Improve dataclasses documentation #10686
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docs/concepts/dataclasses.md
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| behavior of stdlib dataclasses may prevail. For example, any extra fields present on a Pydantic dataclass with | ||
| [`extra`][pydantic.config.ConfigDict.extra] set to `'allow'` are omitted in the dataclass' string representation. | ||
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| ## Nested dataclasses |
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Can we simplify this section and the following one with a single Similarly to Pydantic models, nested dataclasses and generics are supported (and we refer to the relevant model documentation)? Imo the added value is quite low here, we would expect the examples to work anyway
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I'm fine with this as long as we link to model docs. Maybe we could add a few other notes as well like json schema, etc.
| validation will be applied (and the [configuration](#dataclass-config) stays the same). This means that using a stdlib or a Pydantic | ||
| dataclass as a field annotation is functionally equivalent. | ||
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| ```py |
CodSpeed Performance ReportMerging #10686 will not alter performanceComparing Summary
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| When you initialize a dataclass, it is possible to execute code *before* or *after* validation | ||
| with the help of the [`@model_validator`](validators.md#model-validators) decorator `mode` parameter. | ||
| Validators also work with Pydantic dataclasses: |
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Example below moved from the validators.md file
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docs/concepts/dataclasses.md
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| behavior of stdlib dataclasses may prevail. For example, any extra fields present on a Pydantic dataclass with | ||
| [`extra`][pydantic.config.ConfigDict.extra] set to `'allow'` are omitted in the dataclass' string representation. | ||
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| ## Nested dataclasses |
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I'm fine with this as long as we link to model docs. Maybe we could add a few other notes as well like json schema, etc.
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Change Summary
Closes #10679 along the way
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