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).
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Its main goal is to help you to write concise and correct software without slowing down your code.
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Especially those generously supporting us at the The Organization tier and higher:
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Example
attrs gives you a class decorator and a way to declaratively define the attributes on that class:
>>> from attrs import asdict, define, make_class, Factory
>>> @define
... class SomeClass:
... a_number: int = 42
... list_of_numbers: list[int] = 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
>>> asdict(sc)
{'a_number': 1, 'list_of_numbers': [1, 2, 3]}
>>> SomeClass()
SomeClass(a_number=42, list_of_numbers=[])
>>> C = 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__
, - equality-checking methods,
- an initializer,
- and much more,
without writing dull boilerplate code again and again and without runtime performance penalties.
This example uses attrs's modern APIs that have been introduced in version 20.1.0, and the attrs package import name that has been added in version 21.3.0.
The classic APIs (@attr.s
, attr.ib
, plus their serious-business aliases) and the attr
package import name will remain indefinitely.
Check out On The Core API Names for an in-depth explanation!
Hate Type Annotations!?
No problem!
Types are entirely optional with attrs.
Simply assign attrs.field()
to the attributes instead of annotating them with types:
from attrs import define, field
@define
class SomeClass:
a_number = field(default=42)
list_of_numbers = field(factory=list)
Data Classes
On the tin, attrs might remind you of dataclasses
(and indeed, dataclasses
are a descendant of attrs).
In practice it does a lot more and is more flexible.
For instance, it allows you to define special handling of NumPy arrays for equality checks, allows more ways to plug into the initialization process, has a replacement for __init_subclass__
, and allows for stepping through the generated methods using a debugger.
For more details, please refer to our comparison page, but generally speaking, we are more likely to commit crimes against nature to make things work that one would expect to work, but that are quite complicated in practice.
Project Information
attrs for Enterprise
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Release Information
Deprecations
- Given the amount of warnings raised in the broader ecosystem, we've decided to only soft-deprecate the hash argument to
@define
/ @attr.s
.
Please don't use it in new code, but we don't intend to remove it anymore.
#1330
Changes
attrs.converters.pipe()
(and its syntactic sugar of passing a list for attrs.field()
's / attr.ib()
's converter argument) works again when passing attrs.setters.convert
to on_setattr (which is default for attrs.define
).
#1328- Restored support for PEP 649 / 749-implementing Pythons -- currently 3.14-dev.
#1329
Full changelog →