Clarify validate_default and _Unset handling in usage docs and migration guide #6950
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benbenbang
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please review 🙏🏻 |
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Hello @dmontagu or @hramezani |
hramezani
reviewed
Aug 14, 2023
docs/usage/validators.md
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| @@ -266,7 +266,8 @@ print(context['logs']) | |||
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| Validators won't run when the default value is used. | |||
| This applies both to `@field_validator` validators and `Annotated` validators. | |||
| You can force them to run with `Field(validate_defaults=True)`, but you are generally better off using a `@model_validator(mode='before')`. | |||
| You can force them to run with `Field(validate_defaults=True)`. Setting `validate_default` to `True` has the closest behavior to using `always=True` in `validator` in pydantic v1. However, you are generally better off using a `@model_validator(mode='before')` where the function is called before the inner validator is called. | |||
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| You can force them to run with `Field(validate_defaults=True)`. Setting `validate_default` to `True` has the closest behavior to using `always=True` in `validator` in pydantic v1. However, you are generally better off using a `@model_validator(mode='before')` where the function is called before the inner validator is called. | |
| You can force them to run with `Field(validate_defaults=True)`. Setting `validate_default` to `True` has the closest behavior to using `always=True` in `validator` in Pydantic V1. However, you are generally better off using a `@model_validator(mode='before')` where the function is called before the inner validator is called. |
hramezani
reviewed
Aug 14, 2023
docs/migration.md
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| @@ -238,6 +238,10 @@ See [Model Config](usage/model_config.md) for more details. | |||
| for the annotated type will _also_ be applied even to defaults, not just the custom validators. For | |||
| example, despite the fact that the validator below will never error, the following code raises a `ValidationError`: | |||
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| !!! note | |||
| To avoid this, you can use the `validate_default` argument in the `Field` function. When set to `True`, it mimics the behavior of `always=True` in pydantic v1. However, the new way of using `validate_default` is encouraged as it provides more flexibility and control. | |||
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| To avoid this, you can use the `validate_default` argument in the `Field` function. When set to `True`, it mimics the behavior of `always=True` in pydantic v1. However, the new way of using `validate_default` is encouraged as it provides more flexibility and control. | |
| To avoid this, you can use the `validate_default` argument in the `Field` function. When set to `True`, it mimics the behavior of `always=True` in Pydantic V1. However, the new way of using `validate_default` is encouraged as it provides more flexibility and control. |
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Thanks @benbenbang for creating this PR 🙏 |
pydantic-hooky
bot
added
awaiting author revision
Thanks @hramezani for the review, gonna update it |
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@hramezani , all applied. please take a look when you get some time |
hramezani
approved these changes
Aug 14, 2023
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Change Summary
Clarify 'validate_default' and '_Unset' handling in usage docs and migration guide.
Description:
This PR aims to improve the clarity and understanding of Pydantic v2 documentation in the following ways:
validate_defaultdefault value clarification: The documentation for thevalidate_defaultparameter in the Field function is updated to specify that its default value isNone.Validatorusage: The documentation about the usage of validators, specifically with the default values, is updated. Added emphasis on how to mimic thealways=Truebehavior from Pydantic v1 usingvalidate_default=True. In migration guide: The migration guide is updated to include information about thevalidate_defaultparameter for that migrating from Pydantic v1 to v2._Unsetobjects: Added a note to the documentation to clarify that_Unsetobjects will be replaced by the corresponding value defined in the_DefaultValuesdictionary or default to None if no specific value is provided.These updates aim to make it easier for users to understand the changes in Pydantic v2 and how to effectively use the Field function and validators.
Related issue number
fix #6812
Checklist
Selected Reviewer: @dmontagu