README.rst

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   :alt: attrs Logo

======================================
``attrs``: Classes Without Boilerplate
======================================

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.. teaser-begin

``attrs`` is the Python package that will bring back the **joy** of **writing classes** by relieving you from the drudgery of implementing object protocols (aka `dunder <https://nedbatchelder.com/blog/200605/dunder.html>`_ methods).

Its main goal is to help you to write **concise** and **correct** software without slowing down your code.

.. teaser-end

For that, it gives you a class decorator and a way to declaratively define the attributes on that class:

.. -code-begin-

.. code-block:: pycon

   >>> import attr

   >>> @attr.s
   ... class SomeClass(object):
   ...     a_number = attr.ib(default=42)
   ...     list_of_numbers = attr.ib(factory=list)
   ...
   ...     def hard_math(self, another_number):
   ...         return self.a_number + sum(self.list_of_numbers) * another_number


   >>> sc = SomeClass(1, [1, 2, 3])
   >>> sc
   SomeClass(a_number=1, list_of_numbers=[1, 2, 3])

   >>> sc.hard_math(3)
   19
   >>> sc == SomeClass(1, [1, 2, 3])
   True
   >>> sc != SomeClass(2, [3, 2, 1])
   True

   >>> attr.asdict(sc)
   {'a_number': 1, 'list_of_numbers': [1, 2, 3]}

   >>> SomeClass()
   SomeClass(a_number=42, list_of_numbers=[])

   >>> C = attr.make_class("C", ["a", "b"])
   >>> C("foo", "bar")
   C(a='foo', b='bar')


After *declaring* your attributes ``attrs`` gives you:

- a concise and explicit overview of the class's attributes,
- a nice human-readable ``__repr__``,
- a complete set of comparison methods (equality and ordering),
- an initializer,
- and much more,

*without* writing dull boilerplate code again and again and *without* runtime performance penalties.

On Python 3.6 and later, you can often even drop the calls to ``attr.ib()`` by using `type annotations <https://www.attrs.org/en/latest/types.html>`_.

This gives you the power to use actual classes with actual types in your code instead of confusing ``tuple``\ s or `confusingly behaving <https://www.attrs.org/en/stable/why.html#namedtuples>`_ ``namedtuple``\ s.
Which in turn encourages you to write *small classes* that do `one thing well <https://www.destroyallsoftware.com/talks/boundaries>`_.
Never again violate the `single responsibility principle <https://en.wikipedia.org/wiki/Single_responsibility_principle>`_ just because implementing ``__init__`` et al is a painful drag.


.. -getting-help-

Getting Help
============

Please use the ``python-attrs`` tag on `StackOverflow <https://stackoverflow.com/questions/tagged/python-attrs>`_ to get help.

Answering questions of your fellow developers is also a great way to help the project!


.. -project-information-

Project Information
===================

``attrs`` is released under the `MIT <https://choosealicense.com/licenses/mit/>`_ license,
its documentation lives at `Read the Docs <https://www.attrs.org/>`_,
the code on `GitHub <https://github.com/python-attrs/attrs>`_,
and the latest release on `PyPI <https://pypi.org/project/attrs/>`_.
It’s rigorously tested on Python 2.7, 3.5+, and PyPy.

We collect information on **third-party extensions** in our `wiki <https://github.com/python-attrs/attrs/wiki/Extensions-to-attrs>`_.
Feel free to browse and add your own!

If you'd like to contribute to ``attrs`` you're most welcome and we've written `a little guide <https://www.attrs.org/en/latest/contributing.html>`_ to get you started!


``attrs`` for Enterprise
------------------------

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`Learn more. <https://tidelift.com/subscription/pkg/pypi-attrs?utm_source=pypi-attrs&utm_medium=referral&utm_campaign=enterprise&utm_term=repo>`_