| .. _extending: |
| |
| Extending |
| ========= |
| |
| Each ``attrs``-decorated class has a ``__attrs_attrs__`` class attribute. |
| It is a tuple of :class:`attr.Attribute` carrying meta-data about each attribute. |
| |
| So it is fairly simple to build your own decorators on top of ``attrs``: |
| |
| .. doctest:: |
| |
| >>> 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=None, init=True, convert=None, metadata=mappingproxy({}), type=None),) |
| |
| |
| .. warning:: |
| |
| The :func:`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 <https://en.wikipedia.org/wiki/Syntactic_sugar>`_ for:: |
| |
| def original_f(): |
| pass |
| |
| f = a(b(original_f)) |
| |
| |
| Wrapping the Decorator |
| ---------------------- |
| |
| A more elegant way can be to wrap ``attrs`` altogether and build a class `DSL <https://en.wikipedia.org/wiki/Domain-specific_language>`_ on top of it. |
| |
| An example for that is the package `environ_config <https://github.com/hynek/environ_config>`_ that uses ``attrs`` under the hood to define environment-based configurations declaratively without exposing ``attrs`` APIs at all. |
| |
| |
| Types |
| ----- |
| |
| ``attrs`` offers two ways of attaching type information to attributes: |
| |
| - `PEP 526 <https://www.python.org/dev/peps/pep-0526/>`_ annotations on Python 3.6 and later, |
| - and the *type* argument to :func:`attr.ib`. |
| |
| This information is available to you: |
| |
| .. doctest:: |
| |
| >>> import attr |
| >>> @attr.s |
| ... class C(object): |
| ... x: int = attr.ib() |
| ... y = attr.ib(type=str) |
| >>> attr.fields(C).x.type |
| <class 'int'> |
| >>> attr.fields(C).y.type |
| <class 'str'> |
| |
| Currently, ``attrs`` doesn't do anything with this information but it's very useful if you'd like to write your own validators or serializers! |
| |
| |
| .. _extending_metadata: |
| |
| 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. |
| |
| .. doctest:: |
| |
| >>> MY_TYPE_METADATA = '__my_type_metadata' |
| >>> |
| >>> def typed(cls, default=attr.NOTHING, validator=None, repr=True, cmp=True, hash=None, 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'> |