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Initial documentation for plugins, closes #213
https://datasette.readthedocs.io/en/latest/plugins.html
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docs/plugins.rst
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docs/plugins.rst
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Plugins
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=======
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Datasette's plugin system is currently under active development. It allows
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additional features to be implemented as Python code (or, soon, JavaScript)
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which can be wrapped up in a separate Python package.
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You can follow the development of plugins in `issue #14 <https://github.com/simonw/datasette/issues/14>`_.
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Using plugins
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-------------
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If a plugin has been packaged for distribution using setuptools you can use
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the plugin by installing it alongside Datasette in the same virtual
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environment or Docker container.
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You can also define one-off per-project plugins by saving them as
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``plugin_name.py`` functions in a ``plugins/`` folder and then passing that
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folder to ``datasette serve``.
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Writing plugins
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---------------
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The easiest way to write a plugin is to create a ``my_plugin.py`` file and
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drop it into your ``plugins/`` directory. Here is an example plugin, which
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adds a new custom SQL function called ``hello_world()`` which takes no
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arguments and returns the string ``Hello world!``.
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.. code-block:: python
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from datasette import hookimpl
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@hookimpl
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def prepare_connection(conn):
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conn.create_function('hello_world', 0, lambda: 'Hello world!')
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If you save this in ``plugins/my_plugin.py`` you can then start Datasette like
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this::
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datasette serve mydb.db --plugins-dir=plugins/
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Now you can navigate to http://localhost:8001/mydb and run this SQL::
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select hello_world();
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To see the output of your plugin.
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Packaging a plugin
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------------------
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Plugins can be packaged using Python setuptools. You can see an example of a
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packaged plugin at https://github.com/simonw/datasette-plugin-demos
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The example consists of two files: a ``setup.py`` file that defines the plugin:
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.. code-block:: python
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from setuptools import setup
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VERSION = '0.1'
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setup(
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name='datasette-plugin-demos',
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description='Examples of plugins for Datasette',
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author='Simon Willison',
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url='https://github.com/simonw/datasette-plugin-demos',
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license='Apache License, Version 2.0',
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version=VERSION,
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py_modules=['datasette_plugin_demos'],
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entry_points={
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'datasette': [
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'plugin_demos = datasette_plugin_demos'
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]
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},
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install_requires=['datasette']
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)
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And a Python module file, ``datasette_plugin_demos.py``, that implements the
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plugin:
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.. code-block:: python
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from datasette import hookimpl
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import random
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@hookimpl
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def prepare_jinja2_environment(env):
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env.filters['uppercase'] = lambda u: u.upper()
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@hookimpl
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def prepare_connection(conn):
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conn.create_function('random_integer', 2, random.randint)
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Having built a plugin in this way you can turn it into an installable package
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using the following command::
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python3 setup.py sdist
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This will create a ``.tar.gz`` file in the ``dist/`` directory.
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You can then install your new plugin into a Datasette virtual environment or
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Docker container using ``pip``::
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pip install datasette-plugin-demos-0.1.tar.gz
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To learn how to upload your plugin to `PyPI <https://pypi.org/>`_ for use by
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other people, read the PyPA guide to `Packaging and distributing projects
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<https://packaging.python.org/tutorials/distributing-packages/>`_.
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Plugin hooks
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------------
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Datasette will eventually have many more plugin hooks. You can track and
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contribute to their development in `issue #14
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<https://github.com/simonw/datasette/issues/14>`_.
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prepare_connection(conn)
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~~~~~~~~~~~~~~~~~~~~~~~~
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This hook is called when a new SQLite database connection is created. You can
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use it to `register custom SQL functions <https://docs.python.org/2/library/sqlite3.html#sqlite3.Connection.create_function>`_,
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aggregates and collations. For example:
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.. code-block:: python
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from datasette import hookimpl
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import random
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@hookimpl
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def prepare_connection(conn):
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conn.create_function('random_integer', 2, random.randint)
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This registers a SQL function called ``random_integer`` which takes two
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arguments and can be called like this::
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select random_integer(1, 10);
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prepare_jinja2_environment(env)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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This hook is called with the Jinja2 environment that is used to evaluate
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Datasette HTML templates. You can use it to do things like `register custom
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template filters <http://jinja.pocoo.org/docs/2.10/api/#custom-filters>`_, for
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example:
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.. code-block:: python
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from datasette import hookimpl
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@hookimpl
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def prepare_jinja2_environment(env):
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env.filters['uppercase'] = lambda u: u.upper()
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