QT/superset2
1
0
Fork 0
mirror of https://github.com/apache/superset.git synced 2026-04-21 09:04:38 +00:00
Code Issues Packages Projects Releases Wiki Activity

feat(docs): Docusaurus multi-versioning, Developer Portal starter kit (#34271)

Browse Source 
Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
Evan Rusackas
2025-08-22 09:53:01 -07:00
committed by GitHub
parent 2b2cc96f11
commit 0a45a89786
71 changed files with 16791 additions and 1809 deletions
Download Patch File Download Diff File Expand all files Collapse all files

634
docs/versioned_docs/version-6.0.0/contributing/howtos.mdx Normal file
View File

@@ -0,0 +1,634 @@
---
title: Development How-tos
hide_title: true
sidebar_position: 4
version: 1
---
# 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 3](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):
```bash
$ 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:
```bash
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:
```bash
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
`pytest`, backend by docker-compose is how we recommend running tests locally.
For a more complex test matrix (against different database backends, python versions, ...) you
can rely on our GitHub Actions by simply opening a draft pull request.
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
For E2E testing, we recommend that you use a `docker compose` backend
```bash
CYPRESS_CONFIG=true docker compose up --build
```
`docker compose` will get to work and expose a Cypress-ready Superset app.
This app uses a different database schema (`superset_cypress`) to keep it isolated from
your other dev environmen(s)t, a specific set of examples, and a set of configurations that
aligns with the expectations within the end-to-end tests. Also note that it's served on a
different port than the default port for the backend (`8088`).
Now in another terminal, let's get ready to execute some Cypress commands. First, tell cypress
to connect to the Cypress-ready Superset backend.
```
CYPRESS_BASE_URL=http://localhost:8081
```
```bash
# superset-frontend/cypress-base is the base folder for everything Cypress-related
# It's essentially its own npm app, with its own dependencies, configurations and utilities
cd superset-frontend/cypress-base
npm install
# use interactive mode to run tests, while keeping memory usage contained
# this will fire up an interactive Cypress UI
# as you alter the code, the tests will re-run automatically, and you can visualize each
# and every step for debugging purposes
npx cypress open --config numTestsKeptInMemory=5
# to run the test suite on the command line using chrome (same as CI)
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
```
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: "${CYPRESS_CONFIG}"
```
Start Superset as usual
```bash
docker compose up
```
Install the required libraries and packages to the docker container
Enter the superset_app container
```bash
docker exec -it superset_app /bin/bash
root@39ce8cf9d6ab:/app#
```
Run the following commands inside the container
```bash
apt update
apt install -y gdb
apt install -y net-tools
pip install debugpy
```
Find the PID for the Flask process. Make sure to use the first PID. The Flask app will re-spawn a sub-process every time you change any of the python code. So it's important to use the first PID.
```bash
ps -ef
UID PID PPID C STIME TTY TIME CMD
root 1 0 0 14:09 ? 00:00:00 bash /app/docker/docker-bootstrap.sh app
root 6 1 4 14:09 ? 00:00:04 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
root 10 6 7 14:09 ? 00:00:07 /usr/local/bin/python /usr/bin/flask run -p 8088 --with-threads --reload --debugger --host=0.0.0.0
```
Inject debugpy into the running Flask process. In this case PID 6.
```bash
python3 -m debugpy --listen 0.0.0.0:5678 --pid 6
```
Verify that debugpy is listening on port 5678
```bash
netstat -tunap
Active Internet connections (servers and established)
Proto Recv-Q Send-Q Local Address Foreign Address State PID/Program name
tcp 0 0 0.0.0.0:5678 0.0.0.0:* LISTEN 462/python
tcp 0 0 0.0.0.0:8088 0.0.0.0:* LISTEN 6/python
```
You are now ready to attach a debugger to the process. Using VSCode you can configure a launch configuration file .vscode/launch.json like so.
```json
{
"version": "0.2.0",
"configurations": [
{
"name": "Attach to Superset App in Docker Container",
"type": "python",
"request": "attach",
"connect": {
"host": "127.0.0.1",
"port": 5678
},
"pathMappings": [
{
"localRoot": "${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 "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 a 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.
```yaml
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 `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.
```bash
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.
## Contributing 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
Periodically, when working on translations, we need to extract the strings from both the
backend and the frontend to compile a list of all strings to be translated. It doesn't
happen automatically and is a required step to gather the strings and get them into the
`.po` files where they can be translated, so that they can then be compiled.
This script does just that:
```bash
./scripts/translations/babel_update.sh
```
### 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 collection of JSON files. To convert all PO files to formatted JSON files you can use
the `build-translation` script
```bash
# Install dependencies if you haven't already
cd superset-frontend/ && npm ci
# Compile translations for the frontend
npm run build-translation
```
Finally, for the translations to take effect we need to compile translation catalogs into
binary MO files for the backend using `pybabel`.
```bash
# inside the project root
pybabel compile -d superset/translations
```
## Linting
### Python
We use [ruff](https://github.com/astral-sh/ruff) for linting which can be invoked via:
```
# auto-reformat using ruff
ruff format
# lint check with ruff
ruff check
# lint fix with ruff
ruff check --fix
```
Ruff configuration is located in our
(pyproject.toml)[https://github.com/apache/superset/blob/master/pyproject.toml] file
All this is configured to run in pre-commit hooks, which we encourage you to setup
with `pre-commit install`
### 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"
]
```
## GitHub Ephemeral Environments
On any given pull request on GitHub, it's possible to create a temporary environment/deployment
by simply adding the label `testenv-up` to the PR. Once you add the `testenv-up` label, a
GitHub Action will be triggered that will:
- build a docker image
- deploy it in EC2 (sponsored by the folks at [Preset](https://preset.io))
- write a comment on the PR with a link to the ephemeral environment
For more advanced use cases, it's possible to set a feature flag on the PR body, which will
take effect on the ephemeral environment. For example, if you want to set the `TAGGING_SYSTEM`
feature flag to `true`, you can add the following line to the PR body/description:
```
FEATURE_TAGGING_SYSTEM=true
```
Simarly, it's possible to disable feature flags with:
```
FEATURE_TAGGING_SYSTEM=false
```