NumPy support

Install the optional extra:

python -m pip install "dataioc[numpy]"

Define an array type by subclassing DataNDArray:

from dataioc import DataIoC, DataNDArray


class SensorArray(DataNDArray):
    pass


container = DataIoC().with_data(
    SensorArray([1, 1, 1]),
    SensorArray[1]([2, 2, 2]),
)
assert container[SensorArray[1]].sum() == 6

Compatibility

The supported range is numpy>=1.26,<3. Python 3.9 supports NumPy 1.26 and 2.0; newer NumPy releases require newer Python versions. Package installers select a compatible release.

CI tests NumPy 1.26.0, the latest 1.26 release, 2.0.0, and the latest stable 2.x, alongside the locked dependencies across Python 3.9 through 3.14.

Array behavior

Operation	Behavior
Multiple input arrays	Check sample counts, then stack columns
Shape-preserving numerical ufunc	Retain the subclass when the result dtype is compatible
Multiple-output ufunc	Apply the subclass rule separately to each result
Explicit out or in-place operation	Preserve the output object's identity
Slicing or reshaping	Return a plain NumPy array
Scalar indexing or reduction	Follow NumPy's scalar conventions

Numerical promotion and overflow behavior follow the installed NumPy version, so result dtypes can differ between 1.x and 2.x.

Neither the core import nor from dataioc import * imports NumPy. Explicitly importing DataNDArray loads the optional integration; it requires NumPy to be installed.

See the API reference for signatures.