nptyping

💡 Type hints for NumPy
💡 Type hints for pandas.DataFrame
💡 Extensive dynamic type checks for dtypes shapes and structures

Example of a hinted numpy.ndarray:

>>> from nptyping import NDArray, Int, Shape

>>> arr: NDArray[Shape["2, 2"], Int]

Example of a hinted pandas.DataFrame:

>>> from nptyping import DataFrame, Structure as S

>>> df: DataFrame[S["name: Str, x: Float, y: Float"]]

⚠️pandas.DataFrame is not yet supported on Python 3.11.

Installation

Command	Description
`pip install nptyping`	Install the basics
`pip install nptyping[pandas]`	Install with pandas extension (⚠️Python 3.10 or lower)
`pip install nptyping[complete]`	Install with all extensions

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

NumPy 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

Subarrays can be expressed with a shape expression between square brackets:

>>> Structure["name: Int[3, 3]"]
Structure['name: Int[3, 3]']

NumPy 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

Pandas DataFrames

Pandas DataFrames can be expressed with Structure also. To make it more concise, you may want to alias Structure.

>>> from nptyping import DataFrame, Structure as S

>>> df: DataFrame[S["x: Float, y: Float"]]

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.
License
If you want to check out how open source this library is.

Metadata

Release files for nptyping 2.4.1

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 2.4.1
File	Size	Uploaded
nptyping-2.4.1.tar.gz	20.1 kB	Nov 16, 2022	Details

Built distribution (wheel)

Table of built distributions (wheels) for nptyping 2.4.1
File	Interpreter	ABI	Platform	Reset
nptyping-2.4.1-py3-none-any.whl 36.0 kB Nov 16, 2022	Python 3	none	any	Details

Total release size: 56.1 kB

Release files / nptyping-2.4.1.tar.gz

Download URL	nptyping-2.4.1.tar.gz
Size	20.1 kB
Tags	Source
SHA-256 checksum How to use checksums	`57ba684ee5fc5eb681ee04270ee94adb879e4372ce6b640defa08ace8e1df295`
BLAKE2b-256 checksum How to use checksums	`6599fbc6c585dfef7803886a137820cc557e54472dcbf1c2ef34e033640964e9`
Upload date	Nov 16, 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/2.28.1 requests-toolbelt/0.9.1 urllib3/1.26.12 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.5 CPython/3.10.0`

Release files / nptyping-2.4.1-py3-none-any.whl

Download URL	nptyping-2.4.1-py3-none-any.whl
Size	36.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`23e8164b1e2c55e872f392ca7516b9b1b0cb400b03b70accaa63998b4106b0b3`
BLAKE2b-256 checksum How to use checksums	`b2c1e6f8c5f28f9b3bdb5c9c1d349a51941a30f90347b82bd5594363e81cf3ff`
Upload date	Nov 16, 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/2.28.1 requests-toolbelt/0.9.1 urllib3/1.26.12 tqdm/4.63.0 importlib-metadata/4.11.3 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.5 CPython/3.10.0`