Piccolo

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You can now use ``pip install piccolo[all]``, which will install all optional
requirements.

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Added the fixtures app. This is used to dump data from a database to a JSON
file, and then reload it again. It's useful for seeding a database with
essential data, whether that's a colleague setting up their local environment,
or deploying to production.

To create a fixture:

.. code-block:: bash

piccolo fixtures dump --apps=blog > fixture.json

To load a fixture:

.. code-block:: bash

piccolo fixtures load fixture.json

As part of this change, Piccolo's Pydantic support was brought into this
library (prior to this it only existed within the ``piccolo_api`` library). At
a later date, the ``piccolo_api`` library will be updated, so it's Pydantic
code just proxies to what's within the main ``piccolo`` library.

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Nullable UUID fields now work correctly.

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Improvements to ``piccolo schema generate``. It's now smarter about which
imports to include. Also, the ``Table`` classes output will now be sorted based
on their ``ForeignKey`` columns. Internally the sorting algorithm has been
changed to use the ``graphlib`` module, which was added in Python 3.9.

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Added the ``piccolo schema graph`` command for visualising your database
structure, which outputs a Graphviz file. It can then be turned into an
image, for example:

.. code-block:: bash

piccolo schema map | dot -Tpdf -o graph.pdf

Also made some minor changes to the ASGI templates, to reduce MyPy errors.

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Updated ``to_dict`` so it works with nested objects, as introduced by the
``prefetch`` functionality.

For example:

.. code-block:: python

band = Band.objects(Band.manager).first().run_sync()

>>> band.to_dict()
{'id': 1, 'name': 'Pythonistas', 'manager': {'id': 1, 'name': 'Guido'}}

It also works with filtering:

.. code-block:: python

>>> band.to_dict(Band.name, Band.manager.name)
{'name': 'Pythonistas', 'manager': {'name': 'Guido'}}

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