英文:
Type inference issue in Pylance for a variable of Union type
问题
我正在编写一个根据参数是标量还是NumPy数组而具有不同行为的函数。然而，我遇到了以下两个类型错误，我不知道如何解决：
-
表达式类型为"generic | bool | int | float | complex | str | bytes | memoryview"不能赋值给返回类型"float"。
类型"generic | bool | int | float | complex | str | bytes | memoryview"不能赋值给类型"float"。
"bytes"与"float"不兼容。Pylance报告一般类型问题。 -
类型"float"上未定义"getitem"方法。Pylance报告一般类型问题。
我该如何让Pylance知道，如果代码达到if语句内的表达式，x应该是一个float，如果达到else表达式，x应该是一个NumPy数组？
示例代码：
import numpy as np
import numpy.typing as npt
def func(x: float | npt.NDArray[np.float64]) -> float:
if np.isscalar(x):
return x # 错误1）
else:
return x[0] # 错误2）
def main():
x = 0.4
print(func(x))
if __name__ == "__main__":
main()
英文:
I'm writing a function with different behaviors depending on whether the argument is a scalar or a NumPy array. However, I'm getting the following two typing errors that I don't know how to solve:
Expression of type "generic | bool | int | float | complex | str | bytes | memoryview" cannot be assigned to return type "float"PylancereportGeneralTypeIssues
Type "generic | bool | int | float | complex | str | bytes | memoryview" cannot be assigned to type "float"
"bytes" is incompatible with "float""__ getitem __" method not defined on type "float"PylancereportGeneralTypeIssues**.
How can I let Pylance know that if the code reaches the expressions inside the if statement x should be a float, and if it reaches the else expresssions x should be a NumPy array?
Example code:
import numpy as np
import numpy.typing as npt
def func(x: float | npt.NDArray[np.float64]) -> float:
if np.isscalar(x):
return x # Error 1)
else:
return x[0] # Error 2)
def main():
x = 0.4
print(func(x))
if __name__ == "__main__":
main()
答案1
得分: 1
一种可能性是添加一个assert或cast来强制将其视为浮点数。以下任何一种方法都可以工作：
assert isinstance(x, float)
x = cast(float, x)
x = float(x) # type: ignore
总之：
def func(x: float | npt.NDArray[np.float64]) -> float:
if np.isscalar(x):
assert isinstance(x, float)
return x
else:
assert not isinstance(x, float)
return x[0]
...虽然更直接的方式可能是：
def func(x: float | npt.NDArray[np.float64]) -> float:
return x if isinstance(x, float) else x[0]
...除非您依赖于np.isscalar执行与这些类型签名所建议的不同的操作。
英文:
One possibility is to add an assert or a cast to force it to be treated as a float. Any of the following will work:
assert isinstance(x, float)
x = cast(float, x)
x = float(x) # type: ignore
All together:
def func(x: float | npt.NDArray[np.float64]) -> float:
if np.isscalar(x):
assert isinstance(x, float)
return x
else:
assert not isinstance(x, float)
return x[0]
...although, more direct would have been:
def func(x: float | npt.NDArray[np.float64]) -> float:
return x if isinstance(x, float) else x[0]
...unless you're relying upon np.isscalar to do something other than what these type signatures suggest.
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