Datasette plugin that exposes the custom SQL functions from sqlite-fts4.
Interactive demo. Read Exploring search relevance algorithms with SQLite for further details on this project.
pip install datasette-sqlite-fts4
If you are deploying a database using datasette publish you can include this plugin using the --install option:
datasette publish now mydb.db --install=datasette-sqlite-fts4
Datasette plugin that authenticates users based on existing domain cookies.
This plugin allows you to build custom authentication for Datasette when you are hosting a Datasette instance on the same domain as another, authenticated website.
Consider a website on www.example.com which supports user authentication.
You could run Datasette on data.example.com in a way that lets it see cookies that were set for the .example.com domain.
Using this plugin, you could build an API endpoint at www.example.com/user-for-cookies which returns a JSON object representing the currently signed-in user, based on their cookies.
The plugin running on data.example.com will then make the actor available to the rest of Datasette based on the response from that API.
Read about Datasette's authentication and permissions system for more on how actors and permissions work.
This plugin requires some configuration in the Datasette metadata.json file.
The following configuration options are supported:
api_url: this is the API endpoint that Datasette should call with the user's cookies in order to identify the logged in user.cookies: optional. A list of cookie names that should be passed through to the API endpoint - if left blank, the default is to send all cookies.ttl: optional. By default Datasette will make a request to the API endpoint for every HTTP request recieved by Datasette itself. A ttl value of 5 will cause Datasette to cache the actor associated with the user's cookies for 5 seconds, reducing that API traffic.headers: an optional list of other headers to forward to the API endpoint as query string parameters.Here is an example that uses all four of these settings:
{
""plugins"": {
""datasette-auth-existing-cookies"": {
""api_url"": ""http://www.example.com/user-from-cookies"",
""cookies"": [""sessionid""],
""headers"": [""host""],
""ttl"": 10
}
}
}With this configuration any hit to a Datasette hosted at data.example.com will result in the following request being made to the http://www.example.com/user-from-cookies API endpoint:
GET http://www.example.com/user-from-cookies?host=data.example.com
Cookie: sessionid=abc123
That API is expected to return a JSON object representing the current user:
{
""id"": 1,
""name"": ""Barry""
}Since ttl is set to 10 that actor will be cached for ten seconds against that exact combination of cookies and headers. When that cache expires another hit will be made to the API.
When deciding on a TTL value, take into account that users who lose access to the core site - maybe because their session expires, or their account is disabled - will still be able to access the Datasette instance until that cache expires.
Datasette plugin providing a UI for writing to a database
Install this plugin in the same environment as Datasette.
$ pip install datasette-write
Having installed the plugin, visit /-/write on your Datasette instance to submit SQL queries that will be executed against a write connection to the specified database.
By default only the root user can access the page - so you'll need to run Datasette with the --root option and click on the link shown in the terminal to sign in and access the page.
The datasette-write permission governs access. You can use permission plugins such as datasette-permissions-sql to grant additional access to the write interface.
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-write
python3 -mvenv venv
source venv/bin/activate
Or if you are using pipenv:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest
Add GeoJSON as an output option for datasette queries.
Install this plugin in the same environment as Datasette.
datasette install datasette-geojson
To render GeoJSON, add a .geojson extension to any query URL that includes a geometry column. That column should be a valid GeoJSON geometry.
For example, you might use geojson-to-sqlite or shapefile-to-sqlite to load neighborhood boundaries into a SQLite database.
wget -O neighborhoods.geojson https://opendata.arcgis.com/datasets/3525b0ee6e6b427f9aab5d0a1d0a1a28_0.geojson
geojson-to-sqlite boston.db neighborhoods neighborhoods.geojson --spatial-index # create a spatial index
datasette serve boston.db --load-extension spatialiteIf you're using Spatialite, the geometry column will be in a binary format. If not, make sure the geometry column is a well-formed GeoJSON geometry. If you used geojson-to-sqlite or shapefile-to-sqlite, you should be all set.
Run this query in Datasette and you'll see a link to download GeoJSON:
select rowid, OBJECTID, Name, Acres, Neighborhood_ID, SqMiles, ShapeSTArea, ShapeSTLength, geometry from neighborhoods order by rowid limit 101
Note that the geometry column needs to be explicitly named geometry or you won't get the option to export GeoJSON. If you want to use a different column, rename it with AS: SELECT other AS geometry FROM my_table.
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
cd datasette-geojson
python3 -mvenv venv
source venv/bin/activate
Or if you are using pipenv:
pipenv shell
Now install the dependencies and tests:
pip install -e '.[test]'
To run the tests:
pytest