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Glossary

:::{glossary} dunder methods "Dunder" is a contraction of "double underscore".

It's methods like __init__ or __eq__ that are sometimes also called magic methods or it's said that they implement an object protocol.

In spoken form, you'd call __init__ just "dunder init".

Its first documented use is a mailing list posting by Mark Jackson from 2002.

dict classes A regular class whose attributes are stored in the {attr}object.__dict__ attribute of every single instance. This is quite wasteful especially for objects with very few data attributes and the space consumption can become significant when creating large numbers of instances.

This is the type of class you get by default both with and without attrs (except with the next APIs {func}attrs.define(), attrs.mutable(), and attrs.frozen()).

slotted classes A class whose instances have no {attr}object.__dict__ attribute and define their attributes in a object.__slots__ attribute instead. In attrs, they are created by passing slots=True to @attr.s (and are on by default in {func}attrs.define(), attrs.mutable(), and attrs.frozen()).

Their main advantage is that they use less memory on CPython¹ and are slightly faster.

However, they also come with several possibly surprising gotchas:

Slotted classes don't allow for any other attribute to be set except for those defined in one of the class' hierarchies __slots__:

>>> from attr import define
>>> @define
... class Coordinates:
...     x: int
...     y: int
...
>>> c = Coordinates(x=1, y=2)
>>> c.z = 3
Traceback (most recent call last):
    ...
AttributeError: 'Coordinates' object has no attribute 'z'

Slotted classes can inherit from other classes just like non-slotted classes, but some of the benefits of slotted classes are lost if you do that. If you must inherit from other classes, try to inherit only from other slotted classes.
However, it's not possible to inherit from more than one class that has attributes in __slots__ (you will get an TypeError: multiple bases have instance lay-out conflict).

It's not possible to monkeypatch methods on slotted classes. This can feel limiting in test code, however the need to monkeypatch your own classes is usually a design smell.

If you really need to monkeypatch an instance in your tests, but don't want to give up on the advantages of slotted classes in production code, you can always subclass a slotted class as a dict class with no further changes and all the limitations go away:

>>> import unittest.mock
>>> @define
... class Slotted:
...     x: int
...
...     def method(self):
...         return self.x
>>> s = Slotted(42)
>>> s.method()
42
>>> with unittest.mock.patch.object(s, "method", return_value=23):
...     pass
Traceback (most recent call last):
  ...
AttributeError: 'Slotted' object attribute 'method' is read-only
>>> @define(slots=False)
... class Dicted(Slotted):
...     pass
>>> d = Dicted(42)
>>> d.method()
42
>>> with unittest.mock.patch.object(d, "method", return_value=23):
...     assert 23 == d.method()

Slotted classes must implement {meth}__getstate__ <object.__getstate__> and {meth}__setstate__ <object.__setstate__> to be serializable with {mod}pickle protocol 0 and 1. Therefore, attrs creates these methods automatically for slotted classes.

:::{note} When decorating with @attr.s(slots=True) and the class already implements the {meth}__getstate__ <object.__getstate__> and {meth}__setstate__ <object.__setstate__> methods, they will be overwritten by attrs autogenerated implementation by default.

This can be avoided by setting @attr.s(getstate_setstate=False) or by setting @attr.s(auto_detect=True).

{func}~attrs.define sets auto_detect=True by default. :::

Also, think twice before using {mod}pickle.
Slotted classes are weak-referenceable by default. This can be disabled in CPython by passing weakref_slot=False to @attr.s ².
Since it's currently impossible to make a class slotted after it's been created, attrs has to replace your class with a new one. While it tries to do that as graciously as possible, certain metaclass features like {meth}object.__init_subclass__ do not work with slotted classes.
The {attr}class.__subclasses__ attribute needs a garbage collection run (which can be manually triggered using {func}gc.collect), for the original class to be removed. See issue #407 for more details.
Pickling of slotted classes will fail if you define a class with missing attributes.

This situation can occur if you define an attrs.field(init=False) and don't set the attribute by hand before pickling.

field As the project name suggests, attrs is all about attributes. We especially tried to emphasize that we only care about attributes and not about the classes themselves -- because we believe the class belongs to the user.

This explains why the traditional API uses an {func}attr.ib (or attrib) function to define attributes and we still use the term throughout the documentation.

However, with the emergence of {mod}dataclasses, Pydantic, and other libraries, the term "field" has become a common term for a predefined attribute on a class in the Python ecosystem.

So with out new APIs, we've embraced it too by calling the function to create them {func}attrs.field, and use the term "field" throughout the documentation interchangeably.

6.3 KiB Raw Blame History

Glossary

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