Vamos colocar esses dados primeiro no modelo `UserInDB` do Pydantic.

Você nunca deve salvar senhas em texto simples, portanto, usaremos o sistema de hashing de senhas (falsas).

Se as senhas não corresponderem, retornaremos o mesmo erro.

#### Hashing de senha

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.content-wrapper.iframe-mode .tab-loading{background-color:#343a40}.content-wrapper.kanban{height:1px}.content-wrapper.kanban .content{height:100%;overflow-x:auto;overflow-y:hidden}.content-wrapper.kanban .content .container,.content-wrapper.kanban .content .container-fluid,.content-wrapper.kanban .content .container-lg,.content-wrapper.kanban .content .container-md,.content-wrapper.kanban .content .container-sm,.content-wrapper.kanban .content .container-xl{width:-webkit-max-content;width:-moz-max-content;...

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*   `tf.experimental.StructuredTensor`

    *   Introduced `tf.experimental.StructuredTensor`, which provides a flexible
        and Tensorflow-native way to encode structured data such as protocol
        buffers or pandas dataframes.

*   `tf.keras`:

    *   Added method `get_metrics_result()` to `tf.keras.models.Model`.
        *   Returns the current metrics values of the model as a dict.

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