**FastAPI** ile bir *path operation* oluşturduğunuzda, normalde ondan herhangi bir veri döndürebilirsiniz: bir `dict`, bir `list`, bir Pydantic model, bir veritabanı modeli vb.

Bir [Response Model](../tutorial/response-model.md) deklare ederseniz, FastAPI veriyi Pydantic kullanarak JSON'a serialize etmek için bunu kullanır.

from fastapi.openapi.models import SecurityBase as SecurityBaseModel


class SecurityBase:
    model: SecurityBaseModel

Çıkış verisi için de model config'inde `ser_json_bytes` ile `bytes` alanları kullanabilirsiniz; Pydantic JSON response üretirken bytes'ı base64 olarak serialize eder.

{* ../../docs_src/json_base64_bytes/tutorial001_py310.py ln[1:2,12:16,29,38:41] hl[16] *}

## Giriş ve Çıkış Verisi için Pydantic `bytes` { #pydantic-bytes-for-input-and-output-data }

Here are several ways to do it.

## Extra JSON Schema data in Pydantic models { #extra-json-schema-data-in-pydantic-models }

You can declare `examples` for a Pydantic model that will be added to the generated JSON Schema.

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

That extra info will be added as-is to the output **JSON Schema** for that model, and it will be used in the API docs.

        <artifactId>modello-maven-plugin</artifactId>
        <configuration>
          <version>1.2.0</version>
          <models>
            <model>../../api/maven-api-cli/src/main/mdo/core-extensions.mdo</model>
          </models>
          <templates>
            <template>reader-stax.vm</template>
            <template>writer-stax.vm</template>
          </templates>
          <params>

その動作と、必要に応じての変更方法を見ていきます。

## 入出力のPydanticモデル { #pydantic-models-for-input-and-output }

次のようにデフォルト値を持つ Pydantic モデルがあるとします。

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### 入力用モデル { #model-for-input }

このモデルを次のように入力として使うと:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

* data validation
* data serialization
* data documentation, etc.

This works the same way as with Pydantic models. And it is actually achieved in the same way underneath, using Pydantic.

/// info

Keep in mind that dataclasses can't do everything Pydantic models can do.

So, you might still need to use Pydantic models.

Es verbessert die Editor-Unterstützung für Pydantic-Modelle, mit:

* Code-Vervollständigung
* Typüberprüfungen
* Refaktorisierung
* Suche
* Inspektionen

///

## Das Modell verwenden { #use-the-model }

Innerhalb der Funktion können Sie alle Attribute des Modellobjekts direkt verwenden:

{* ../../docs_src/body/tutorial002_py310.py *}

        }

        return false;
    }

    /**
     * Checks if a model version is eligible for inference optimizations.
     * Models 4.0.0+ are eligible (4.0.0 has limited inference, 4.1.0+ has full inference).
     *
     * @param modelVersion the model version to check
     * @return true if eligible for inference
     */

/**
 * A test which demonstrates maven's recursive inheritance where
 * a distinct value is taken from each parent contributing to
 * the final model of the project being assembled. There is no
 * overriding going on amongst the models being used in this test:
 * each model in the lineage is providing a value that is not present
 * anywhere else in the lineage. We are just making sure that values