id,page,ref,title,content,breadcrumbs,references
writing_plugins:writing-plugins-building-urls,writing_plugins,writing-plugins-building-urls,Building URLs within plugins,"Plugins that define their own custom user interface elements may need to link to other pages within Datasette. 
             This can be a bit tricky if the Datasette instance is using the  base_url  configuration setting to run behind a proxy, since that can cause Datasette's URLs to include an additional prefix. 
             The  datasette.urls  object provides internal methods for correctly generating URLs to different pages within Datasette, taking any  base_url  configuration into account. 
             This object is exposed in templates as the  urls  variable, which can be used like this: 
             Back to the <a href=""{{ urls.instance() }}"">Homepage</a> 
             See  datasette.urls  for full details on this object.","[""Writing plugins""]",[]
writing_plugins:writing-plugins-configuration,writing_plugins,writing-plugins-configuration,Writing plugins that accept configuration,"When you are writing plugins, you can access plugin configuration like this using the  datasette plugin_config()  method. If you know you need plugin configuration for a specific table, you can access it like this: 
             plugin_config = datasette.plugin_config(
    ""datasette-cluster-map"", database=""sf-trees"", table=""Street_Tree_List""
) 
             This will return the  {""latitude_column"": ""lat"", ""longitude_column"": ""lng""}  in the above example. 
             If there is no configuration for that plugin, the method will return  None . 
             If it cannot find the requested configuration at the table layer, it will fall back to the database layer and then the root layer. For example, a user may have set the plugin configuration option inside  datasette.yaml  like so: 
             [[[cog
from metadata_doc import metadata_example
metadata_example(cog, {
    ""databases"": {
        ""sf-trees"": {
            ""plugins"": {
                ""datasette-cluster-map"": {
                    ""latitude_column"": ""xlat"",
                    ""longitude_column"": ""xlng""
                }
            }
        }
    }
}) 
             ]]] 
             [[[end]]] 
             In this case, the above code would return that configuration for ANY table within the  sf-trees  database. 
             The plugin configuration could also be set at the top level of  datasette.yaml : 
             [[[cog
metadata_example(cog, {
    ""plugins"": {
        ""datasette-cluster-map"": {
            ""latitude_column"": ""xlat"",
            ""longitude_column"": ""xlng""
        }
    }
}) 
             ]]] 
             [[[end]]] 
             Now that  datasette-cluster-map  plugin configuration will apply to every table in every database.","[""Writing plugins""]",[]
writing_plugins:writing-plugins-cookiecutter,writing_plugins,writing-plugins-cookiecutter,Starting an installable plugin using cookiecutter,"Plugins that can be installed should be written as Python packages using a  setup.py  file. 
             The quickest way to start writing one an installable plugin is to use the  datasette-plugin  cookiecutter template. This creates a new plugin structure for you complete with an example test and GitHub Actions workflows for testing and publishing your plugin. 
             Install cookiecutter  and then run this command to start building a plugin using the template: 
             cookiecutter gh:simonw/datasette-plugin 
             Read  a cookiecutter template for writing Datasette plugins  for more information about this template.","[""Writing plugins""]","[{""href"": ""https://github.com/simonw/datasette-plugin"", ""label"": ""datasette-plugin""}, {""href"": ""https://cookiecutter.readthedocs.io/en/stable/installation.html"", ""label"": ""Install cookiecutter""}, {""href"": ""https://simonwillison.net/2020/Jun/20/cookiecutter-plugins/"", ""label"": ""a cookiecutter template for writing Datasette plugins""}]"
writing_plugins:writing-plugins-custom-templates,writing_plugins,writing-plugins-custom-templates,Custom templates,"If your plugin has a  templates/  directory, Datasette will attempt to load templates from that directory before it uses its own default templates. 
             The priority order for template loading is: 
             
                 
                     templates from the  --template-dir  argument, if specified 
                 
                 
                     templates from the  templates/  directory in any installed plugins 
                 
                 
                     default templates that ship with Datasette 
                 
             
             See  Custom pages and templates  for more details on how to write custom templates, including which filenames to use to customize which parts of the Datasette UI. 
             Templates should be bundled for distribution using the same  package_data  mechanism in  setup.py  described for static assets above, for example: 
             package_data = (
    {
        ""datasette_plugin_name"": [
            ""templates/my_template.html"",
        ],
    },
) 
             You can also use wildcards here such as  templates/*.html . See  datasette-edit-schema  for an example of this pattern.","[""Writing plugins""]","[{""href"": ""https://github.com/simonw/datasette-edit-schema"", ""label"": ""datasette-edit-schema""}]"
writing_plugins:writing-plugins-designing-urls,writing_plugins,writing-plugins-designing-urls,Designing URLs for your plugin,"You can register new URL routes within Datasette using the  register_routes(datasette)  plugin hook. 
             Datasette's default URLs include these: 
             
                 
                     /dbname  - database page 
                 
                 
                     /dbname/tablename  - table page 
                 
                 
                     /dbname/tablename/pk  - row page 
                 
             
             See  Pages and API endpoints  and  Introspection  for more default URL routes. 
             To avoid accidentally conflicting with a database file that may be loaded into Datasette, plugins should register URLs using a  /-/  prefix. For example, if your plugin adds a new interface for uploading Excel files you might register a URL route like this one: 
             
                 
                     /-/upload-excel 
                 
             
             Try to avoid registering URLs that clash with other plugins that your users might have installed. There is no central repository of reserved URL paths (yet) but you can review existing plugins by browsing the  plugins directory . 
             If your plugin includes functionality that relates to a specific database you could also register a URL route like this: 
             
                 
                     /dbname/-/upload-excel 
                 
             
             Or for a specific table like this: 
             
                 
                     /dbname/tablename/-/modify-table-schema 
                 
             
             Note that a row could have a primary key of  -  and this URL scheme will still work, because Datasette row pages do not ever have a trailing slash followed by additional path components.","[""Writing plugins""]","[{""href"": ""https://datasette.io/plugins"", ""label"": ""plugins directory""}]"
writing_plugins:writing-plugins-extra-hooks,writing_plugins,writing-plugins-extra-hooks,Plugins that define new plugin hooks,"Plugins can define new plugin hooks that other plugins can use to further extend their functionality. 
             datasette-graphql  is one example of a plugin that does this. It defines a new hook called  graphql_extra_fields ,  described here , which other plugins can use to define additional fields that should be included in the GraphQL schema. 
             To define additional hooks, add a file to the plugin called  datasette_your_plugin/hookspecs.py  with content that looks like this: 
             from pluggy import HookspecMarker

hookspec = HookspecMarker(""datasette"")


@hookspec
def name_of_your_hook_goes_here(datasette):
    ""Description of your hook."" 
             You should define your own hook name and arguments here, following the documentation for  Pluggy specifications . Make sure to pick a name that is unlikely to clash with hooks provided by any other plugins. 
             Then, to register your plugin hooks, add the following code to your  datasette_your_plugin/__init__.py  file: 
             from datasette.plugins import pm
from . import hookspecs

pm.add_hookspecs(hookspecs) 
             This will register your plugin hooks as part of the  datasette  plugin hook namespace. 
             Within your plugin code you can trigger the hook using this pattern: 
             from datasette.plugins import pm

for (
    plugin_return_value
) in pm.hook.name_of_your_hook_goes_here(
    datasette=datasette
):
    # Do something with plugin_return_value
    pass 
             Other plugins will then be able to register their own implementations of your hook using this syntax: 
             from datasette import hookimpl


@hookimpl
def name_of_your_hook_goes_here(datasette):
    return ""Response from this plugin hook"" 
             These plugin implementations can accept 0 or more of the named arguments that you defined in your hook specification.","[""Writing plugins""]","[{""href"": ""https://github.com/simonw/datasette-graphql"", ""label"": ""datasette-graphql""}, {""href"": ""https://github.com/simonw/datasette-graphql/blob/main/README.md#adding-custom-fields-with-plugins"", ""label"": ""described here""}, {""href"": ""https://pluggy.readthedocs.io/en/stable/#specs"", ""label"": ""Pluggy specifications""}]"
writing_plugins:writing-plugins-one-off,writing_plugins,writing-plugins-one-off,Writing one-off plugins,"The quickest way to start writing a plugin is to create a  my_plugin.py  file and drop it into your  plugins/  directory. Here is an example plugin, which adds a new custom SQL function called  hello_world()  which takes no arguments and returns the string  Hello world! . 
             from datasette import hookimpl


@hookimpl
def prepare_connection(conn):
    conn.create_function(
        ""hello_world"", 0, lambda: ""Hello world!""
    ) 
             If you save this in  plugins/my_plugin.py  you can then start Datasette like this: 
             datasette serve mydb.db --plugins-dir=plugins/ 
             Now you can navigate to  http://localhost:8001/mydb  and run this SQL: 
             select hello_world(); 
             To see the output of your plugin.","[""Writing plugins""]","[{""href"": ""http://localhost:8001/mydb"", ""label"": ""http://localhost:8001/mydb""}]"
writing_plugins:writing-plugins-packaging,writing_plugins,writing-plugins-packaging,Packaging a plugin,"Plugins can be packaged using Python setuptools. You can see an example of a packaged plugin at  https://github.com/simonw/datasette-plugin-demos 
             The example consists of two files: a  setup.py  file that defines the plugin: 
             from setuptools import setup

VERSION = ""0.1""

setup(
    name=""datasette-plugin-demos"",
    description=""Examples of plugins for Datasette"",
    author=""Simon Willison"",
    url=""https://github.com/simonw/datasette-plugin-demos"",
    license=""Apache License, Version 2.0"",
    version=VERSION,
    py_modules=[""datasette_plugin_demos""],
    entry_points={
        ""datasette"": [
            ""plugin_demos = datasette_plugin_demos""
        ]
    },
    install_requires=[""datasette""],
) 
             And a Python module file,  datasette_plugin_demos.py , that implements the plugin: 
             from datasette import hookimpl
import random


@hookimpl
def prepare_jinja2_environment(env):
    env.filters[""uppercase""] = lambda u: u.upper()


@hookimpl
def prepare_connection(conn):
    conn.create_function(
        ""random_integer"", 2, random.randint
    ) 
             Having built a plugin in this way you can turn it into an installable package using the following command: 
             python3 setup.py sdist 
             This will create a  .tar.gz  file in the  dist/  directory. 
             You can then install your new plugin into a Datasette virtual environment or Docker container using  pip : 
             pip install datasette-plugin-demos-0.1.tar.gz 
             To learn how to upload your plugin to  PyPI  for use by other people, read the PyPA guide to  Packaging and distributing projects .","[""Writing plugins""]","[{""href"": ""https://github.com/simonw/datasette-plugin-demos"", ""label"": ""https://github.com/simonw/datasette-plugin-demos""}, {""href"": ""https://pypi.org/"", ""label"": ""PyPI""}, {""href"": ""https://packaging.python.org/tutorials/distributing-packages/"", ""label"": ""Packaging and distributing projects""}]"
writing_plugins:writing-plugins-static-assets,writing_plugins,writing-plugins-static-assets,Static assets,"If your plugin has a  static/  directory, Datasette will automatically configure itself to serve those static assets from the following path: 
             /-/static-plugins/NAME_OF_PLUGIN_PACKAGE/yourfile.js 
             Use the  datasette.urls.static_plugins(plugin_name, path)  method to generate URLs to that asset that take the  base_url  setting into account, see  datasette.urls . 
             To bundle the static assets for a plugin in the package that you publish to PyPI, add the following to the plugin's  setup.py : 
             package_data = (
    {
        ""datasette_plugin_name"": [
            ""static/plugin.js"",
        ],
    },
) 
             Where  datasette_plugin_name  is the name of the plugin package (note that it uses underscores, not hyphens) and  static/plugin.js  is the path within that package to the static file. 
             datasette-cluster-map  is a useful example of a plugin that includes packaged static assets in this way.","[""Writing plugins""]","[{""href"": ""https://github.com/simonw/datasette-cluster-map"", ""label"": ""datasette-cluster-map""}]"
writing_plugins:writing-plugins-tracing,writing_plugins,writing-plugins-tracing,Tracing plugin hooks,"The  DATASETTE_TRACE_PLUGINS  environment variable turns on detailed tracing showing exactly which hooks are being run. This can be useful for understanding how Datasette is using your plugin. 
             DATASETTE_TRACE_PLUGINS=1 datasette mydb.db 
             Example output: 
             actor_from_request:
{   'datasette': <datasette.app.Datasette object at 0x100bc7220>,
    'request': <asgi.Request method=""GET"" url=""http://127.0.0.1:4433/"">}
Hook implementations:
[   <HookImpl plugin_name='codespaces', plugin=<module 'datasette_codespaces' from '.../site-packages/datasette_codespaces/__init__.py'>>,
    <HookImpl plugin_name='datasette.actor_auth_cookie', plugin=<module 'datasette.actor_auth_cookie' from '.../datasette/datasette/actor_auth_cookie.py'>>,
    <HookImpl plugin_name='datasette.default_permissions', plugin=<module 'datasette.default_permissions' from '.../datasette/default_permissions.py'>>]
Results:
[{'id': 'root'}]","[""Writing plugins""]",[]