Extending¶
Each attrs
-decorated class has a __attrs_attrs__
class attribute.
It is a tuple of attr.Attribute
carrying meta-data about each attribute.
So it is fairly simple to build your own decorators on top of attrs
:
>>> import attr
>>> def print_attrs(cls):
... print(cls.__attrs_attrs__)
>>> @print_attrs
... @attr.s
... class C(object):
... a = attr.ib()
(Attribute(name='a', default=NOTHING, validator=None, repr=True, cmp=True, hash=True, init=True, convert=None, metadata=mappingproxy({})),)
Warning
The attr.s()
decorator must be applied first because it puts __attrs_attrs__
in place!
That means that is has to come after your decorator because:
@a
@b
def f():
pass
is just syntactic sugar for:
def original_f():
pass
f = a(b(original_f))
Metadata¶
If you’re the author of a third-party library with attrs
integration, you may want to take advantage of attribute metadata.
Here are some tips for effective use of metadata:
Try making your metadata keys and values immutable. This keeps the entire
Attribute
instances immutable too.To avoid metadata key collisions, consider exposing your metadata keys from your modules.:
from mylib import MY_METADATA_KEY @attr.s class C(object): x = attr.ib(metadata={MY_METADATA_KEY: 1})
Metadata should be composable, so consider supporting this approach even if you decide implementing your metadata in one of the following ways.
Expose
attr.ib
wrappers for your specific metadata. This is a more graceful approach if your users don’t require metadata from other libraries.>>> MY_TYPE_METADATA = '__my_type_metadata' >>> >>> def typed(cls, default=attr.NOTHING, validator=None, repr=True, cmp=True, hash=True, init=True, convert=None, metadata={}): ... metadata = dict() if not metadata else metadata ... metadata[MY_TYPE_METADATA] = cls ... return attr.ib(default, validator, repr, cmp, hash, init, convert, metadata) >>> >>> @attr.s ... class C(object): ... x = typed(int, default=1, init=False) >>> attr.fields(C).x.metadata[MY_TYPE_METADATA] <class 'int'>