On Sun, Dec 17, 2017 at 8:22 AM, Guido van Rossum <gu...@python.org> wrote:
> On Sun, Dec 17, 2017 at 2:11 AM, Julien Salort <lis...@salort.eu> wrote:
>
>> Naive question from a lurker: does it mean that it works also if one
>> annotates with something that is not a type, e.g. a comment,
>>
>> @dataclass
>> class C:
>> a: "This represents the amplitude" = 0.0
>> b: "This is an offset" = 0.0
>
>
> I would personally not use the notation for this, but it is legal code.
> However static type checkers like mypy won't be happy with this.
>
Mypy definitely won't like that use of annotation, but documentation
systems might. For example, in a hover tooltip in an IDE/editor, it's
probably more helpful to see the descriptive message than "int" or "float"
for the attribute.
What about data that isn't built-in scalars? Does this look right to people
(and will mypy be happy with it)?
@dataclass
class C:
a:numpy.ndarray = numpy.random.random((3,3))
b:MyCustomClass = MyCustomClass("foo", 37.2, 1+2j)
I don't think those look terrible, but I think this looks better:
@dataclass
class C:
a:Infer = np.random.random((3,3))
b:Infer = MyCustomClass("foo", 37.2, 1+2j)
Where the name 'Infer' (or some other spelling) was a name defined in the
`dataclasses` module. In this case, I don't want to use `typing.Any` since
I really do want "the type of thing the default value has."
--
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from the bellies of the hungry; books from the hands of the
uneducated; technology from the underdeveloped; and putting
advocates of freedom in prisons. Intellectual property is
to the 21st century what the slave trade was to the 16th.
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