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Classes Without Boilerplate

Project description

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attrs: Classes Without Boilerplate

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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 methods).

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

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

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

>>> 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,
  • 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.

This gives you the power to use actual classes with actual types in your code instead of confusing tuples or confusingly behaving namedtuples. Which in turn encourages you to write small classes that do one thing well. Never again violate the single responsibility principle just because implementing __init__ et al is a painful drag.


Amber Hawkie Brown, Twisted Release Manager and Computer Owl:

Writing a fully-functional class using attrs takes me less time than writing this testimonial.

Glyph Lefkowitz, creator of Twisted, Automat, and other open source software, in The One Python Library Everyone Needs:

I’m looking forward to is being able to program in Python-with-attrs everywhere. It exerts a subtle, but positive, design influence in all the codebases I’ve see it used in.

Kenneth Reitz, author of Requests and Developer Advocate at DigitalOcean, (on paper no less!):

attrs—classes for humans. I like it.

Łukasz Langa, prolific CPython core developer and Production Engineer at Facebook:

I’m increasingly digging your attr.ocity. Good job!

Getting Help

Please use the python-attrs tag on StackOverflow to get help.

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

Project Information

attrs is released under the MIT license, its documentation lives at Read the Docs, the code on GitHub, and the latest release on PyPI. It’s rigorously tested on Python 2.7, 3.4+, and PyPy.

We collect information on third-party extensions in our wiki. 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 to get you started!

Release Information

18.2.0 (2018-09-01)


  • Comparing subclasses using <, >, <=, and >= is now deprecated. The docs always claimed that instances are only compared if the types are identical, so this is a first step to conform to the docs.

    Equality operators (== and !=) were always strict in this regard. #394


  • attrs now ships its own PEP 484 type hints. Together with mypy’s attrs plugin, you’ve got all you need for writing statically typed code in both Python 2 and 3!

    At that occasion, we’ve also added narrative docs about type annotations in attrs. #238

  • Added kw_only arguments to attr.ib and attr.s, and a corresponding kw_only attribute to attr.Attribute. This change makes it possible to have a generated __init__ with keyword-only arguments on Python 3, relaxing the required ordering of default and non-default valued attributes. #281, #411

  • The test suite now runs with hypothesis.HealthCheck.too_slow disabled to prevent CI breakage on slower computers. #364, #396

  • attr.validators.in_() now raises a ValueError with a useful message even if the options are a string and the value is not a string. #383

  • attr.asdict() now properly handles deeply nested lists and dictionaries. #395

  • Added attr.converters.default_if_none() that allows to replace None values in attributes. For example attr.ib(converter=default_if_none("")) replaces None by empty strings. #400, #414

  • Fixed a reference leak where the original class would remain live after being replaced when slots=True is set. #407

  • Slotted classes can now be made weakly referenceable by passing @attr.s(weakref_slot=True). #420

  • Added cache_hash option to @attr.s which causes the hash code to be computed once and stored on the object. #425

  • Attributes can be named property and itemgetter now. #430

  • It is now possible to override a base class’ class variable using only class annotations. #431

Full changelog.


attrs is written and maintained by Hynek Schlawack.

The development is kindly supported by Variomedia AG.

A full list of contributors can be found in GitHub’s overview.

It’s the spiritual successor of characteristic and aspires to fix some of it clunkiness and unfortunate decisions. Both were inspired by Twisted’s FancyEqMixin but both are implemented using class decorators because subclassing is bad for you, m’kay?

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