Type hints for NumPy.
Project description
⚠ This describes the 2.0.0 alpha release.
For the latest stable release, pick 1.4.4
💡 Type hints for NumPy
💡 Extensive dynamic type checks for dtypes and shapes of arrays
💡 Limited static type checks with MyPy
Example of a hinted function with nptyping
:
>>> from nptyping import NDArray, Int, Shape
>>> def func(arr: NDArray[Shape["2, 2"], Int]) -> None:
... pass
Example of instance checking:
>>> from numpy import array
>>> isinstance(array([[1, 2], [3, 4]]), NDArray[Shape["2, 2"], Int])
True
>>> isinstance(array([[1., 2.], [3., 4.]]), NDArray[Shape["2, 2"], Int])
False
>>> isinstance(array([1, 2, 3, 4]), NDArray[Shape["2, 2"], Int])
False
nptyping
also provides assert_isinstance
. In contrast to assert isinstance(...)
, this won't cause IDEs or MyPy
complaints. Here is an example:
>>> from nptyping import assert_isinstance
>>> assert_isinstance(array([1]), NDArray[Shape["1"], Int])
True
Here is an example of how detailed expressions can become with nptyping
:
def plan_route(locations: NDArray[Shape["[from, to], [x, y]"], Float]) -> NDArray[Shape["* stops, [x, y]"], Float]:
...
More examples can be found in the documentation.
Installation
pip install nptyping
Documentation
-
User documentation
The place to go if you are using this library. -
Release notes
To see what's new, check out the release notes. -
Contributing
If you're interested in developing along, find the guidelines here. -
Licence
If you want to check out how open source this library is.
Project details
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