datasette/docs/plugins.rst

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.. _plugins:
Plugins
=======
Datasette's plugin system allows additional features to be implemented as Python
code (or front-end JavaScript) which can be wrapped up in a separate Python
package. The underlying mechanism uses `pluggy <https://pluggy.readthedocs.io/>`_.
See the `Datasette plugins directory <https://datasette.io/plugins>`__ for a list of existing plugins, or take a look at the
`datasette-plugin <https://github.com/topics/datasette-plugin>`__ topic on GitHub.
Things you can do with plugins include:
* Add visualizations to Datasette, for example
`datasette-cluster-map <https://github.com/simonw/datasette-cluster-map>`__ and
`datasette-vega <https://github.com/simonw/datasette-vega>`__.
* Make new custom SQL functions available for use within Datasette, for example
`datasette-haversine <https://github.com/simonw/datasette-haversine>`__ and
`datasette-jellyfish <https://github.com/simonw/datasette-jellyfish>`__.
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* Define custom output formats with custom extensions, for example `datasette-atom <https://github.com/simonw/datasette-atom>`__ and
`datasette-ics <https://github.com/simonw/datasette-ics>`__.
* Add template functions that can be called within your Jinja custom templates,
for example `datasette-render-markdown <https://github.com/simonw/datasette-render-markdown#markdown-in-templates>`__.
* Customize how database values are rendered in the Datasette interface, for example
`datasette-render-binary <https://github.com/simonw/datasette-render-binary>`__ and
`datasette-pretty-json <https://github.com/simonw/datasette-pretty-json>`__.
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* Customize how Datasette's authentication and permissions systems work, for example `datasette-auth-passwords <https://github.com/simonw/datasette-auth-passwords>`__ and
`datasette-permissions-sql <https://github.com/simonw/datasette-permissions-sql>`__.
.. _plugins_installing:
Installing plugins
------------------
If a plugin has been packaged for distribution using setuptools you can use the plugin by installing it alongside Datasette in the same virtual environment or Docker container.
You can install plugins using the ``datasette install`` command::
datasette install datasette-vega
You can uninstall plugins with ``datasette uninstall``::
datasette uninstall datasette-vega
You can upgrade plugins with ``datasette install --upgrade`` or ``datasette install -U``::
datasette install -U datasette-vega
This command can also be used to upgrade Datasette itself to the latest released version::
datasette install -U datasette
You can install multiple plugins at once by listing them as lines in a ``requirements.txt`` file like this::
datasette-vega
datasette-cluster-map
Then pass that file to ``datasette install -r``::
datasette install -r requirements.txt
The ``install`` and ``uninstall`` commands are thin wrappers around ``pip install`` and ``pip uninstall``, which ensure that they run ``pip`` in the same virtual environment as Datasette itself.
One-off plugins using --plugins-dir
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You can also define one-off per-project plugins by saving them as ``plugin_name.py`` functions in a ``plugins/`` folder and then passing that folder to ``datasette`` using the ``--plugins-dir`` option::
datasette mydb.db --plugins-dir=plugins/
Deploying plugins using datasette publish
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
The ``datasette publish`` and ``datasette package`` commands both take an optional ``--install`` argument. You can use this one or more times to tell Datasette to ``pip install`` specific plugins as part of the process::
datasette publish cloudrun mydb.db --install=datasette-vega
You can use the name of a package on PyPI or any of the other valid arguments to ``pip install`` such as a URL to a ``.zip`` file::
datasette publish cloudrun mydb.db \
--install=https://url-to-my-package.zip
.. _plugins_datasette_load_plugins:
Controlling which plugins are loaded
------------------------------------
Datasette defaults to loading every plugin that is installed in the same virtual environment as Datasette itself.
You can set the ``DATASETTE_LOAD_PLUGINS`` environment variable to a comma-separated list of plugin names to load a controlled subset of plugins instead.
For example, to load just the ``datasette-vega`` and ``datasette-cluster-map`` plugins, set ``DATASETTE_LOAD_PLUGINS`` to ``datasette-vega,datasette-cluster-map``:
.. code-block:: bash
export DATASETTE_LOAD_PLUGINS='datasette-vega,datasette-cluster-map'
datasette mydb.db
Or:
.. code-block:: bash
DATASETTE_LOAD_PLUGINS='datasette-vega,datasette-cluster-map' \
datasette mydb.db
To disable the loading of all additional plugins, set ``DATASETTE_LOAD_PLUGINS`` to an empty string:
.. code-block:: bash
export DATASETTE_LOAD_PLUGINS=''
datasette mydb.db
A quick way to test this setting is to use it with the ``datasette plugins`` command:
.. code-block:: bash
DATASETTE_LOAD_PLUGINS='datasette-vega' datasette plugins
This should output the following:
.. code-block:: json
[
{
"name": "datasette-vega",
"static": true,
"templates": false,
"version": "0.6.2",
"hooks": [
"extra_css_urls",
"extra_js_urls"
]
}
]
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.. _plugins_installed:
Seeing what plugins are installed
---------------------------------
You can see a list of installed plugins by navigating to the ``/-/plugins`` page of your Datasette instance - for example: https://fivethirtyeight.datasettes.com/-/plugins
You can also use the ``datasette plugins`` command::
datasette plugins
Which outputs:
.. code-block:: json
[
{
"name": "datasette_json_html",
"static": false,
"templates": false,
"version": "0.4.0"
}
]
.. [[[cog
from datasette import cli
from click.testing import CliRunner
import textwrap, json
cog.out("\n")
result = CliRunner().invoke(cli.cli, ["plugins", "--all"])
# cog.out() with text containing newlines was unindenting for some reason
cog.outl("If you run ``datasette plugins --all`` it will include default plugins that ship as part of Datasette:\n")
cog.outl(".. code-block:: json\n")
plugins = [p for p in json.loads(result.output) if p["name"].startswith("datasette.")]
indented = textwrap.indent(json.dumps(plugins, indent=4), " ")
for line in indented.split("\n"):
cog.outl(line)
cog.out("\n\n")
.. ]]]
If you run ``datasette plugins --all`` it will include default plugins that ship as part of Datasette:
.. code-block:: json
[
{
"name": "datasette.actor_auth_cookie",
"static": false,
"templates": false,
"version": null,
"hooks": [
"actor_from_request"
]
},
{
"name": "datasette.blob_renderer",
"static": false,
"templates": false,
"version": null,
"hooks": [
"register_output_renderer"
]
},
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{
"name": "datasette.default_actions",
"static": false,
"templates": false,
"version": null,
"hooks": [
"register_actions"
]
},
{
"name": "datasette.default_magic_parameters",
"static": false,
"templates": false,
"version": null,
"hooks": [
"register_magic_parameters"
]
},
{
"name": "datasette.default_menu_links",
"static": false,
"templates": false,
"version": null,
"hooks": [
"menu_links"
]
},
{
"name": "datasette.default_permissions",
"static": false,
"templates": false,
"version": null,
"hooks": [
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"canned_queries",
"permission_resources_sql",
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"skip_csrf"
]
},
register_token_handler() plugin hook for custom API token backends (#2650) Closes #2649 * Add register_token_handler plugin hook for pluggable token backends Adds a new register_token_handler hook that allows plugins to provide custom token creation and verification backends. This enables plugins like datasette-oauth to issue tokens without depending on specific backend plugins like datasette-auth-tokens. Key changes: - New datasette/tokens.py with TokenHandler base class and SignedTokenHandler (the default signed-token implementation moved here) - New register_token_handler hookspec in hookspecs.py - Datasette.create_token() is now async and delegates to token handlers - New Datasette.verify_token() method tries all handlers in sequence - handler= parameter on create_token() to select a specific backend - TokenHandler exported from datasette package for plugin use - Fixed actor_from_request loop to await all coroutines (avoids warnings) * Add documentation and hook test for register_token_handler Fixes CI failures: the new hook needs a section in docs/plugin_hooks.rst (checked by test_plugin_hooks_are_documented) and a test_hook_* function in test_plugins.py (checked by test_plugin_hooks_have_tests). * Register tokens module as separate default plugin Instead of re-exporting hookimpls from default_permissions/__init__.py, register datasette.default_permissions.tokens as its own DEFAULT_PLUGINS entry. Cleaner and avoids confusing import-for-side-effect patterns. * Replace restrict_x params with TokenRestrictions dataclass Consolidates the three separate restrict_all, restrict_database, and restrict_resource parameters into a single TokenRestrictions dataclass. Cleaner API surface for both Datasette.create_token() and TokenHandler.create_token(). Also clarifies docs re: default handler selection via pluggy ordering. * Add builder methods to TokenRestrictions Adds allow_all(), allow_database(), and allow_resource() methods that return self for chaining. Callers no longer need to manipulate nested dicts directly: restrictions = (TokenRestrictions() .allow_all("view-instance") .allow_database("mydb", "create-table") .allow_resource("mydb", "mytable", "insert-row")) * docs: add 1.0a25 upgrade guide section for create_token() signature change Ref: https://github.com/simonw/datasette/issues/2649#issuecomment-3962639393 * docs: note that create_token() is now async in upgrade guide * docs: update internals, plugin_hooks, authentication for new token API - internals.rst: new async create_token() signature with restrictions and handler params, add TokenRestrictions reference docs - plugin_hooks.rst: show full create_token signature in TokenHandler example, note list returns and error cases - authentication.rst: cross-reference TokenRestrictions from the restrictions section * style: apply black formatting to token handler files * docs: fix RST heading underline length in internals.rst * tests: add restrictions round-trip and expiration tests for token handler Covers allow_database/allow_resource builders, _r payload encoding, and token_expires in verified actors. Coverage 76% -> 90%. * tests: add test for signed tokens disabled * fix: add TokenRestrictions TYPE_CHECKING import to fix ruff F821 * docs: regenerate plugins.rst with cog * docs: reformat code blocks in plugin_hooks.rst with blacken-docs * docs: add await .verify_token() to internals.rst * tests: rewrite register_token_handler test to use real plugin handler Adds a HardcodedTokenHandler to the test plugins dir that creates tokens like dstok_hardcoded_token_1. The test now exercises creating tokens via the default handler (which is the plugin's hardcoded one), by explicitly naming the hardcoded handler, and by explicitly naming the signed handler -- then verifies each token round-trips correctly. * tests: clarify test_token_handler_via_http tests the default signed handler * fix: use handler="signed" explicitly where signed tokens are expected The HardcodedTokenHandler in my_plugin.py gets globally registered, so create_token() without a handler name picks it up as the default. Fix the create-token view, CLI, and tests to explicitly request the signed handler where they depend on signed token behavior. * fix: use handler="signed" in test_create_table_permissions https://claude.ai/code/session_013cQFiDQjYRrRBH2biFfKuS
2026-02-25 16:32:45 -08:00
{
"name": "datasette.default_permissions.tokens",
"static": false,
"templates": false,
"version": null,
"hooks": [
"actor_from_request",
"register_token_handler"
]
},
{
"name": "datasette.events",
"static": false,
"templates": false,
"version": null,
"hooks": [
"register_events"
]
},
{
"name": "datasette.facets",
"static": false,
"templates": false,
"version": null,
"hooks": [
"register_facet_classes"
]
},
{
"name": "datasette.filters",
"static": false,
"templates": false,
"version": null,
"hooks": [
"filters_from_request"
]
},
{
"name": "datasette.forbidden",
"static": false,
"templates": false,
"version": null,
"hooks": [
"forbidden"
]
},
{
"name": "datasette.handle_exception",
"static": false,
"templates": false,
"version": null,
"hooks": [
"handle_exception"
]
},
{
"name": "datasette.publish.cloudrun",
"static": false,
"templates": false,
"version": null,
"hooks": [
"publish_subcommand"
]
},
{
"name": "datasette.publish.heroku",
"static": false,
"templates": false,
"version": null,
"hooks": [
"publish_subcommand"
]
},
{
"name": "datasette.sql_functions",
"static": false,
"templates": false,
"version": null,
"hooks": [
"prepare_connection"
]
}
]
.. [[[end]]]
You can add the ``--plugins-dir=`` option to include any plugins found in that directory.
Add ``--requirements`` to output a list of installed plugins that can then be installed in another Datasette instance using ``datasette install -r requirements.txt``::
datasette plugins --requirements
The output will look something like this::
datasette-codespaces==0.1.1
datasette-graphql==2.2
datasette-json-html==1.0.1
datasette-pretty-json==0.2.2
datasette-x-forwarded-host==0.1
To write that to a ``requirements.txt`` file, run this::
datasette plugins --requirements > requirements.txt
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.. _plugins_configuration:
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Plugin configuration
--------------------
Plugins can have their own configuration, embedded in a :ref:`configuration file <configuration>`. Configuration options for plugins live within a ``"plugins"`` key in that file, which can be included at the root, database or table level.
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Here is an example of some plugin configuration for a specific table:
.. [[[cog
from metadata_doc import config_example
config_example(cog, {
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"databases": {
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"sf-trees": {
"tables": {
"Street_Tree_List": {
"plugins": {
"datasette-cluster-map": {
"latitude_column": "lat",
"longitude_column": "lng"
}
}
}
}
}
}
})
.. ]]]
.. tab:: datasette.yaml
.. code-block:: yaml
databases:
sf-trees:
tables:
Street_Tree_List:
plugins:
datasette-cluster-map:
latitude_column: lat
longitude_column: lng
.. tab:: datasette.json
.. code-block:: json
{
"databases": {
"sf-trees": {
"tables": {
"Street_Tree_List": {
"plugins": {
"datasette-cluster-map": {
"latitude_column": "lat",
"longitude_column": "lng"
}
}
}
}
}
}
}
.. [[[end]]]
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This tells the ``datasette-cluster-map`` column which latitude and longitude columns should be used for a table called ``Street_Tree_List`` inside a database file called ``sf-trees.db``.
.. _plugins_configuration_secret:
Secret configuration values
~~~~~~~~~~~~~~~~~~~~~~~~~~~
Some plugins may need configuration that should stay secret - API keys for example. There are two ways in which you can store secret configuration values.
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**As environment variables**. If your secret lives in an environment variable that is available to the Datasette process, you can indicate that the configuration value should be read from that environment variable like so:
.. [[[cog
config_example(cog, {
"plugins": {
"datasette-auth-github": {
"client_secret": {
"$env": "GITHUB_CLIENT_SECRET"
}
}
}
})
.. ]]]
.. tab:: datasette.yaml
.. code-block:: yaml
plugins:
datasette-auth-github:
client_secret:
$env: GITHUB_CLIENT_SECRET
.. tab:: datasette.json
.. code-block:: json
{
"plugins": {
"datasette-auth-github": {
"client_secret": {
"$env": "GITHUB_CLIENT_SECRET"
}
}
}
}
.. [[[end]]]
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**As values in separate files**. Your secrets can also live in files on disk. To specify a secret should be read from a file, provide the full file path like this:
.. [[[cog
config_example(cog, {
"plugins": {
"datasette-auth-github": {
"client_secret": {
"$file": "/secrets/client-secret"
}
}
}
})
.. ]]]
.. tab:: datasette.yaml
.. code-block:: yaml
plugins:
datasette-auth-github:
client_secret:
$file: /secrets/client-secret
.. tab:: datasette.json
.. code-block:: json
{
"plugins": {
"datasette-auth-github": {
"client_secret": {
"$file": "/secrets/client-secret"
}
}
}
}
.. [[[end]]]
If you are publishing your data using the :ref:`datasette publish <cli_publish>` family of commands, you can use the ``--plugin-secret`` option to set these secrets at publish time. For example, using Heroku you might run the following command::
datasette publish heroku my_database.db \
--name my-heroku-app-demo \
--install=datasette-auth-github \
--plugin-secret datasette-auth-github client_id your_client_id \
--plugin-secret datasette-auth-github client_secret your_client_secret
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This will set the necessary environment variables and add the following to the deployed ``metadata.yaml``:
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.. [[[cog
config_example(cog, {
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"plugins": {
"datasette-auth-github": {
"client_id": {
"$env": "DATASETTE_AUTH_GITHUB_CLIENT_ID"
},
"client_secret": {
"$env": "DATASETTE_AUTH_GITHUB_CLIENT_SECRET"
}
}
}
})
.. ]]]
.. tab:: datasette.yaml
.. code-block:: yaml
plugins:
datasette-auth-github:
client_id:
$env: DATASETTE_AUTH_GITHUB_CLIENT_ID
client_secret:
$env: DATASETTE_AUTH_GITHUB_CLIENT_SECRET
.. tab:: datasette.json
.. code-block:: json
{
"plugins": {
"datasette-auth-github": {
"client_id": {
"$env": "DATASETTE_AUTH_GITHUB_CLIENT_ID"
},
"client_secret": {
"$env": "DATASETTE_AUTH_GITHUB_CLIENT_SECRET"
}
}
}
}
.. [[[end]]]