Split out new 'Writing plugins' page, refs #687

docs/writing_plugins.rst

@@ -0,0 +1,156 @@
+.. _writing_plugins:
+
+Writing plugins
+===============
+
+You can write one-off plugins that apply to just one Datasette instance, or you can write plugins which can be installed using ``pip`` and can be shipped to the Python Package Index (`PyPI <https://pypi.org/>`__) for other people to install.
+
+.. _plugins_writing_one_off:
+
+Writing one-off plugins
+-----------------------
+
+The easiest way to write 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!``.
+
+.. code-block:: python
+
+    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.
+
+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:
+
+.. code-block:: python
+
+    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:
+
+.. code-block:: python
+
+    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 <https://pypi.org/>`_ for use by other people, read the PyPA guide to `Packaging and distributing projects <https://packaging.python.org/tutorials/distributing-packages/>`_.
+
+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
+
+See `the datasette-plugin-demos repository <https://github.com/simonw/datasette-plugin-demos/tree/0ccf9e6189e923046047acd7878d1d19a2cccbb1>`_ for an example of how to create a package that includes a static folder.
+
+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 :ref:`customization` for more details on how to write custom templates, including which filenames to use to customize which parts of the Datasette UI.
+
+.. _plugins_plugin_config:
+
+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 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 like so::
+
+    {
+        "databases: {
+            "sf-trees": {
+                "plugins": {
+                    "datasette-cluster-map": {
+                        "latitude_column": "xlat",
+                        "longitude_column": "xlng"
+                    }
+                }
+            }
+        }
+    }
+
+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 ``metadata.json``::
+
+    {
+        "title": "This is the top-level title in metadata.json",
+        "plugins": {
+            "datasette-cluster-map": {
+                "latitude_column": "xlat",
+                "longitude_column": "xlng"
+            }
+        }
+    }
+
+Now that ``datasette-cluster-map`` plugin configuration will apply to every table in every database.