---
name: Configuring Superset
menu: Installation and Configuration
route: /docs/installation/configuring-superset
index: 3
version: 1
---

## Configuring Superset

### Configuration

To configure your application, you need to create a file `superset_config.py` and add it to your
`PYTHONPATH`. Here are some of the parameters you can set in that file:

```
# Superset specific config
ROW_LIMIT = 5000

SUPERSET_WEBSERVER_PORT = 8088

# Flask App Builder configuration
# Your App secret key
SECRET_KEY = '\2\1thisismyscretkey\1\2\e\y\y\h'

# The SQLAlchemy connection string to your database backend
# This connection defines the path to the database that stores your
# superset metadata (slices, connections, tables, dashboards, ...).
# Note that the connection information to connect to the datasources
# you want to explore are managed directly in the web UI
SQLALCHEMY_DATABASE_URI = 'sqlite:////path/to/superset.db'

# Flask-WTF flag for CSRF
WTF_CSRF_ENABLED = True
# Add endpoints that need to be exempt from CSRF protection
WTF_CSRF_EXEMPT_LIST = []
# A CSRF token that expires in 1 year
WTF_CSRF_TIME_LIMIT = 60 * 60 * 24 * 365

# Set this API key to enable Mapbox visualizations
MAPBOX_API_KEY = ''
```

All the parameters and default values defined in
[https://github.com/apache/incubator-superset/blob/master/superset/config.py](https://github.com/apache/incubator-superset/blob/master/superset/config.py)
can be altered in your local `superset_config.py`. Administrators will want to read through the file
to understand what can be configured locally as well as the default values in place.

Since `superset_config.py` acts as a Flask configuration module, it can be used to alter the
settings Flask itself, as well as Flask extensions like `flask-wtf`, `flask-cache`, `flask-migrate`,
and `flask-appbuilder`. Flask App Builder, the web framework used by Superset, offers many
configuration settings. Please consult the
[Flask App Builder Documentation](https://flask-appbuilder.readthedocs.org/en/latest/config.html)
for more information on how to configure it.

Make sure to change:

- `SQLALCHEMY_DATABASE_URI`: by default it is stored at ~/.superset/superset.db
- `SECRET_KEY`: to a long random string

If you need to exempt endpoints from CSRF (e.g. if you are running a custom auth postback endpoint),
you can add the endpoints to `WTF_CSRF_EXEMPT_LIST`:

```
WTF_CSRF_EXEMPT_LIST = [‘’]
```

### Flask AppBuilder Permissions

By default, every time the Flask-AppBuilder (FAB) app is initialized the permissions and views are
added automatically to the backend and associated with the ‘Admin’ role. The issue, however, is when
you are running multiple concurrent workers this creates a lot of contention and race conditions
when defining permissions and views.

To alleviate this issue, the automatic updating of permissions can be disabled by setting
`FAB_UPDATE_PERMS = False` (defaults to True).

In a production environment initialization could take on the following form:

```
superset init gunicorn -w 10 … superset:app
```

### Running on a WSGI HTTP Server

While you can run Superset on NGINX or Apache, we recommend using Gunicorn in async mode. This
enables impressive concurrency even and is fairly easy to install and configure. Please refer to the
documentation of your preferred technology to set up this Flask WSGI application in a way that works
well in your environment. Here’s an async setup known to work well in production:

```
      -w 10 \
      -k gevent \
      --timeout 120 \
      -b  0.0.0.0:6666 \
      --limit-request-line 0 \
      --limit-request-field_size 0 \
      --statsd-host localhost:8125 \
      "superset.app:create_app()"
```

Refer to the [Gunicorn documentation](https://docs.gunicorn.org/en/stable/design.html) for more
information. _Note that the development web server (`superset run` or `flask run`) is not intended
for production use._

If you're not using Gunicorn, you may want to disable the use of `flask-compress` by setting
`COMPRESS_REGISTER = False` in your `superset_config.py`.

### Configuration Behind a Load Balancer

If you are running superset behind a load balancer or reverse proxy (e.g. NGINX or ELB on AWS), you
may need to utilize a healthcheck endpoint so that your load balancer knows if your superset
instance is running. This is provided at `/health` which will return a 200 response containing “OK”
if the the webserver is running.

If the load balancer is inserting `X-Forwarded-For/X-Forwarded-Proto` headers, you should set
`ENABLE_PROXY_FIX = True` in the superset config file (`superset_config.py`) to extract and use the
headers.

In case the reverse proxy is used for providing SSL encryption, an explicit definition of the
`X-Forwarded-Proto` may be required. For the Apache webserver this can be set as follows:

```
RequestHeader set X-Forwarded-Proto "https"
```

### Custom OAuth2 Configuration

Beyond FAB supported providers (Github, Twitter, LinkedIn, Google, Azure, etc), its easy to connect
Superset with other OAuth2 Authorization Server implementations that support “code” authorization.

First, configure authorization in Superset `superset_config.py`.

```python
AUTH_TYPE = AUTH_OAUTH
OAUTH_PROVIDERS = [
    {   'name':'egaSSO',
        'token_key':'access_token', # Name of the token in the response of access_token_url
        'icon':'fa-address-card',   # Icon for the provider
        'remote_app': {
            'consumer_key':'myClientId',  # Client Id (Identify Superset application)
            'consumer_secret':'MySecret', # Secret for this Client Id (Identify Superset application)
            'request_token_params':{
                'scope': 'read'               # Scope for the Authorization
            },
            'access_token_method':'POST',    # HTTP Method to call access_token_url
            'access_token_params':{        # Additional parameters for calls to access_token_url
                'client_id':'myClientId'
            },
            'access_token_headers':{    # Additional headers for calls to access_token_url
                'Authorization': 'Basic Base64EncodedClientIdAndSecret'
            },
            'base_url':'https://myAuthorizationServer/oauth2AuthorizationServer/',
            'access_token_url':'https://myAuthorizationServer/oauth2AuthorizationServer/token',
            'authorize_url':'https://myAuthorizationServer/oauth2AuthorizationServer/authorize'
        }
    }
]

# Will allow user self registration, allowing to create Flask users from Authorized User
AUTH_USER_REGISTRATION = True

# The default user self registration role
AUTH_USER_REGISTRATION_ROLE = "Public"
```

Then, create a `CustomSsoSecurityManager` that extends `SupersetSecurityManager` and overrides
`oauth_user_info`:

```python
from superset.security import SupersetSecurityManager

class CustomSsoSecurityManager(SupersetSecurityManager):

    def oauth_user_info(self, provider, response=None):
        logging.debug("Oauth2 provider: {0}.".format(provider))
        if provider == 'egaSSO':
            # As example, this line request a GET to base_url + '/' + userDetails with Bearer  Authentication,
    # and expects that authorization server checks the token, and response with user details
            me = self.appbuilder.sm.oauth_remotes[provider].get('userDetails').data
            logging.debug("user_data: {0}".format(me))
            return { 'name' : me['name'], 'email' : me['email'], 'id' : me['user_name'], 'username' : me['user_name'], 'first_name':'', 'last_name':''}
    ...
```

This file must be located at the same directory than `superset_config.py` with the name
`custom_sso_security_manager.py`. Finally, add the following 2 lines to `superset_config.py`:

```
from custom_sso_security_manager import CustomSsoSecurityManager
CUSTOM_SECURITY_MANAGER = CustomSsoSecurityManager
```

### Feature Flags

To support a diverse set of users, Superset has some features that are not enabled by default. For
example, some users have stronger security restrictions, while some others may not. So Superset
allow users to enable or disable some features by config. For feature owners, you can add optional
functionalities in Superset, but will be only affected by a subset of users.

You can enable or disable features with flag from `superset_config.py`:

```python
DEFAULT_FEATURE_FLAGS = {
    'CLIENT_CACHE': False,
    'ENABLE_EXPLORE_JSON_CSRF_PROTECTION': False,
    'PRESTO_EXPAND_DATA': False,
}
```

Here is a list of flags and descriptions:

- `ENABLE_EXPLORE_JSON_CSRF_PROTECTION`: For some security concerns, you may need to enforce CSRF
  protection on all query request to the `explore_json` endpoint. When
  `ENABLE_EXPLORE_JSON_CSRF_PROTECTION` is set to true, your users cannot make GET request to
  `explore_json`. The default value for this feature is `False` and `explore_json` will accept both
  GET and POST request. See [PR 7935](https://github.com/apache/incubator-superset/pull/7935) for
  more details.

- `PRESTO_EXPAND_DATA`: When this feature is enabled, nested types in Presto will be expanded into
  extra columns and / or arrays. This is experimental, and doesn’t work with all nested types.

### SIP 15

[Superset Improvement Proposal 15](https://github.com/apache/incubator-superset/issues/6360) aims to
ensure that time intervals are handled in a consistent and transparent manner for both the Druid and
SQLAlchemy connectors.

Prior to SIP-15 SQLAlchemy used inclusive endpoints however these may behave like exclusive for
string columns (due to lexicographical ordering) if no formatting was defined and the column
formatting did not conform to an ISO 8601 date-time (refer to the SIP for details).

To remedy this rather than having to define the date/time format for every non-IS0 8601 date-time
column, once can define a default column mapping on a per database level via the `extra` parameter:

```
{
    "python_date_format_by_column_name": {
        "ds": "%Y-%m-%d"
    }
}
```

**New Deployments**

All new deployments should enable SIP-15 by setting this value in `superset_config.py`:

```
SIP_15_ENABLED = True

```

**Existing Deployments**

Given that it is not apparent whether the chart creator was aware of the time range inconsistencies
(and adjusted the endpoints accordingly) changing the behavior of all charts is overly aggressive.
Instead SIP-15 proivides a soft transistion allowing producers (chart owners) to see the impact of
the proposed change and adjust their charts accordingly.

Prior to enabling SIP-15, existing deployments should communicate to their users the impact of the
change and define a grace period end date (exclusive of course) after which all charts will conform
to the [start, end) interval.

```python
from dateime import date

SIP_15_ENABLED = True
SIP_15_GRACE_PERIOD_END = date(<YYYY>, <MM>, <DD>)
```

To aid with transparency the current endpoint behavior is explicitly called out in the chart time
range (post SIP-15 this will be [start, end) for all connectors and databases). One can override the
defaults on a per database level via the `extra` parameter.

```python
{
    "time_range_endpoints": ["inclusive", "inclusive"]
}
```

Note in a future release the interim SIP-15 logic will be removed (including the
`time_grain_endpoints` form-data field) via a code change and Alembic migration.
