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Introduced workarounds for technical debt 251 #254

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db9f27b
Started workaround for skipped documentation tests bug.
KostaIlic2 Jan 10, 2026
12f005e
Completed the workaround. Improved comments.
KostaIlic2 Jan 10, 2026
7a01b84
Improving the workaround so it does not violate the style guide.
KostaIlic2 Jan 10, 2026
331df5f
Minor changes to minimize changes from the original version of the code.
KostaIlic2 Jan 10, 2026
95d08eb
Improved comments. Reordered some tests to match the original order t…
KostaIlic2 Jan 10, 2026
f2c0f64
Added a line per style guide check failure. Improved local variable n…
KostaIlic2 Jan 10, 2026
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1 change: 1 addition & 0 deletions docs/conf.py
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@bkeryan bkeryan Jan 14, 2026

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I don't think we need/want to run doctests through Sphinx. I assume you added this to enable the .. testsetup:: directive and that pytest supports it.

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@KostaIlic2 KostaIlic2 Jan 14, 2026

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@bkeryan, I suggest we look together at the root cause and a fix I'd like to propose for that before spending more time on this PR.

Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
"autoapi.extension",
"m2r2",
"sphinx.ext.autodoc",
"sphinx.ext.doctest",
"sphinx.ext.intersphinx",
"sphinx.ext.napoleon",
"sphinx.ext.viewcode",
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31 changes: 30 additions & 1 deletion src/nitypes/_arguments.py
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@bkeryan bkeryan Jan 14, 2026

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Does this issue only affect run_unit_tests_oldest_deps.yml? If so, I think disabling doctests on the command line in that workflow file would be a less obtrusive workaround. If --no-doctest-modules doesn't work, try -p no:doctest.

Original file line number Diff line number Diff line change
Expand Up @@ -16,14 +16,27 @@

# Some of these doctests use types introduced in NumPy 2.0 (np.long and np.ulong) or highlight
# formatting differences between NumPy 1.x and 2.x (e.g. dtype=int32, 1.23 vs. np.float64(1.23)).
__doctest_requires__ = {("arg_to_float", "is_dtype", "validate_dtype"): ["numpy>=2.0"]}
# The following line is commented out as workaround for technical debt #251.
# __doctest_requires__ = {("arg_to_float", "is_dtype", "validate_dtype"): ["numpy>=2.0"]}
# When the technical debt is resolved, uncomment the line above
# and remove testsetup blocks that include comments like the one below:
# # Workaround for technical debt #251: Skip doctest if numpy<2.0
# >>> pytest.skip("requires numpy>=2.0") if version_check else None # doctest: +SKIP


def arg_to_float(
arg_description: str, value: SupportsFloat | None, default_value: float | None = None
) -> float:
"""Convert an argument to a float.

.. testsetup::

# Workaround for technical debt #251: Skip doctest if numpy<2.0
import numpy as np
import pytest
numpy_version = tuple(map(int, np.__version__.split(".")[:2])) < (2, 0)
pytest.skip("requires numpy>=2.0") if numpy_version else None

>>> arg_to_float("xyz", 1.234)
1.234
>>> arg_to_float("xyz", 1234)
Expand Down Expand Up @@ -143,6 +156,14 @@ def is_dtype(dtype: npt.DTypeLike, supported_dtypes: tuple[npt.DTypeLike, ...])

Unlike :any:`numpy.isdtype`, this function supports structured data types.

.. testsetup::

# Workaround for technical debt #251: Skip doctest if numpy<2.0
import numpy as np
import pytest
numpy_version = tuple(map(int, np.__version__.split(".")[:2])) < (2, 0)
pytest.skip("requires numpy>=2.0") if numpy_version else None

>>> is_dtype(np.float64, (np.float64, np.intc, np.long,))
True
>>> is_dtype("float64", (np.float64, np.intc, np.long,))
Expand Down Expand Up @@ -172,6 +193,14 @@ def is_dtype(dtype: npt.DTypeLike, supported_dtypes: tuple[npt.DTypeLike, ...])
def validate_dtype(dtype: npt.DTypeLike, supported_dtypes: tuple[npt.DTypeLike, ...]) -> None:
"""Validate a dtype-like object against a tuple of supported dtype-like objects.

.. testsetup::

# Workaround for technical debt #251: Skip doctest if numpy<2.0
import numpy as np
import pytest
numpy_version = tuple(map(int, np.__version__.split(".")[:2])) < (2, 0)
pytest.skip("requires numpy>=2.0") if numpy_version else None

>>> validate_dtype(np.float64, (np.float64, np.intc, np.long,))
>>> validate_dtype("float64", (np.float64, np.intc, np.long,))
>>> validate_dtype(np.float64, (np.byte, np.short, np.intc, np.int_, np.long, np.longlong))
Expand Down
14 changes: 13 additions & 1 deletion src/nitypes/complex/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,14 @@

You can construct an array of complex integers from a sequence of tuples using :func:`numpy.array`:

.. testsetup::

# Workaround for technical debt #251: Skip doctest if numpy<2.0
import numpy as np
import pytest
numpy_version = tuple(map(int, np.__version__.split(".")[:2])) < (2, 0)
pytest.skip("requires numpy>=2.0") if numpy_version else None

>>> import numpy as np
>>> np.array([(1, 2), (3, 4)], dtype=ComplexInt32DType)
array([(1, 2), (3, 4)], dtype=[('real', '<i2'), ('imag', '<i2')])
Expand Down Expand Up @@ -127,4 +135,8 @@
from nitypes.complex._dtypes import ComplexInt32Base, ComplexInt32DType

__all__ = ["convert_complex", "ComplexInt32DType", "ComplexInt32Base"]
__doctest_requires__ = {".": ["numpy>=2.0"]}
# The following line is commented out as workaround for technical debt #251.
# __doctest_requires__ = {".": ["numpy>=2.0"]}
# When the technical debt is resolved, uncomment the line above
# and remove testsetup blocks that include comments like the one below:
# # Workaround for technical debt #251: Skip doctest if numpy<2.0