numpy-typing-compat
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.
[!TIP]
numpy-typing-compatis intended as a helper package for theoptypelibrary, which provides high-level typing utilities for annotating NumPy operations. In most situations, it is recommended to useoptypeinstead ofnumpy-typing-compat. See theoptype.numpydocumentation for more details.
Installation and Versioning
The numpy-typing-compat packages are available on PyPI and conda-forge.
Modern package managers such as uv and
pixi will automatically install the
appropriate version of numpy-typing-compat that matches your installed NumPy version,
in order to satisfy the numpy dependency restrictions of numpy-typing-compat.
[!WARNING] Legacy package managers such as
pipdon't always respect dependency restrictions. Runningpip install --upgrade numpywill not automatically upgradenumpy-typing-compatto the correct version. If for some reason you need to usepip, then be sure to manually install the correct version ofnumpy-typing-compatthat matches your installed NumPy version. Runningpip checkwill tell you whether the installednumpy-typing-compatandnumpyversions are compatible.
To illustrate, the numpy-typing-compat==20250818.2.1 distribution of release v20250818
specifies numpy>=2.1,<2.2 as a required dependency. Modern package managers will
ensure that these dependency restrictions are satisfied. That way, if you upgrade
numpy from 2.1 to 2.3 (e.g. by running uv sync --upgrade) then uv will also
automatically look for a version of numpy-typing-compat that satisfies the new numpy
version, which for this example would be numpy-typing-compat==20250818.2.3.
| numpy-typing-compat | NumPy | Python |
|---|---|---|
20251206.2.0 |
>=2.0,<2.1 |
>=3.10 |
20251206.2.1 |
>=2.1,<2.2 |
>=3.10 |
20251206.2.2 |
>=2.2,<2.3 |
>=3.10 |
20251206.2.3 |
>=2.3,<2.4 |
>=3.11 |
20251206.2.4 |
>=2.4,<2.5 |
>=3.11 |
Reference
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.*.
ABCPolyBase
In NumPy 2.1, the numpy.polynomial._polybase.ABCPolyBase was made into a generic type,
and in NumPy 2.2 the type parameter was made optional. This can be problematic on
numpy==2.1.* if you also require support for numpy < 2.1.
To work around this, the numpy_typing_compat.ABCPolyBase is a type alias for
numpy.polynomial._polybase.ABCPolyBase[LiteralString | None] on numpy==2.1.*, and
a direct re-export of numpy.polynomial._polybase.ABCPolyBase otherwise. This way,
type checkers (when configured in strict mode) won't report an error on numpy==2.1.*
when using ABCPolyBase. Note that numpy_typing_compat.ABCPolyBase does not accept a
type parameter, even on numpy >= 2.1, for the sake of consistency.
LiteralTrue and LiteralFalse
In NumPy 2.2, the np.bool scalar type became a generic type that accepts a type
parameter of either True or False. For compatibility with numpy < 2.2, the
numpy_typing_compat.LiteralTrue and numpy_typing_compat.LiteralFalse types are
provided. These are type aliases for Literal[True] and Literal[False] on
numpy < 2.2, and Literal[True] | np.bool[Literal[True]] and
Literal[False] | np.bool[Literal[False]] on numpy >= 2.2, respectively.
Version constants
The following low-level boolean version constants are available:
| Constant | True when |
|---|---|
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 |
NUMPY_GE_2_4 |
numpy >= 2.4 |
Each constant is typed as Literal[True] or Literal[False] depending on your NumPy
version, so that static type-checkers are able to understand the NumPy version being
used.
[!WARNING] At the moment, mypy and pyright only have limited support for
Literaltype conditions, and will not treatif NUMPY_GE_2_0: ...in the same way asif sys.version_info >= (3, 12): ...orif sys.platform == "win32": ....
2 maintainers
Release files for numpy-typing-compat 20260602.2.5
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| numpy_typing_compat-20260602.2.5.tar.gz | 4.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| numpy_typing_compat-20260602.2.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.5 kB
Release files / numpy_typing_compat-20260602.2.5.tar.gz
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