Bump numpydantic from 1.6.4 to 1.6.7

[dependabot]

Bumps numpydantic from 1.6.4 to 1.6.7.

Release notes

Sourced from numpydantic's releases.

v1.6.6

1.6.6 - 24-12-13

Bugfix

• #38, #39 -
  • JSON Schema generation failed when the dtype was embedded from dtypes that lack a __name__ attribute. An additional check was added for presence of __name__ when embedding.
  • NDArray types were incorrectly cached s.t. pipe-union dtypes were considered equivalent to Union[] dtypes. An additional tuple with the type of the args was added to the cache key to disambiguate them.
• #38, #40 -
  • Tuple dtypes were naively checked by just testing for whether the given dtype was contained by the tuple, ignoring special cases like string type checking. Tuple dtypes are now checked recursively with the same logic as all other type checking.
  • Zarr treats dtype=str as numpy type O - added special case when validating from JSON to cast to np.str_

Testing

• #39 - Test that all combinations of shapes, dtypes, and interfaces can generate JSON schema.
• #39 - Add python 3.13 to the testing matrix.
• #39 - Add an additional marks field to ValidationCase for finer-grained control over running tests.
• #40 - Explicitly test for np.str_ annotation dtypes alone and in tuples.

v1.6.5 - Bump minimum pydantic version

Bugfix

• #36, #37 - @​gerhardadler identifies that serialization context was only introduced in pydantic 2.7, minimum pydantic version has been updated accordingly

Changelog

Sourced from numpydantic's changelog.

1.6.7 - 25-01-23

UX

• #42, #43 - Use an ImportWarning rather than a UserWarning when a stubfile can't be generated and saved (e.g. due to a read-only filesystem or permissions error) so it only shows in CI and not at runtime.
• #44 - Zarr 3.0 changed a ton about how zarr works, so until we can adapt the interface, put an upper bound of <3.0.0 for zarr

1.6.6 - 24-12-13

Bugfix

• #38, #39 -
  • JSON Schema generation failed when the dtype was embedded from dtypes that lack a __name__ attribute. An additional check was added for presence of __name__ when embedding.
  • NDArray types were incorrectly cached s.t. pipe-union dtypes were considered equivalent to Union[] dtypes. An additional tuple with the type of the args was added to the cache key to disambiguate them.
• #38, #40 -
  • Tuple dtypes were naively checked by just testing for whether the given dtype was contained by the tuple, ignoring special cases like string type checking. Tuple dtypes are now checked recursively with the same logic as all other type checking.
  • Zarr treats dtype=str as numpy type O - added special case when validating from JSON to cast to np.str_

Testing

• #39 - Test that all combinations of shapes, dtypes, and interfaces can generate JSON schema.
• #39 - Add python 3.13 to the testing matrix.
• #39 - Add an additional marks field to ValidationCase for finer-grained control over running tests.
• #40 - Explicitly test for np.str_ annotation dtypes alone and in tuples.

1.6.5 - 24-12-04 - Bump Pydantic Minimum

Bugfix

• #36, #37 - @​gerhardadler identifies that serialization context was only introduced in pydantic 2.7, minimum pydantic version has been updated accordingly

Commits

• 700cd97 Merge pull request #43 from p2p-ld/ux-pyi-import-warning
• 4d0af25 changelog
• 3fdaef8 upper bound for zarr
• 8f46c9c bump version, changelog
• ee74149 use ImportWarning when ndarray.pyi stubfile can't be generated
• 62f307f Merge pull request #40 from p2p-ld/bugfix-numpy-str
• f90df30 bump version, move changelog into place
• 4fe3a72 changelog
• 616785e zarr roundtripping strings to/from json
• e942da4 recursively validate tuples instead of simple containment checking
• Additional commits viewable in compare view

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