Add more unit tests, use DataclassValidatorFieldException#5
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JGaukrogers
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Mar 31, 2026
flauschzelle
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Apr 2, 2026
ninanomenon
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Apr 7, 2026
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| assert type(fields['regular_required'].metadata.get('validator')) is StringValidator | ||
| assert type(fields['regular_optional'].metadata.get('validator')) is StringValidator | ||
| assert type(fields['explicit_field'].metadata.get('validator')) is StringValidator | ||
| assert type(fields['filter1'].metadata.get('validator')) is IntegerValidator | ||
| assert type(fields['filter2'].metadata.get('validator')) is IntegerValidator | ||
| assert type(fields['filter3'].metadata.get('validator')) is IntegerValidator | ||
| assert type(fields['filter4'].metadata.get('validator')) is MultiSelectIntegerValidator | ||
| assert type(fields['filter5'].metadata.get('validator')) is BooleanValidator |
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I wonder if isinstance is more correct here
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In general it's better to use isinstance() because it works with subtypes as well, yes. It's less strict.
But here in the unit tests, I don't really see a reason to use a less strict test. The validators should always have the exact types that we used in the dataclass definition. Otherwise something is happening that somehow modifies the validators, which would be unexpected behavior.
ninanomenon
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Apr 7, 2026
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This PR adds some more unit tests to the project. I figured it makes sense to have some more unit tests before updating to validataclass 0.12 and changing several things related to that.
I also noticed an inconsistency between the
@search_query_dataclassand@validataclassdecorators, where the former didn't use theDataclassValidatorFieldExceptionclass for errors that are similar or the same as those in the@validataclassdecorator, so I fixed that. I don't consider this a breaking change, because it's just a different exception class for errors that effectively mean your code isn't valid.