* Verwenden Sie die von Ihnen erstellten `templates`, um eine `TemplateResponse` zu rendern und zurückzugeben, übergeben Sie den Namen des Templates, das Requestobjekt und ein „Kontext“-Dictionary mit Schlüssel-Wert-Paaren, die innerhalb des Jinja2-Templates verwendet werden sollen.

{* ../../docs_src/templates/tutorial001.py hl[4,11,15:18] *}

/// note | Hinweis

5. You can use other standard type annotations with dataclasses as the request body.

    In this case, it's a list of `Item` dataclasses.

6. Here we are returning a dictionary that contains `items` which is a list of dataclasses.

    FastAPI is still capable of <abbr title="converting the data to a format that can be transmitted">serializing</abbr> the data to JSON.

Import the `Response` class (sub-class) you want to use and declare it in the *path operation decorator*.

For large responses, returning a `Response` directly is much faster than returning a dictionary.

    /** The number of records per page. */
    private int pageSize;

    /** The current page number. */
    private int currentPageNumber;

    /** The ID of the synonym dictionary. */
    public String id;

    /**
     * Clears the pager's state to its default values.
     */
    public void clear() {
        allRecordCount = 0;
        allPageCount = 0;
        existPrePage = false;

For example, you could want to **return a dictionary** or a database object, but **declare it as a Pydantic model**. This way the Pydantic model would do all the data documentation, validation, etc. for the object that you returned (e.g. a dictionary or database object).

* scratch the surface: tocar los conceptos básicos
* string: string
* bug: bug
* docs: documentación (do not translate to "documentos")
* cheat sheet: cheat sheet (do not translate to "chuleta")
* key (as in key-value pair, dictionary key): clave
* array (as in JSON array): array
* API key: API key (do not translate to "clave API")
* 100% test coverage: cobertura de tests del 100%
* back and forth: de un lado a otro

                    }
                },
                "x-aperture-labs-portal": "blue"
            }
        }
    }
}
```

### Benutzerdefiniertes OpenAPI-*Pfadoperation*-Schema

Das Dictionary in `openapi_extra` wird mit dem automatisch generierten OpenAPI-Schema für die *Pfadoperation* zusammengeführt (mittels Deep Merge).

Sie können dem automatisch generierten Schema also zusätzliche Daten hinzufügen.

{* ../../docs_src/events/tutorial003.py hl[16,19] *}

Here we are simulating the expensive *startup* operation of loading the model by putting the (fake) model function in the dictionary with machine learning models before the `yield`. This code will be executed **before** the application **starts taking requests**, during the *startup*.

     * @return The message manager.
     */
    public static MessageManager getMessageManager() {
        return getComponent(MESSAGE_MANAGER);
    }

    /**
     * Gets the dictionary manager component.
     * @return The dictionary manager.
     */
    public static DictionaryManager getDictionaryManager() {
        return getComponent(DICTIONARY_MANAGER);
    }

    /**
     * Gets the data service component.

        assertEquals("/error/system.jsp", FessHtmlPath.path_Error_SystemJsp.getRoutingPath());
    }

    public void test_dictPaths() throws Exception {
        // Test dictionary paths structure
        assertEquals("/admin/dict/admin_dict.jsp", FessHtmlPath.path_AdminDict_AdminDictJsp.getRoutingPath());
        assertEquals("/admin/dict/kuromoji/admin_dict_kuromoji.jsp",