* Pour le HTTPS, le serveur a besoin de "certificats" générés par une tierce partie.
    * Ces certificats sont en fait acquis auprès de la tierce partie, et non "générés".
* Les certificats ont une durée de vie.
    * Ils expirent.
    * Puis ils doivent être renouvelés et acquis à nouveau auprès de la tierce partie.
* Le cryptage de la connexion se fait au niveau du protocole TCP.
    * C'est une couche en dessous de HTTP.

with open("file.txt") as file:
    file.read()
```

Nas versões mais recentes de Python, há também um **gerenciador de contexto assíncrono**. Você o usaria com `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

		err := tryParse(t, func() {
			parser.Parse()
		})

		switch {
		case err == nil:
			t.Errorf("#%d: %q: want error %q; have none", i, test.input, test.error)
		case !strings.Contains(err.Error(), test.error):
			t.Errorf("#%d: %q: want error %q; have %q", i, test.input, test.error, err)
		}
	}

    * E.g., `await myfile.seek(0)` navegaria para o ínicio do arquivo.
    * Isso é especialmente útil se você executar `await myfile.read()` uma vez e depois precisar ler os conteúdos do arquivo de novo.
* `close()`: Fecha o arquivo.

Como todos esses métodos são assíncronos (`async`) você precisa esperar ("await") por eles.

* `seek(versatz)`: Geht zur Position `versatz` (`int`) in der Datei.
    * Z. B. würde `await myfile.seek(0)` zum Anfang der Datei gehen.
    * Das ist besonders dann nützlich, wenn Sie `await myfile.read()` einmal ausführen und dann diese Inhalte erneut auslesen müssen.
* `close()`: Schließt die Datei.

Da alle diese Methoden `async`hron sind, müssen Sie sie `await`en („erwarten“).

Vous pouvez le faire avec `openapi_extra` :

{* ../../docs_src/path_operation_advanced_configuration/tutorial006.py hl[20:37,39:40] *}

```Python
with open("file.txt") as file:
    file.read()
```

En versiones recientes de Python, también hay un **async context manager**. Lo usarías con `async with`:

```Python
async with lifespan(app):
    await do_stuff()
```

In this type of scenario, you probably would want to have **a single (Uvicorn) process per container**, as you would already be handling replication at the cluster level.

So, in this case, you **would not** want to have a multiple workers in the container, for example with the `--workers` command line option.You would want to have just a **single Uvicorn process** per container (but probably multiple containers).

## Do not Separate Schemas { #do-not-separate-schemas }

Now, there are some cases where you might want to have the **same schema for input and output**.

Probably the main use case for this is if you already have some autogenerated client code/SDKs and you don't want to update all the autogenerated client code/SDKs yet, you probably will want to do it at some point, but maybe not right now.

<div class="screenshot">
<img src="/img/tutorial/header-param-models/image01.png">
</div>

## Forbid Extra Headers { #forbid-extra-headers }

In some special use cases (probably not very common), you might want to **restrict** the headers that you want to receive.

You can use Pydantic's model configuration to `forbid` any `extra` fields:

{* ../../docs_src/header_param_models/tutorial002_an_py310.py hl[10] *}