Type Annotations

attrs comes with first class support for type annotations for both Python 3.6 (PEP 526) and legacy syntax.

On Python 3.6 and later, you can even drop the attr.ibs if you’re willing to annotate all attributes. That means that on modern Python versions, the declaration part of the example from the README can be simplified to:

>>> import attr
>>> import typing

>>> @attr.s(auto_attribs=True)
... class SomeClass:
...     a_number: int = 42
...     list_of_numbers: typing.List[int] = attr.Factory(list)

>>> sc = SomeClass(1, [1, 2, 3])
>>> sc
SomeClass(a_number=1, list_of_numbers=[1, 2, 3])
>>> attr.fields(SomeClass).a_number.type
<class 'int'>

You will still need attr.ib for advanced features, but not for the common cases.

One of those features are the decorator-based features like defaults. It’s important to remember that attrs doesn’t do any magic behind your back. All the decorators are implemented using an object that is returned by the call to attr.ib.

Attributes that only carry a class annotation do not have that object so trying to call a method on it will inevitably fail.

Please note that types – however added – are only metadata that can be queried from the class and they aren’t used for anything out of the box!

Because Python does not allow references to a class object before the class is defined, types may be defined as string literals, so-called forward references. Also, starting in Python 3.10 (PEP 526) all annotations will be string literals. When this happens, attrs will simply put these string literals into the type attributes. If you need to resolve these to real types, you can call attr.resolve_types which will update the attribute in place.

In practice though, types show their biggest usefulness in combination with tools like mypy or pytype that both have dedicated support for attrs classes.


While having a nice syntax for type metadata is great, it’s even greater that mypy as of 0.570 ships with a dedicated attrs plugin which allows you to statically check your code.

Imagine you add another line that tries to instantiate the defined class using SomeClass("23"). Mypy will catch that error for you:

$ mypy t.py
t.py:12: error: Argument 1 to "SomeClass" has incompatible type "str"; expected "int"

This happens without running your code!

And it also works with both Python 2-style annotation styles. To mypy, this code is equivalent to the one above:

class SomeClass(object):
    a_number = attr.ib(default=42)  # type: int
    list_of_numbers = attr.ib(factory=list, type=typing.List[int])

The addition of static types is certainly one of the most exciting features in the Python ecosystem and helps you writing correct and verified self-documenting code.

If you don’t know where to start, Carl Meyer gave a great talk on Type-checked Python in the Real World at PyCon US 2018 that will help you to get started in no time.