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Attributes without boilerplate.

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attrs is an MIT-licensed Python package with class decorators that ease the chores of implementing the most common attribute-related object protocols:

>>> import attr
>>> @attr.s
... class C(object):
...     x = attr.ib(default=42)
...     y = attr.ib(default=attr.Factory(list))
>>> i = C(x=1, y=2)
>>> i
C(x=1, y=2)
>>> i == C(1, 2)
True
>>> i != C(2, 1)
True
>>> attr.asdict(i)
{'y': 2, 'x': 1}
>>> C()
C(x=42, y=[])
>>> C2 = attr.make_class("C2", ["a", "b"])
>>> C2("foo", "bar")
C2(a='foo', b='bar')

(If you don’t like the playful attr.s and attr.ib, you can also use their no-nonsense aliases attr.attributes and attr.attr).

You just specify the attributes to work with and attrs gives you:

  • a nice human-readable __repr__,

  • a complete set of comparison methods,

  • an initializer,

  • and much more

without writing dull boilerplate code again and again.

This gives you the power to use actual classes with actual types in your code instead of confusing tuples or confusingly behaving namedtuples.

So put down that type-less data structures and welcome some class into your life!

attrs’s documentation lives at Read the Docs, the code on GitHub. It’s rigorously tested on Python 2.6, 2.7, 3.3+, and PyPy.

Changelog

Versions are year-based with a strict backwards compatibility policy. The third digit is only for regressions.

15.2.0 (2015-12-08)

Changes:

  • Add a convert argument to attr.ib, which allows specifying a function to run on arguments. This allows for simple type conversions, e.g. with attr.ib(convert=int). [26]

  • Speed up object creation when attribute validators are used. [28]

15.1.0 (2015-08-20)

Changes:

  • Add attr.validators.optional that wraps other validators allowing attributes to be None. [16]

  • Fix multi-level inheritance. [24]

  • Fix __repr__ to work for non-redecorated subclasses. [20]

15.0.0 (2015-04-15)

Changes:

Initial release.

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