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Classes Without Boilerplate

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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)
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,
  • 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.

Testimonials

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

19.1.0 (2019-03-03)

Backward-incompatible Changes

  • Fixed a bug where deserialized objects with cache_hash=True could have incorrect hash code values. This change breaks classes with cache_hash=True when a custom __setstate__ is present. An exception will be thrown when applying the attrs annotation to such a class. This limitation is tracked in issue #494. #482

Changes

  • Add is_callable, deep_iterable, and deep_mapping validators.

    • is_callable: validates that a value is callable
    • deep_iterable: Allows recursion down into an iterable, applying another validator to every member in the iterable as well as applying an optional validator to the iterable itself.
    • deep_mapping: Allows recursion down into the items in a mapping object, applying a key validator and a value validator to the key and value in every item. Also applies an optional validator to the mapping object itself.

    You can find them in the attr.validators package. #425

  • Fixed stub files to prevent errors raised by mypy’s disallow_any_generics = True option. #443

  • Attributes with init=False now can follow after kw_only=True attributes. #450

  • attrs now has first class support for defining exception classes.

    If you define a class using @attr.s(auto_exc=True) and subclass an exception, the class will behave like a well-behaved exception class including an appropriate __str__ method, and all attributes additionally available in an args attribute. #500

  • Clarified documentation for hashing to warn that hashable objects should be deeply immutable (in their usage, even if this is not enforced). #503

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?

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