CONTRIBUTING.md

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# Contributing

Contributions are welcome and are greatly appreciated! Every
little bit helps, and credit will always be given.

## Table of Contents

- [Types of Contributions](#types-of-contributions)
  - [Report Bugs](#report-bugs)
  - [Submit Ideas or Feature Requests](#submit-ideas-or-feature-requests)
  - [Ask Questions](#ask-questions)
  - [Fix Bugs](#fix-bugs)
  - [Implement Features](#implement-features)
  - [Improve Documentation](#improve-documentation)
  - [Add Translations](#add-translations)
- [Pull Request Guidelines](#pull-request-guidelines)
  - [Protocol](#protocol)
- [Managing Issues and PRs](#managing-issues-and-prs)
- [Setup Local Environment for Development](#setup-local-environment-for-development)
  - [Documentation](#documentation)
  - [Flask server](#flask-server)
  - [Frontend assets](#frontend-assets)
- [Testing](#testing)
  - [JavaScript testing](#javascript-testing)
  - [Integration testing](#integration-testing)
  - [Linting](#linting)
- [Translating](#translating)
  - [Enabling language selection](#enabling-language-selection)
  - [Extracting new strings for translation](#extracting-new-strings-for-translation)
  - [Creating a new language dictionary](#creating-a-new-language-dictionary)
- [Tips](#tips)
  - [Adding a new datasource](#adding-a-new-datasource)
  - [Creating a new visualization type](#creating-a-new-visualization-type)
  - [Adding a DB migration](#adding-a-db-migration)
  - [Merging DB migrations](#merging-db-migrations)
  - [SQL Lab Async](#sql-lab-async)

## 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/).

### Submit Ideas or Feature Requests

The best way is to file an issue 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 contributions are welcome :)

For large features or major changes to codebase, please create **Superset Improvement Proposal (SIP)**. See template from [SIP-0](https://github.com/apache/incubator-superset/issues/5602)

### Fix Bugs

Look through the GitHub issues. Issues tagged with `#bug` is
open to whoever wants to implement it.

### 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 in to 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.

## 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 you’re only fixing a small bug, it’s fine to submit a pull request right away but we highly recommend to file an issue detailing what you’re fixing. This is helpful in case we don’t 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 requires 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.

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.
- 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.
- **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 `setup.py` denoting any specific restrictions and in `requirements.txt` pinned to a specific version which ensures that the application build is deterministic.
  - For 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. Doc string are often sufficient, make sure to follow the sphinx compatible standards.
- **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.

#### 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 that does not provide new features and is also not a bug fix nor refactor, such as adjust padding, refine UI style. | Implementation of improvement that does not provide new features and is also not a bug fix nor refactor, such as adjust padding, refine UI style. |
| `#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`.

## Setup Local Environment for Development

First, [fork the repository on GitHub](https://help.github.com/articles/about-forks/), then clone it. 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/incubator-superset.git
cd incubator-superset
```

### Documentation

The latest documentation and tutorial are available at https://superset.incubator.apache.org/.

Contributing to the official documentation is relatively easy, once you've setup
your environment and done an edit end-to-end. The docs can be found in the
`docs/` subdirectory of the repository, and are written in the
[reStructuredText format](https://en.wikipedia.org/wiki/ReStructuredText) (.rst).
If you've written Markdown before, you'll find the reStructuredText format familiar.

Superset uses [Sphinx](http://www.sphinx-doc.org/en/1.5.1/) to convert the rst files
in `docs/` to the final HTML output users see.

Finally, to make changes to the rst files and build the docs using Sphinx,
you'll need to install a handful of dependencies from the repo you cloned:

```bash
pip install -r docs/requirements.txt
```

To get the feel for how to edit and build the docs, let's edit a file, build
the docs and see our changes in action. First, you'll want to
[create a new branch](https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging)
to work on your changes:

```bash
git checkout -b changes-to-docs
```

Now, go ahead and edit one of the files under `docs/`, say `docs/tutorial.rst` - change
it however you want. Check out the
[ReStructuredText Primer](http://docutils.sourceforge.net/docs/user/rst/quickstart.html)
for a reference on the formatting of the rst files.

Once you've made your changes, run this command to convert the docs into HTML:

```bash
make html
```

You'll see a lot of output as Sphinx handles the conversion. After it's done, the
HTML Sphinx generated should be in `docs/_build/html`. Navigate there
and start a simple web server so we can check out the docs in a browser:

```bash
cd docs/_build/html
python -m http.server # Python2 users should use SimpleHTTPServer

```

This will start a small Python web server listening on port 8000. Point your
browser to http://localhost:8000, find the file
you edited earlier, and check out your changes!

If you've made a change you'd like to contribute to the actual docs, just commit
your code, push your new branch to Github:

```bash
git add docs/tutorial.rst
git commit -m 'Awesome new change to tutorial'
git push origin changes-to-docs
```

Then, [open a pull request](https://help.github.com/articles/about-pull-requests/).

#### Images

If you're adding new images to the documentation, you'll notice that the images
referenced in the rst, e.g.

    .. image:: _static/img/tutorial/tutorial_01_sources_database.png

aren't actually stored in that directory. Instead, you should add and commit
images (and any other static assets) to the `superset/assets/images` directory.
When the docs are deployed to https://superset.incubator.apache.org/, images
are copied from there to the `_static/img` directory, just like they're referenced
in the docs.

For example, the image referenced above actually lives in `superset/assets/images/tutorial`. Since the image is moved during the documentation build process, the docs reference the image in `_static/img/tutorial` instead.

#### API documentation

Generate the API documentation with:

```bash
pip install -r docs/requirements.txt
python setup.py build_sphinx
```

### Flask server

#### OS Dependencies

Make sure your machine meets the [OS dependencies](https://superset.incubator.apache.org/installation.html#os-dependencies) before following these steps.

Developers should use a virtualenv.

```
pip install virtualenv
```

Then proceed with:

```bash
# Create a virtual environemnt and activate it (recommended)
virtualenv -p python3 venv # setup a python3.6 virtualenv
source venv/bin/activate

# Install external dependencies
pip install -r requirements.txt
pip install -r requirements-dev.txt

# Install Superset in editable (development) mode
pip install -e .

# Create an admin user in your metadata database
flask fab create-admin

# Initialize the database
superset db upgrade

# Create default roles and permissions
superset init

# Load some data to play with
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.
FLASK_ENV=development superset run -p 8088 --with-threads --reload --debugger
```

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:
`FLASK_ENV=development superset run -p 8088 --reload --debugger`

#### 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
FLASK_ENV=development gunicorn superset: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

Frontend assets (JavaScript, CSS, and images) must be compiled in order to properly display the web UI. The `superset/assets` directory contains all NPM-managed front end assets. Note that 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.

#### nvm and node

First, be sure you are using recent versions of NodeJS and npm. Using [nvm](https://github.com/creationix/nvm) to manage them is recommended. Check the docs at the link to be sure, but at the time of writing the following would install nvm and node:

```bash
curl -o- https://raw.githubusercontent.com/creationix/nvm/v0.34.0/install.sh | bash
nvm install node
```

#### Prerequisite

#### Installing Dependencies

Install third-party dependencies listed in `package.json`:

```bash
# From the root of the repository
cd superset/assets

# Install dependencies from `package-lock.json`
npm ci
```

#### Building

You can run the Webpack dev server (in a separate terminal from Flask), which runs on port 9000 and proxies non-asset requests to the Flask server on port 8088. After pointing your browser to `http://localhost:9000`, updates to asset sources will be reflected in-browser without a refresh.

```bash
# Run the dev server
npm run dev-server

# Run the dev server on a non-default port
npm run dev-server -- --port=9001

# Run the dev server proxying to a Flask server on a non-default port
npm run dev-server -- --supersetPort=8081
```

Alternatively you can use one of the following commands.

```bash
# Start a watcher that recompiles your assets as you modify them (but have to manually reload your browser to see changes.)
npm run dev

# Compile the Javascript and CSS in production/optimized mode for official releases
npm run prod
```

If you run this service from somewhere other than your local machine, you may need to add hostname value to webpack.config.js at .devServer.public specifying the endpoint at which you will access the app. For example: myhost:9001. For convenience you may want to install webpack, webpack-cli and webpack-dev-server globally so that you can run them directly:

```bash
npm install --global webpack webpack-cli webpack-dev-server
```

#### Updating NPM packages

Use npm in the prescribed way, making sure that
`superset/assets/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:
```
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/assets/src/featureFlags.ts`. For example,
```
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 }`.

## 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-dev.txt
pre-commit install
```

## Linting

Lint the project with:

```bash
# for python
tox -e flake8

# for javascript
cd superset/assets
npm ci
npm run lint
```

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/editor_integration.html).


## 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 py36
```

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.

#### Typing

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 using Sphinx documentation.

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)
```


### JavaScript Testing

We use [Jest](https://jestjs.io/) and [Enzyme](https://airbnb.io/enzyme/) to test Javascript. Tests can be run with:

```bash
cd superset/assets
npm run test
```

### 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.superset_test_config
superset db upgrade
superset init
superset load_test_users
superset load_examples
superset run --port 8081
```

Run Cypress tests:

```bash
cd superset/assets
npm run build
npm run install-cypress
npm run cypress run

# run tests from a specific file
npm run cypress run -- --spec cypress/integration/explore/link.test.js

# run specific file with video capture
npm run cypress run -- --spec cypress/integration/dashboard/index.test.js --config video=true
```

See [`superset/assets/cypress_build.sh`](https://github.com/apache/incubator-superset/blob/master/superset/assets/cypress_build.sh).

## Translating

We use [Babel](http://babel.pocoo.org/en/latest/) 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 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'},
}
```

### Extracting new strings for translation

```bash
flask fab babel-extract --target superset/translations --output superset/translations/messages.pot --config superset/translations/babel.cfg -k _ -k __ -k t -k tn -k tct
```

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).

For the translations to take effect:

```bash
# 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.
npm install -g po2json
flask fab babel-compile --target superset/translations
# Convert the en PO file into a JSON file
po2json -d superset -f jed1.x superset/translations/en/LC_MESSAGES/messages.po superset/translations/en/LC_MESSAGES/messages.json
```

If you get errors running `po2json`, you might be running the Ubuntu package with the same
name, rather than the NodeJS 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.

### 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, [extract strings for the new language](#extracting-new-strings-for-translation).

## 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.

### Creating a new visualization type

Here's an example as a Github PR with comments that describe what the
different sections of the code do:
https://github.com/apache/incubator-superset/pull/3013

### 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/incubator-superset/commit/6c25f549384d7c2fc288451222e50493a7b14104)

1. Generate the migration file

    ```bash
    superset db migrate -m 'add_metadata_column_to_annotation_model.py'
    ```

    This will generate a file in `migrations/version/{SHA}_this_will_be_in_the_migration_filename.py`.

    [Example commit](https://github.com/apache/incubator-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/incubator-superset/pull/5745/commits/6220966e2a0a0cf3e6d87925491f8920fe8a3458)

### Merging DB migrations

When two DB migrations collide, you'll get an error message like this one:

```
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.

1. Create a new merge migration

    ```bash
    superset db merge {HASH1} {HASH2}
    ```

1. Upgrade the DB to the new checkpoint

    ```bash
    superset db upgrade
    ```

### 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 werkzeug.contrib.cache import FileSystemCache
    RESULTS_BACKEND = FileSystemCache('/tmp/sqllab')
    ```

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