attrs/docs/how-does-it-work.rst

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.. _how:
How Does It Work?
=================
``attrs`` certainly isn't the first library that aims to simplify class definition in Python.
But its **declarative** approach combined with **no runtime overhead** lets it stand out.
Once you apply the ``@attr.s`` decorator to a class, ``attrs`` searches the class object for instances of ``attr.ib``\ s.
Internally they're a representation of the data passed into ``attr.ib`` along with a counter to preserve the order of the attributes.
In order to ensure that sub-classing works as you'd expect it to work, ``attrs`` also walks the class hierarchy and collects the attributes of all super-classes.
Please note that ``attrs`` does *not* call ``super()`` *ever*.
It will write dunder methods to work on *all* of those attributes which also has performance benefits due to less function calls.
Once ``attrs`` knows what attributes it has to work on, it writes the requested dunder methods and attaches them to your class.
To be very clear: if you define a class with a single attribute without a default value, the generated ``__init__`` will look *exactly* how you'd expect:
.. doctest::
>>> import attr, inspect
>>> @attr.s
... class C:
... x = attr.ib()
>>> print(inspect.getsource(C.__init__))
def __init__(self, x):
self.x = x
<BLANKLINE>
No magic, no meta programming, no expensive introspection at runtime.
****
Everything until this point happens exactly *once* when the class is defined.
As soon as a class is done, it's done.
And it's just a regular Python class like any other, except for a single ``__attrs_attrs__`` attribute that can be used for introspection or for writing your own tools and decorators on top of ``attrs`` (like :func:`attr.asdict`.
And once you start instantiating your classes, ``attrs`` is out of your way completely.
This **static** approach was very much a design goal of ``attrs`` and what I strongly believe makes it distinct.