A_ | |
| `userid` | _N/A_ | |

View File

@ -92,11 +92,11 @@ const config = {
from: '/visualization.html',
},
{
to: '/docs/frequently-asked-questions',
to: '/docs/faq',
from: '/videos.html',
},
{
to: '/docs/frequently-asked-questions',
to: '/docs/faq',
from: '/faq.html',
},
{
@ -120,13 +120,21 @@ const config = {
from: '/docs/roadmap',
},
{
to: '/docs/contributing/contributing-page',
to: '/docs/contributing/',
from: '/docs/contributing/contribution-guidelines',
},
{
to: '/docs/contributing/',
from: '/docs/contributing/contribution-page',
},
{
to: '/docs/databases/yugabytedb',
from: '/docs/databases/yugabyte/',
},
{
to: '/docs/faq',
from: '/docs/frequently-asked-questions',
},
],
},
],
@ -182,7 +190,7 @@ const config = {
},
{
label: 'FAQ',
to: '/docs/frequently-asked-questions',
to: '/docs/faq',
},
],
},

View File

@ -86,8 +86,8 @@ const sidebars = {
},
{
type: 'doc',
label: 'Frequently Asked Questions',
id: 'frequently-asked-questions',
label: 'FAQ',
id: 'faq',
},
{
type: 'doc',