Both typing.NamedTuple and dataclasses.dataclass use the somewhat beautiful PEP 526 variable notations at the class level:
@dataclasses.dataclass class Color: hue: int saturation: float lightness: float = 0.5 and class Color(typing.NamedTuple): hue: int saturation: float lightness: float = 0.5 I'm looking for guidance or workarounds for two issues that have arisen. First, the use of default values seems to completely preclude the use of __slots__. For example, this raises a ValueError: class A: __slots__ = ['x', 'y'] x: int = 10 y: int = 20 The second issue is that the different annotations give different signatures than would produced for manually written classes. It is unclear what the best practice is for where to put the annotations and their associated docstrings. In Pydoc for example, this class: class A: 'Class docstring. x is distance in miles' x: int y: int gives a different signature and docstring than for this class: class A: 'Class docstring' def __init__(self, x: int, y: int): 'x is distance in kilometers' pass or for this class: class A: 'Class docstring' def __new__(cls, x: int, y: int) -> A: '''x is distance in inches A is a singleton (once instance per x,y) ''' if (x, y) in cache: return cache[x, y] return object.__new__(cls, x, y) The distinction is important because the dataclass decorator allows you to suppress the generation of __init__ when you need more control than dataclass offers or when you need a __new__ method. I'm unclear on where the docstring and signature for the class is supposed to go so that we get useful signatures and matching docstrings. _______________________________________________ Python-Dev mailing list [email protected] https://mail.python.org/mailman/listinfo/python-dev Unsubscribe: https://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com