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This change introduces a new plugin hook, publish_subcommand, which can be used to implement new subcommands for the "datasette publish" command family. I've used this new hook to refactor out the "publish now" and "publish heroku" implementations into separate modules. I've also added unit tests for these two publishers, mocking the subprocess.call and subprocess.check_output functions. As part of this, I introduced a mechanism for loading default plugins. These are defined in the new "default_plugins" list inside datasette/app.py Closes #217 (Plugin support for datasette publish) Closes #348 (Unit tests for "datasette publish") Refs #14, #59, #102, #103, #146, #236, #347
269 lines
8.1 KiB
ReStructuredText
269 lines
8.1 KiB
ReStructuredText
.. _plugins:
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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 front-end JavaScript)
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which can be wrapped up in a separate Python package. The underlying mechanism
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uses `pluggy <https://pluggy.readthedocs.io/>`_.
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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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The ``datasette publish`` and ``datasette package`` commands both take an
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optional ``--install`` argument. You can use this one or more times to tell
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Datasette to ``pip install`` specific plugins as part of the process. You can
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use the name of a package on PyPI or any of the other valid arguments to ``pip
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install`` such as a URL to a ``.zip`` file::
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datasette publish now mydb.db \
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--install=datasette-plugin-demos \
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--install=https://url-to-my-package.zip
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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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Static assets
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-------------
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If your plugin has a ``static/`` directory, Datasette will automatically
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configure itself to serve those static assets from the following path::
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/-/static-plugins/NAME_OF_PLUGIN_PACKAGE/yourfile.js
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See `the datasette-plugin-demos repository <https://github.com/simonw/datasette-plugin-demos/tree/0ccf9e6189e923046047acd7878d1d19a2cccbb1>`_
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for an example of how to create a package that includes a static folder.
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Custom templates
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----------------
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If your plugin has a ``templates/`` directory, Datasette will attempt to load
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templates from that directory before it uses its own default templates.
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The priority order for template loading is:
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* templates from the ``--template-dir`` argument, if specified
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* templates from the ``templates/`` directory in any installed plugins
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* default templates that ship with Datasette
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See :ref:`customization` for more details on how to write custom templates,
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including which filenames to use to customize which parts of the Datasette UI.
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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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You can now use this filter in your custom templates like so::
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Table name: {{ table|uppercase }}
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extra_css_urls()
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~~~~~~~~~~~~~~~~
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Return a list of extra CSS URLs that should be included on every page. These can
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take advantage of the CSS class hooks described in :ref:`customization`.
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This can be a list of URLs:
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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 extra_css_urls():
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return [
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'https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css'
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]
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Or a list of dictionaries defining both a URL and an
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`SRI hash <https://www.srihash.org/>`_:
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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 extra_css_urls():
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return [{
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'url': 'https://stackpath.bootstrapcdn.com/bootstrap/4.1.0/css/bootstrap.min.css',
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'sri': 'sha384-9gVQ4dYFwwWSjIDZnLEWnxCjeSWFphJiwGPXr1jddIhOegiu1FwO5qRGvFXOdJZ4',
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}]
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extra_js_urls()
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~~~~~~~~~~~~~~~
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This works in the same way as ``extra_css_urls()`` but for JavaScript. You can
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return either a list of URLs or a list of dictionaries:
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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 extra_js_urls():
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return [{
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'url': 'https://code.jquery.com/jquery-3.3.1.slim.min.js',
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'sri': 'sha384-q8i/X+965DzO0rT7abK41JStQIAqVgRVzpbzo5smXKp4YfRvH+8abtTE1Pi6jizo',
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}]
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You can also return URLs to files from your plugin's ``static/`` directory, if
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you have one:
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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 extra_js_urls():
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return [
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'/-/static-plugins/your_plugin/app.js'
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]
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publish_subcommand(publish)
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~~~~~~~~~~~~~~~~~~~~~~~~~~~
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This hook allows you to create new providers for the ``datasette publish``
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command. Datasette uses this hook internally to implement the default ``now``
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and ``heroku`` subcommands, so you can read
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`their source <https://github.com/simonw/datasette/tree/master/datasette/publish>`_
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to see examples of this hook in action.
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