numpy-typing-compat 1.25.20250725

NumPy version information that type-checkers understand

numpy-typing-compat

NumPy version information that type-checkers understand

Overview

This package provides version-specific boolean constants that allow library authors to write NumPy-version-dependent static type annotations. Similar to how you might use if sys.version_info >= (3, 12): for Python version checks, numpy-typing-compat enables static type-checkers to understand which NumPy version is being used and apply appropriate type annotations.

Use Case

This package is particularly useful for libraries that need to support multiple NumPy versions, for example because they follow SPEC 0. However, there may have been changes in NumPy that affect type annotations. For instance, the numpy.exceptions module was introduced in NumPy 1.25, and contains the exceptions that were previously in the global numpy namespace. In NumPy 2.0, these exceptions were removed from the global namespace. So if you support <1.25 and also >=2.0, you will need to conditionally import these exceptions to ensure compatibility across versions.

from numpy_typing_compat import NUMPY_GE_1_25

if NUMPY_GE_1_25:
    from numpy.exceptions import AxisError
else:
    from numpy import AxisError

Type checkers like mypy, pyright, and basedpyright understand these patterns and will apply the correct type annotations based on the installed NumPy version.

Installation

pip install numpy-typing-compat

The package automatically selects the appropriate version constants based on your installed NumPy version. It does so by requiring a specific version of NumPy in its pyproject.toml file, so that your package manager will install the correct version of numpy-typing-compat that matches the NumPy version you have installed.

For example, if you have numpy==2.1.3 pinned in your pyproject.toml, and you run uv add numpy-typing-compat, it will install numpy-typing-compat==2.1.*. That specific version has NUMPY_GE_2_1 = True, and NUMPY_GE_2_2 = False set.

Note that numpy-typing-compat does not import numpy, and instead relies on the package manager to install the correct version of numpy-typing-compat that matches the installed NumPy version.

Reference

Array API

Additionally, the package provides a numpy_typing_compat.array_api namespace that's a re-export of the numpy.array_api module on numpy < 2.0, or the main numpy module on numpy >= 2.0. Note that the numpy.array_api module was introduced in numpy >= 1.23, so it isn't available in numpy-typing-compat==1.22.*.

numpy.long

NumPy 2.0 introduced the new long and ulong scalar types, which are not available in numpy < 2.0, and instead went by the names int_ and uint (which in numpy >= 2.0 are aliases for intp and uintp). If you need to support both NumPy versions, you can use the long and ulong types from numpy_typing_compat, which on numpy < 2.0 are aliases for np.int_ and np.uint, and on numpy >= 2.0 are re-exports of np.long and np.ulong.

numpy.dtypes.StringDType

In NumPy 2.0, the numpy.dtypes.StringDType was introduced, but it wasn't until NumPy 2.1 that it was also available in the numpy stubs. The numpy_typing_compat.StringDType is a re-export of numpy.dtypes.StringDType on numpy >= 2.1, and an alias of np.dtype[Never] on numpy < 2.1. This allows type checkers to also accept StringDType as a valid type on numpy == 2.0.*.

Version constants

The following low-level boolean version constants are available:

Constant	True when
NUMPY_GE_1_22	numpy >= 1.22
NUMPY_GE_1_23	numpy >= 1.23
NUMPY_GE_1_25	numpy >= 1.25
NUMPY_GE_2_0	numpy >= 2.0
NUMPY_GE_2_1	numpy >= 2.1
NUMPY_GE_2_2	numpy >= 2.2
NUMPY_GE_2_3	numpy >= 2.3

Each constant is typed as Literal[True] or Literal[False] depending on your NumPy version, allowing type checkers to perform accurate type narrowing.