# Using the Request Directly { #using-the-request-directly }

Up to now, you have been declaring the parts of the request that you need with their types.

Taking data from:

* The path as parameters.
* Headers.
* Cookies.
* etc.

And by doing so, **FastAPI** is validating that data, converting it and generating documentation for your API automatically.

But there are situations where you might need to access the `Request` object directly.

Dans ce cadre, j'ai dû étudier, tester et utiliser de nombreuses alternatives.

L'histoire de **FastAPI** est en grande partie l'histoire de ses prédécesseurs.

Comme dit dans la section [Alternatives](alternatives.md){.internal-link target=\_blank} :

<blockquote markdown="1">

**FastAPI** n'existerait pas sans le travail antérieur d'autres personnes.

```

You may run builds and tests against different versions of Python sequentially
on the same machine by simply switching the value of `HERMETIC_PYTHON_VERSION`
between the runs. All the python-agnostic parts of the build cache from the
previous build will be preserved and reused for the subsequent builds.

### Specifying Python dependencies

During bazel build all TensorFlow's Python dependencies are pinned to their

///

## Returning a custom `Response` { #returning-a-custom-response }

The example above shows all the parts you need, but it's not very useful yet, as you could have just returned the `item` directly, and **FastAPI** would put it in a `JSONResponse` for you, converting it to a `dict`, etc. All that by default.

Da lista de conceitos de implantação acima, o uso de trabalhadores ajudaria principalmente com a parte da **replicação** e um pouco com as **reinicializações**, mas você ainda precisa cuidar dos outros:

* **Segurança - HTTPS**
* **Executando na inicialização**
* ***Reinicializações***

Python 3.6+

FastAPI è basata su importanti librerie:

* <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> per le parti web.
* <a href="https://docs.pydantic.dev/" class="external-link" target="_blank">Pydantic</a> per le parti dei dati.

## Installazione

<div class="termy">

```console
$ pip install fastapi

---> 100%
```

</div>

		expectedErrCode  APIErrorCode
	}{
		// Test case - 1.
		// SignElement doesn't have 2 parts on an attempt to split at '='.
		// ErrMissingFields expected.
		{
			inputSignElement: "Signature",
			expectedSignStr:  "",
			expectedErrCode:  ErrMissingFields,
		},
		// Test case - 2.
		// SignElement does have 2 parts but doesn't have valid signature value.
		// ErrMissingFields expected.
		{

	c.Assert(err, nil)
	// verify whether complete multipart was successful.
	c.Assert(response.StatusCode, http.StatusOK)
	var parts []CompletePart
	for _, part := range completeUploads.Parts {
		part.ETag = canonicalizeETag(part.ETag)
		parts = append(parts, part)
	}
	etag := getCompleteMultipartMD5(parts)
	c.Assert(canonicalizeETag(response.Header.Get(xhttp.ETag)), etag)

{* ../../docs_src/security/tutorial002_an_py310.py...

//// tab | Python 3.9+

En Python 3.9, `Annotated` es parte de la librería estándar, así que puedes importarlo desde `typing`.

```Python hl_lines="1  4"
{!> ../../docs_src/python_types/tutorial013_py39.py!}
```

////

//// tab | Python 3.8+