We can annotate variable-length homogeneous tuples using the … literal (aka Ellipsis) like this: def process_tuple(t: Tuple[str, …]): … or for Python3.9+ def process_tuple(t: tuple[str, …]): … After that, the errors should go away. From the docs: To specify a variable-length tuple of homogeneous type, use literal ellipsis, e.g. Tuple[int, …]. A plain Tuple is … Read more
What are variable annotations? Variable annotations are just the next step from # type comments, as they were defined in PEP 484; the rationale behind this change is highlighted in the respective section of PEP 526. So, instead of hinting the type with: primes = [] # type: List[int] New syntax was introduced to allow … Read more
You need to import the typing module. As per docs: The return type of generator functions can be annotated by the generic type Generator[yield_type, send_type, return_type] provided by typing.py module Try this way instead: from typing import Generator def generate() -> Generator[int, None, None]: for i in range(10): yield i The above will have the … Read more
Update Check recent numpy versions for a new typing module https://numpy.org/doc/stable/reference/typing.html#module-numpy.typing dated answer It looks like typing module was developed at: https://github.com/python/typing The main numpy repository is at https://github.com/numpy/numpy Python bugs and commits can be tracked at http://bugs.python.org/ The usual way of adding a feature is to fork the main repository, develop the feature till … Read more
Yes, you can use special documentation format for methods and their parameters so that PyCharm can know the type. Recent PyCharm version supports most common doc formats. For example, PyCharm extracts types from @param style comments. See also reStructuredText and docstring conventions (PEP 257). Another option is Python 3 annotations. Please refer to the PyCharm … Read more
When you specify cls: A, you’re saying that cls expects an instance of type A. The type hint to specify cls as a class object for the type A (or its subtypes) uses typing.Type. from typing import Type def process_any_subclass_type_of_A(cls: Type[A]): pass From The type of class objects : Sometimes you want to talk about … Read more
The former is correct, if arg accepts an instance of CustomClass: def FuncA(arg: CustomClass): # ^ instance of CustomClass In case you want the class CustomClass itself (or a subtype), then you should write: from typing import Type # you have to import Type def FuncA(arg: Type[CustomClass]): # ^ CustomClass (class object) itself Like it … Read more
Until Python 3.9 added support for type hinting using standard collections, you had to use typing.Tuple and typing.List if you wanted to document what type the contents of the containers needed to be: def f(points: Tuple[float, float]): return map(do_stuff, points) Up until Python 3.8, tuple and list did not support being used as generic types. … Read more
The prefered Syntax for a typed named tuple since 3.6 is from typing import NamedTuple class Point(NamedTuple): x: int y: int = 1 # Set default value Point(3) # -> Point(x=3, y=1) Edit Starting Python 3.7, consider using dataclasses (your IDE may not yet support them for static type checking): from dataclasses import dataclass @dataclass … Read more
According to PEP 526, this is not allowed: In addition, one cannot annotate variables used in a for or with statement; they can be annotated ahead of time, in a similar manner to tuple unpacking Annotate it before the loop: i: int for i in range(5): pass PyCharm 2018.1 and up now recognizes the type … Read more