Proposal: Programmatically create types

This proposal is aimed at solving two related problem. First, when defining a multi-ary operator on Numpy arrays, e.g., leaky integral, then you ideally want to bake in Numpy type promotion rules. However, even Numpy doesn't use its own type promotion rules in its type annotations.

So, my suggestion is the following:

from typing import SyntheticType

def ResultType(*args: Any) -> SyntheticType[DType]:
  return result_type(*args)  # Something like this, but would have to deal with e.g., numpy.ndarray[typing.Any, numpy.dtype[numpy.floating[typing.Any]]]

# Then...
    @overload
    def __add__(self: T, other: U) -> NDArray[ResultType[T, U]]: ...  # type: ignore[misc]

The type checker could be called with a special argument, like --create_synthetic_stubs. This would

• Run type checking and collect a list of unique argument tuples to synthetic type functions like ResultType.
• Start a Python interpreter and call the synthetic type functions using the the arguments (which are Python objects representing types, e.g., T=float and U=numpy.ndarray[typing.Any, numpy.dtype[numpy.floating[typing.Any]]]).
• It would then write the results to some pyi file in some canonical table-like format, like:
  `ResultType: SyntheticTypeMapping = {(float, float): float, ...}

The table could either be just stored in the cache. Users of the library would have to generate this file, which means type checkers run code in the library.

The other problem this solves is one that I would like to annotate dataclasses whose elements can be None or int besides whatever they've specified as. See here for a description as to why. It would be pretty easy to code a Python transformation from a dataclass type to a new dataclass type with the transformed field types.

I realize this is pretty extreme, but the payoff would be commensurate.

从提案以及其中链接的 tjax leaky_integral.py、NumPy 类型注解和 JAX pytrees 参考资料开始。审查建议的 SyntheticType 工作流、type-checker 收集步骤、生成的 stub 格式和 dataclass 转换，然后确定范围是否能够形成一份达成共识的设计。完成的标准应是确定方向或规范，而不是完成一个孤立的小改动。