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https://github.com/brianpugh/autoregistry

Automatic registry design-pattern library for mapping names to functionality.
https://github.com/brianpugh/autoregistry

abc abstract automatic config configuration design interface introspection mapping metaclass pattern reflection registry

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Automatic registry design-pattern library for mapping names to functionality.

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README 

        
.. image:: https://raw.githubusercontent.com/BrianPugh/autoregistry/main/assets/logo_400w.png



|Python compat| |PyPi| |GHA tests| |Codecov report| |readthedocs|



.. inclusion-marker-do-not-remove



AutoRegistry

============



Invoking functions and class-constructors from a string is a common design pattern

that AutoRegistry aims to solve.

For example, a user might specify a backend of type ``"sqlite"`` in a yaml configuration

file, for which our program needs to construct the ``SQLite`` subclass of our ``Database`` class.

Classically, you would need to manually create a lookup, mapping the string ``"sqlite"`` to

the ``SQLite`` constructor.

With AutoRegistry, the lookup is automatically created for you.



AutoRegistry has a single  powerful class ``Registry`` that can do the following:



* Be inherited to automatically register subclasses by their name.



* Be directly invoked ``my_registry = Registry()`` to create a decorator

  for registering callables like functions.



* Traverse and automatically create registries for other python libraries.



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AutoRegistry is also highly configurable, with features like name-schema-enforcement and name-conversion-rules.

`Checkout the docs for more information `_.



`Watch AutoRegistry in action! `_



Installation

============

AutoRegistry requires Python ``>=3.8``.



.. code-block:: bash



   python -m pip install autoregistry



Examples

========



Class Inheritance

^^^^^^^^^^^^^^^^^



``Registry`` adds a dictionary-like interface to class constructors

for looking up subclasses.



.. code-block:: python



   from abc import abstractmethod

   from dataclasses import dataclass

   from autoregistry import Registry



   @dataclass

   class Pokemon(Registry):

       level: int

       hp: int



       @abstractmethod

       def attack(self, target):

           """Attack another Pokemon."""



   class Charmander(Pokemon):

       def attack(self, target):

           return 1



   class Pikachu(Pokemon):

       def attack(self, target):

           return 2



   class SurfingPikachu(Pikachu):

       def attack(self, target):

           return 3



   print(f"{len(Pokemon)} Pokemon types registered:")

   print(f"    {list(Pokemon)}")

   # By default, lookup is case-insensitive

   charmander = Pokemon["cHaRmAnDer"](level=7, hp=31)

   print(f"Created Pokemon: {charmander}")



This code block produces the following output:



.. code-block::



   3 Pokemon types registered:

       ['charmander', 'pikachu', 'surfingpikachu']

   Created Pokemon: Charmander(level=7, hp=31)



Function Registry

^^^^^^^^^^^^^^^^^



Directly instantiating a ``Registry`` object allows you to

register functions by decorating them.



.. code-block:: python



   from autoregistry import Registry



   pokeballs = Registry()



   @pokeballs

   def masterball(target):

       return 1.0



   @pokeballs

   def pokeball(target):

       return 0.1



   for ball in ["pokeball", "masterball"]:

       success_rate = pokeballs[ball](None)

       print(f"Ash used {ball} and had {success_rate=}")



This code block produces the following output:



.. code-block:: text



   Ash used pokeball and had success_rate=0.1

   Ash used masterball and had success_rate=1.0



Module Registry

^^^^^^^^^^^^^^^



Create a registry for another python module.



.. code-block:: python



   import torch

   from autoregistry import Registry



   optims = Registry(torch.optim)



   # "adamw" and ``lr`` could be coming from a configuration file.

   optimizer = optims["adamw"](model.parameters(), lr=3e-3)



   assert list(optims) == [

       "asgd",

       "adadelta",

       "adagrad",

       "adam",

       "adamw",

       "adamax",

       "lbfgs",

       "nadam",

       "optimizer",

       "radam",

       "rmsprop",

       "rprop",

       "sgd",

       "sparseadam",

       "lr_scheduler",

       "swa_utils",

   ]



.. |GHA tests| image:: https://github.com/BrianPugh/autoregistry/workflows/tests/badge.svg

   :target: https://github.com/BrianPugh/autoregistry/actions?query=workflow%3Atests

   :alt: GHA Status

.. |Codecov report| image:: https://codecov.io/github/BrianPugh/autoregistry/coverage.svg?branch=main

   :target: https://codecov.io/github/BrianPugh/autoregistry?branch=main

   :alt: Coverage

.. |readthedocs| image:: https://readthedocs.org/projects/autoregistry/badge/?version=latest

        :target: https://autoregistry.readthedocs.io/en/latest/?badge=latest

        :alt: Documentation Status

.. |Python compat| image:: https://img.shields.io/badge/>=python-3.8-blue.svg

.. |PyPi| image:: https://img.shields.io/pypi/v/autoregistry.svg

        :target: https://pypi.python.org/pypi/autoregistry