nptyping

💡 Type hints for NumPy
💡 Extends numpy.typing
💡 Extensive dynamic type checks for dtypes and shapes of arrays

Example of a hinted function with nptyping:

>>> from nptyping import NDArray, Int, Shape

>>> def func(arr: NDArray[Shape["2, 2"], Int]) -> None:
...     pass

Installation

pip install nptyping

Instance checking

Example of instance checking:

>>> import numpy as np

>>> isinstance(np.array([[1, 2], [3, 4]]), NDArray[Shape["2, 2"], Int])
True

>>> isinstance(np.array([[1., 2.], [3., 4.]]), NDArray[Shape["2, 2"], Int])
False

>>> isinstance(np.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(np.array([1]), NDArray[Shape["1"], Int])
True

Structured arrays

You can also express structured arrays using nptyping.Structure:

>>> from nptyping import Structure

>>> Structure["name: Str, age: Int"]
Structure['age: Int, name: Str']

Here is an example to see it in action:

>>> from typing import Any
>>> import numpy as np
>>> from nptyping import NDArray, Structure

>>> arr = np.array([("Peter", 34)], dtype=[("name", "U10"), ("age", "i4")])
>>> isinstance(arr, NDArray[Any, Structure["name: Str, age: Int"]])
True

Record arrays

The recarray is a specialization of a structured array. You can use RecArray to express them.

>>> from nptyping import RecArray

>>> arr = np.array([("Peter", 34)], dtype=[("name", "U10"), ("age", "i4")])
>>> rec_arr = arr.view(np.recarray)
>>> isinstance(rec_arr, RecArray[Any, Structure["name: Str, age: Int"]])
True

More examples

Here is an example of a rich expression that can be done 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.

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.

Metadata

Release files for nptyping 2.1.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for nptyping 2.1.3
File	Size	Uploaded
nptyping-2.1.3.tar.gz	18.0 kB	Jun 19, 2022	Details

Built distribution (wheel)

Table of built distributions (wheels) for nptyping 2.1.3
File	Interpreter	ABI	Platform	Reset
nptyping-2.1.3-py3-none-any.whl 31.8 kB Jun 19, 2022	Python 3	none	any	Details

Total release size: 49.8 kB

Release files / nptyping-2.1.3.tar.gz

Download URL	nptyping-2.1.3.tar.gz
Size	18.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`d2a8be7b55b81880f07bd74a09f5c12d48c896e8a756d75ca94eb62cf0d82c8f`
BLAKE2b-256 checksum How to use checksums	`785eb7f5f02349440479e39d728bbcc9063e66df0e7c0c7ea77a7b992ae0b900`
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Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.0`

Release files / nptyping-2.1.3-py3-none-any.whl

Download URL	nptyping-2.1.3-py3-none-any.whl
Size	31.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f12131d8b4ef843085bd06282d44763cf48b54a87cbe713e42f3367484be0abc`
BLAKE2b-256 checksum How to use checksums	`a3a650e0fcf477c7cc065b08fb231cb049ab1b3d73c87bceaa32e720a01328dd`
Upload date	Jun 19, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.10.0`