Classes Without Boilerplate
Project description
attrs: 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).
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 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
20.1.0 (2020-08-20)
Backward-incompatible Changes
Python 3.4 is not supported anymore. It has been unsupported by the Python core team for a while now, its PyPI downloads are negligible, and our CI provider removed it as a supported option.
It’s very unlikely that attrs will break under 3.4 anytime soon, which is why we do not block its installation on Python 3.4. But we don’t test it anymore and will block it once someone reports breakage. #608
Deprecations
Less of a deprecation and more of a heads up: the next release of attrs will introduce an attrs namespace. That means that you’ll finally be able to run import attrs with new functions that aren’t cute abbreviations and that will carry better defaults.
This should not break any of your code, because project-local packages have priority before installed ones. If this is a problem for you for some reason, please report it to our bug tracker and we’ll figure something out.
The old attr namespace isn’t going anywhere and its defaults are not changing – this is a purely additive measure. Please check out the linked issue for more details.
These new APIs have been added provisionally as part of #666 so you can try them out today and provide feedback. Learn more in the API docs. #408
Changes
Added attr.resolve_types(). It ensures that all forward-references and types in string form are resolved into concrete types.
You need this only if you need concrete types at runtime. That means that if you only use types for static type checking, you do not need this function. #288, #302
Added @attr.s(collect_by_mro=False) argument that if set to True fixes the collection of attributes from base classes.
It’s only necessary for certain cases of multiple-inheritance but is kept off for now for backward-compatibility reasons. It will be turned on by default in the future.
As a side-effect, attr.Attribute now always has an inherited attribute indicating whether an attribute on a class was directly defined or inherited. #428, #635
On Python 3, all generated methods now have a docstring explaining that they have been created by attrs. #506
It is now possible to prevent attrs from auto-generating the __setstate__ and __getstate__ methods that are required for pickling of slotted classes.
Either pass @attr.s(getstate_setstate=False) or pass @attr.s(auto_detect=True) and implement them yourself: if attrs finds either of the two methods directly on the decorated class, it assumes implicitly getstate_setstate=False (and implements neither).
This option works with dict classes but should never be necessary. #512, #513, #642
Fixed a ValueError: Cell is empty bug that could happen in some rare edge cases. #590
attrs can now automatically detect your own implementations and infer init=False, repr=False, eq=False, order=False, and hash=False if you set @attr.s(auto_detect=True). attrs will ignore inherited methods. If the argument implies more than one method (e.g. eq=True creates both __eq__ and __ne__), it’s enough for one of them to exist and attrs will create neither.
This feature requires Python 3. #607
Added attr.converters.pipe(). The feature allows combining multiple conversion callbacks into one by piping the value through all of them, and retuning the last result.
As part of this feature, we had to relax the type information for converter callables. #618
Fixed serialization behavior of non-slots classes with cache_hash=True. The hash cache will be cleared on operations which make “deep copies” of instances of classes with hash caching, though the cache will not be cleared with shallow copies like those made by copy.copy().
Previously, copy.deepcopy() or serialization and deserialization with pickle would result in an un-initialized object.
This change also allows the creation of cache_hash=True classes with a custom __setstate__, which was previously forbidden (#494). #620
It is now possible to specify hooks that are called whenever an attribute is set after a class has been instantiated.
You can pass on_setattr both to @attr.s() to set the default for all attributes on a class, and to @attr.ib() to overwrite it for individual attributes.
attrs also comes with a new module attr.setters that brings helpers that run validators, converters, or allow to freeze a subset of attributes. #645, #660
Provisional APIs called attr.define(), attr.mutable(), and attr.frozen() have been added.
They are only available on Python 3.6 and later, and call attr.s() with different default values.
If nothing comes up, they will become the official way for creating classes in 20.2.0 (see above).
Please note that it may take some time until mypy – and other tools that have dedicated support for attrs – recognize these new APIs. Please do not open issues on our bug tracker, there is nothing we can do about it. #666
We have also provisionally added attr.field() that supplants attr.ib(). It also requires at least Python 3.6 and is keyword-only. Other than that, it only dropped a few arguments, but changed no defaults.
As with attr.s(): attr.ib() is not going anywhere. #669
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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