docs/developer_portal/contributing/development-setup.md

---
title: Setting up a Development Environment
sidebar_position: 2
---

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# Setting up a Development Environment

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 a "hello world" into any part of Superset should be as simple as

```bash
# getting docker compose to fire up services, and rebuilding if some docker layers have changed
# using the `--build` suffix may be slower and optional if layers like py dependencies haven't changed
docker compose up --build
```

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 which
    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 the 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 within the services, meaning updating
  the code on the host will be reflected in the docker images
- Superset is served at localhost:9000/
- You can login with admin/admin

:::note
Installing and building Node modules for Apache Superset inside `superset-node` can take a
significant amount of time. This is normal due to the size of the dependencies. Please be
patient while the process completes, as long wait times do not indicate an issue with your setup.
If delays seem excessive, check your internet connection or system resources.
:::

:::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.
:::

### Supported environment variables

Affecting the Docker build process:

- **SUPERSET_BUILD_TARGET (default=dev):** which --target to build, either `lean` or `dev` are commonly used
- **INCLUDE_FIREFOX (default=false):** whether to include the Firefox headless browser in the build
- **INCLUDE_CHROMIUM (default=false):** whether to include the Chromium headless browser in the build
- **BUILD_TRANSLATIONS(default=false):** whether to compile the translations from the .po files available
- **SUPERSET_LOAD_EXAMPLES (default=yes):** whether to load the examples into the database upon startup,
  save some precious time on startup by `SUPERSET_LOAD_EXAMPLES=no docker compose up`
- **SUPERSET_LOG_LEVEL (default=info)**: Can be set to debug, info, warning, error, critical
  for more verbose logging

For more env vars that affect your configuration, see this
[superset_config.py](https://github.com/apache/superset/blob/master/docker/pythonpath_dev/superset_config.py)
used in the `docker compose` context to assign env vars to the superset configuration.

### Accessing the postgres database

Sometimes it's useful to access the database in the docker container directly.
You can enter a `psql` shell (the official Postgres client) by running the following command:

```bash
docker compose exec db psql -U superset
```

Also note that the database is exposed on port 5432, so you can connect to it using your favorite
Postgres client or even SQL Lab itself directly in Superset by creating a new database connection
to `localhost:5432`.

### Nuking the postgres database

At times, it's possible to end up with your development database in a bad state, it's
common while switching branches that contain migrations for instance, where the database
version stamp that `alembic` manages is no longer available after switching branch.

In that case, the easy solution is to nuke the postgres db and start fresh. Note that the full
state of the database will be gone after doing this, so be cautious.

```bash
# first stop docker-compose if it's running
docker-compose down
# delete the volume containing the database
docker volume rm superset_db_home
# restart docker-compose, which will init a fresh database and load examples
docker-compose up
```

## GitHub Codespaces (Cloud Development)

GitHub Codespaces provides a complete, pre-configured development environment in the cloud. This is ideal for:
- Quick contributions without local setup
- Consistent development environments across team members
- Working from devices that can't run Docker locally
- Safe experimentation in isolated environments

:::info
We're grateful to GitHub for providing this excellent cloud development service that makes
contributing to Apache Superset more accessible to developers worldwide.
:::

### Getting Started with Codespaces

1. **Create a Codespace**: Use this pre-configured link that sets up everything you need:

   [**Launch Superset Codespace →**](https://github.com/codespaces/new?skip_quickstart=true&machine=standardLinux32gb&repo=39464018&ref=master&devcontainer_path=.devcontainer%2Fdevcontainer.json&geo=UsWest)

   :::caution
   **Important**: You must select at least the **4 CPU / 16GB RAM** machine type (pre-selected in the link above).
   Smaller instances will not have sufficient resources to run Superset effectively.
   :::

2. **Wait for Setup**: The initial setup takes several minutes. The Codespace will:
   - Build the development container
   - Install all dependencies
   - Start all required services (PostgreSQL, Redis, etc.)
   - Initialize the database with example data

3. **Access Superset**: Once ready, check the **PORTS** tab in VS Code for port `9001`.
   Click the globe icon to open Superset in your browser.
   - Default credentials: `admin` / `admin`

### Key Features

- **Auto-reload**: Both Python and TypeScript files auto-refresh on save
- **Pre-installed Extensions**: VS Code extensions for Python, TypeScript, and database tools
- **Multiple Instances**: Run multiple Codespaces for different branches/features
- **SSH Access**: Connect via terminal using `gh cs ssh` or through the GitHub web UI
- **VS Code Integration**: Works seamlessly with VS Code desktop app

### Managing Codespaces

- **List active Codespaces**: `gh cs list`
- **SSH into a Codespace**: `gh cs ssh`
- **Stop a Codespace**: Via GitHub UI or `gh cs stop`
- **Delete a Codespace**: Via GitHub UI or `gh cs delete`

### Debugging and Logs

Since Codespaces uses `docker-compose-light.yml`, you can monitor all services:

```bash
# Stream logs from all services
docker compose -f docker-compose-light.yml logs -f

# Stream logs from a specific service
docker compose -f docker-compose-light.yml logs -f superset

# View last 100 lines and follow
docker compose -f docker-compose-light.yml logs --tail=100 -f

# List all running services
docker compose -f docker-compose-light.yml ps
```

:::tip
Codespaces automatically stop after 30 minutes of inactivity to save resources.
Your work is preserved and you can restart anytime.
:::

## 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, after installing
the prerequisites mentioned in [OS Dependencies](https://superset.apache.org/docs/installation/pypi/#os-dependencies)

```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
```

This will install the hooks in your local repository. From now on, a series of checks will
automatically run whenever you make a Git commit.

#### Running Pre-commit Manually

You can also run the pre-commit checks manually in various ways:

- **Run pre-commit on all files (same as CI):**

  To run the pre-commit checks across all files in your repository, use the following command:

  ```bash
  pre-commit run --all-files
  ```

  This is the same set of checks that will run during CI, ensuring your changes meet the project's standards.

- **Run pre-commit on a specific file:**

  If you want to check or fix a specific file, you can do so by specifying the file path:

  ```bash
  pre-commit run --files path/to/your/file.py
  ```

  This will only run the checks on the file(s) you specify.

- **Run a specific pre-commit check:**

  To run a specific check (hook) across all files or a particular file, use the following command:

  ```bash
  pre-commit run <hook_id> --all-files
  ```

  Or for a specific file:

  ```bash
  pre-commit run <hook_id> --files path/to/your/file.py
  ```

  Replace `<hook_id>` with the ID of the specific hook you want to run. You can find the list
  of available hooks in the `.pre-commit-config.yaml` file.

## Working with LLMs

### Environment Setup
Ensure Docker Compose is running before starting LLM sessions:
```bash
docker compose up
```

Validate your environment:
```bash
curl -f http://localhost:8088/health && echo "✅ Superset ready"
```

### LLM Session Best Practices
- Always validate environment setup first using the health checks above
- Use focused validation commands: `pre-commit run` (not `--all-files`)
- **Read [LLMS.md](https://github.com/apache/superset/blob/master/LLMS.md) first** - Contains comprehensive development guidelines, coding standards, and critical refactor information
- **Check platform-specific files** when available:
  - `CLAUDE.md` - For Claude/Anthropic tools
  - `CURSOR.md` - For Cursor editor
  - `GEMINI.md` - For Google Gemini tools
  - `GPT.md` - For OpenAI/ChatGPT tools
- Follow the TypeScript migration guidelines and avoid deprecated patterns listed in LLMS.md

### Key Development Commands
```bash
# Frontend development
cd superset-frontend
npm run dev          # Development server on http://localhost:9000
npm run test         # Run all tests
npm run test -- filename.test.tsx  # Run single test file
npm run lint         # Linting and type checking

# Backend validation
pre-commit run mypy  # Type checking
pytest              # Run all tests
pytest tests/unit_tests/specific_test.py  # Run single test file
pytest tests/unit_tests/  # Run all tests in directory
```

For detailed development context, environment setup, and coding guidelines, see [LLMS.md](https://github.com/apache/superset/blob/master/LLMS.md).

## 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 is 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.

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 on how to build the front-end assets.
superset run -p 8088 --with-threads --reload --debugger --debug
```

Or you can install it 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
./scripts/uv-pip-compile.sh
```

When upgrading the version number of a single package, you should run `./scripts/uv-pip-compile.sh` with the `-P` flag:

```bash
./scripts/uv-pip-compile.sh -P some-package-to-upgrade
```

To bring all dependencies up to date as per the restrictions defined in `setup.py` and `requirements/*.in`, run `./scripts/uv-pip-compile.sh --upgrade`

```bash
./scripts/uv-pip-compile.sh --upgrade
```

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
```

### 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 20
- `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

in case 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` environment 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 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 an 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 the 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.

## Linting

See [how tos](./howtos#linting)

## GitHub Actions and `act`

:::tip
`act` compatibility of Superset's GHAs is not fully tested. Running `act` locally may or may not
work for different actions, and may require fine tuning and local secret-handling.
For those more intricate GHAs that are tricky to run locally, we recommend iterating
directly on GHA's infrastructure, by pushing directly on a branch and monitoring GHA logs.
For more targeted iteration, see the `gh workflow run --ref {BRANCH}` subcommand of the GitHub CLI.
:::

For automation and CI/CD, Superset makes extensive use of GitHub Actions (GHA). You
can find all of the workflows and other assets under the `.github/` folder. This includes:

- running the backend unit test suites (`tests/`)
- running the frontend test suites (`superset-frontend/src/**.*.test.*`)
- running our Playwright end-to-end tests (`superset-frontend/playwright/`) and legacy Cypress tests (`superset-frontend/cypress-base/`)
- linting the codebase, including all Python, Typescript and Javascript, yaml and beyond
- checking for all sorts of other rules conventions

When you open a pull request (PR), the appropriate GitHub Actions (GHA) workflows will
automatically run depending on the changes in your branch. It's perfectly reasonable
(and required!) to rely on this automation. However, the downside is that it's mostly an
all-or-nothing approach and doesn't provide much control to target specific tests or
iterate quickly.

At times, it may be more convenient to run GHA workflows locally. For that purpose
we use [act](https://github.com/nektos/act), a tool that allows you to run GitHub Actions (GHA)
workflows locally. It simulates the GitHub Actions environment, enabling developers to
test and debug workflows on their local machines before pushing changes to the repository. More
on how to use it in the next section.

:::note
In both GHA and `act`, we can run a more complex matrix for our tests, executing against different
database engines (PostgreSQL, MySQL, SQLite) and different versions of Python.
This enables us to ensure compatibility and stability across various environments.
:::

### Using `act`

First, install `act` -> https://nektosact.com/

To list the workflows, simply:

```bash
act --list
```

To run a specific workflow:

```bash
act pull_request --job {workflow_name} --secret GITHUB_TOKEN=$GITHUB_TOKEN --container-architecture linux/amd64
```

In the example above, notice that:

- we target a specific workflow, using `--job`
- we pass a secret using `--secret`, as many jobs require read access (public) to the repo
- we simulate a `pull_request` event by specifying it as the first arg,
  similarly, we could simulate a `push` event or something else
- we specify `--container-architecture`, which tends to emulate GHA more reliably

:::note
`act` is a rich tool that offers all sorts of features, allowing you to simulate different
events (pull_request, push, ...), semantics around passing secrets where required and much
more. For more information, refer to [act's documentation](https://nektosact.com/)
:::

:::note
Some jobs require secrets to interact with external systems and accounts that you may
not have in your possession. In those cases you may have to rely on remote CI or parameterize the
job further to target a different environment/sandbox or your own alongside the related
secrets.
:::

---

## Testing

### Python Testing

#### Unit Tests

For unit tests located in `tests/unit_tests/`, it's usually easy to simply run the script locally using:

```bash
pytest tests/unit_tests/*
```

#### Integration Tests

For more complex pytest-defined integration tests (not to be confused with our end-to-end Cypress tests), many tests will require having a working test environment. Some tests require a database, Celery, and potentially other services or libraries installed.

### Running Tests with `act`

To run integration tests locally using `act`, ensure you have followed the setup instructions from the [GitHub Actions and `act`](#github-actions-and-act) section. You can run specific workflows or jobs that include integration tests. For example:

```bash
act --job test-python-38 --secret GITHUB_TOKEN=$GITHUB_TOKEN --event pull_request --container-architecture linux/amd64
```

#### Running locally using a test script

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` 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
```

#### Known Issues and Workarounds

**Jest Test Hanging (MessageChannel Issue)**

If Jest tests hang with "Jest did not exit one second after the test run has completed", this is likely due to the MessageChannel issue from rc-overflow (Ant Design v5 components).

**Root Cause**: `rc-overflow@1.4.1` creates MessageChannel handles for responsive overflow detection that remain open after test completion.

**Current Workaround**: MessageChannel is mocked as undefined in `spec/helpers/jsDomWithFetchAPI.ts`, forcing rc-overflow to use requestAnimationFrame fallback.

**To verify if still needed**: Remove the MessageChannel mocking lines and run `npm test -- --shard=4/8`. If tests hang, the workaround is still required.

**Future removal conditions**: This workaround can be removed when:
- rc-overflow updates to properly clean up MessagePorts in test environments
- Jest updates to handle MessageChannel/MessagePort cleanup better
- Ant Design switches away from rc-overflow
- We switch away from Ant Design v5

**See**: [PR #34871](https://github.com/apache/superset/pull/34871) for full technical details.

### 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 --build
```

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 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 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.

## 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 theme 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:

   ```log
   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:

   ```log
   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
   ```