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Initial documentation for plugins, closes #213
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simonw committed Apr 16, 2018
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3 changes: 3 additions & 0 deletions README.md
Expand Up @@ -117,6 +117,7 @@ http://localhost:8001/History/downloads.json?_shape=objects will return that dat
-m, --metadata FILENAME Path to JSON file containing license/source
metadata
--template-dir DIRECTORY Path to directory containing custom templates
--plugins-dir DIRECTORY Path to directory containing custom plugins
--static STATIC MOUNT mountpoint:path-to-directory for serving static
files
--help Show this message and exit.
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--force Pass --force option to now
--branch TEXT Install datasette from a GitHub branch e.g. master
--template-dir DIRECTORY Path to directory containing custom templates
--plugins-dir DIRECTORY Path to directory containing custom plugins
--static STATIC MOUNT mountpoint:path-to-directory for serving static
files
--title TEXT Title for metadata
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--extra-options TEXT Extra options to pass to datasette serve
--branch TEXT Install datasette from a GitHub branch e.g. master
--template-dir DIRECTORY Path to directory containing custom templates
--plugins-dir DIRECTORY Path to directory containing custom plugins
--static STATIC MOUNT mountpoint:path-to-directory for serving static
files
--title TEXT Title for metadata
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1 change: 1 addition & 0 deletions docs/getting_started.rst
Expand Up @@ -110,6 +110,7 @@ datasette serve options
-m, --metadata FILENAME Path to JSON file containing license/source
metadata
--template-dir DIRECTORY Path to directory containing custom templates
--plugins-dir DIRECTORY Path to directory containing custom plugins
--static STATIC MOUNT mountpoint:path-to-directory for serving static
files
--help Show this message and exit.
1 change: 1 addition & 0 deletions docs/index.rst
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sql_queries
metadata
custom_templates
plugins
changelog

.. _Zeit Now: https://zeit.co/now
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Plugins
=======

Datasette's plugin system is currently under active development. It allows
additional features to be implemented as Python code (or, soon, JavaScript)
which can be wrapped up in a separate Python package.

You can follow the development of plugins in `issue #14 <https://github.com/simonw/datasette/issues/14>`_.

Using 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 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 serve``.

Writing 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/>`_.


Plugin hooks
------------

Datasette will eventually have many more plugin hooks. You can track and
contribute to their development in `issue #14
<https://github.com/simonw/datasette/issues/14>`_.

prepare_connection(conn)
~~~~~~~~~~~~~~~~~~~~~~~~

This hook is called when a new SQLite database connection is created. You can
use it to `register custom SQL functions <https://docs.python.org/2/library/sqlite3.html#sqlite3.Connection.create_function>`_,
aggregates and collations. For example:

.. code-block:: python
from datasette import hookimpl
import random
@hookimpl
def prepare_connection(conn):
conn.create_function('random_integer', 2, random.randint)
This registers a SQL function called ``random_integer`` which takes two
arguments and can be called like this::

select random_integer(1, 10);

prepare_jinja2_environment(env)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This hook is called with the Jinja2 environment that is used to evaluate
Datasette HTML templates. You can use it to do things like `register custom
template filters <http://jinja.pocoo.org/docs/2.10/api/#custom-filters>`_, for
example:

.. code-block:: python
from datasette import hookimpl
@hookimpl
def prepare_jinja2_environment(env):
env.filters['uppercase'] = lambda u: u.upper()

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