attrs 21.1.0

Classes Without Boilerplate

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). Trusted by NASA for Mars missions since 2020!

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)
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.

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.

Getting Help

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

Answering questions of your fellow developers is also a 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, 3.5+, 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!

attrs for Enterprise

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Release Information

21.1.0 (2021-05-06)

Deprecations

• The long-awaited, much-talked-about, little-delivered import attrs is finally upon us!

  Since the NG APIs have now been proclaimed stable, the next release of attrs will allow you to actually import attrs. We’re taking this opportunity to replace some defaults in our APIs that made sense in 2015, but don’t in 2021.

  So please, if you have any pet peeves about defaults in attrs’s APIs, now is the time to air your grievances in #487! We’re not gonna get such a chance for a second time, without breaking our backward-compatibility guarantees, or long deprecation cycles. Therefore, speak now or forever hold you peace! #487

• The cmp argument to attr.s() and attr.ib() has been undeprecated It will continue to be supported as syntactic sugar to set eq and order in one go.

  I’m terribly sorry for the hassle around this argument! The reason we’re bringing it back is it’s usefulness regarding customization of equality/ordering.

  The cmp attribute and argument on attr.Attribute remains deprecated and will be removed later this year. #773

Changes

• It’s now possible to customize the behavior of eq and order by passing in a callable. #435, #627

• The instant favorite next-generation APIs are not provisional anymore!

  They are also officially supported by Mypy as of their 0.800 release.

  We hope the next release will already contain an (additional) importable package called attrs. #668, #786

• If an attribute defines a converter, the type of its parameter is used as type annotation for its corresponding __init__ parameter.

  If an attr.converters.pipe is used, the first one’s is used. #710

• Fixed the creation of an extra slot for an attr.ib when the parent class already has a slot with the same name. #718

• __attrs__init__() will now be injected if init=False, or if auto_detect=True and a user-defined __init__() exists.

  This enables users to do “pre-init” work in their __init__() (such as super().__init__()).

  __init__() can then delegate constructor argument processing to self.__attrs_init__(*args, **kwargs). #731

• bool(attr.NOTHING) is now False. #732

• It’s now possible to use super() inside of properties of slotted classes. #747

• Allow for a __attrs_pre_init__() method that – if defined – will get called at the beginning of the attrs-generated __init__() method. #750

• Added forgotten attr.Attribute.evolve() to type stubs. #752

• attrs.evolve() now works recursively with nested attrs classes. #759

• Python 3.10 is now officially supported. #763

• attr.resolve_types() now takes an optional attrib argument to work inside a field_transformer. #774

• ClassVars are now also detected if they come from typing-extensions. #782

• To make it easier to customize attribute comparison (#435), we have added the attr.cmp_with() helper.

  See the new docs on comparison for more details. #787

• Added provisional support for static typing in pyright via the dataclass_transforms specification. Both the pyright specification and attrs implementation may change in future versions of both projects.

  Your constructive feedback is welcome in both attrs#795 and pyright#1782. #796

Full changelog.

Credits

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?