| single |
.. image:: https://www.attrs.org/en/stable/_static/attrs_logo.png
:alt: attrs logo
:align: center
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.
.. teaser-end
For that, it gives you a class decorator and a way to declaratively define
the attributes on that class:
.. -code-begin-
.. code-block:: pycon
>>> 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.
**Hate type annotations**!?
No problem!
Types are entirely **optional** with attrs.
Simply assign ``attrs.field()`` to the attributes instead of annotating
them with types.
----
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**.
Please check out [On The Core API Names] for a more in-depth explanation.
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], or allows more ways to [plug into the initialization
process].
For more details, please refer to our [comparison page].
.. -project-information-
Project Information
===================
- **License**: [MIT]
- **PyPI**: https://pypi.org/project/attrs/
|