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update changelog, bump version
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## 1.*
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### 1.3.1 - 24-08-12 - Allow arbitrary dtypes, pydantic models as dtypes
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Previously we would only allow dtypes if we knew for sure that there was some
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python base type to generate a schema with.
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That seems overly restrictive, so relax the requirements to allow
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any type to be a dtype. If there are problems with serialization (we assume there will)
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or handling the object in a given array framework, we leave that up to the person
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who declared the model to handle :). Let people break things and have fun!
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Also support the ability to use a pydantic model as the inner type, which works
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as expected because pydantic already knows how to generate a schema from its own models.
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Only one substantial change, and that is a `get_object_dtype` method which
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interfaces can override if there is some fancy way they have of getting
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types/items from an object array.
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### 1.3.0 - 24-08-05 - Better string dtype handling
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API Changes:
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[project]
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name = "numpydantic"
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version = "1.3.0"
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version = "1.3.1"
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description = "Type and shape validation and serialization for numpy arrays in pydantic models"
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authors = [
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{name = "sneakers-the-rat", email = "sneakers-the-rat@protonmail.com"},
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