Entretanto, se você usar o comando `pip install fastapi`, o pacote `python-multipart` não é incluído por padrão.

Para instalá-lo manualmente, certifique-se de criar um [ambiente virtual](../../virtual-environments.md), ativá-lo e então instalá-lo com:

```console
$ pip install python-multipart
```

## Installer `PyJWT` { #install-pyjwt }

Nous devons installer `PyJWT` pour générer et vérifier les jetons JWT en Python.

Assurez-vous de créer un [environnement virtuel](../../virtual-environments.md), de l'activer, puis d'installer `pyjwt` :

<div class="termy">

```console
$ pip install pyjwt

---> 100%
```

</div>

/// info

## Çalıştırın { #run-it }

/// info | Bilgi

The [`python-multipart`](https://github.com/Kludex/python-multipart) paketi, `pip install "fastapi[standard]"` komutunu çalıştırdığınızda **FastAPI** ile birlikte otomatik olarak kurulur.

Ancak `pip install fastapi` komutunu kullanırsanız, `python-multipart` paketi varsayılan olarak dahil edilmez.

## Установка `PyJWT` { #install-pyjwt }

Нам необходимо установить `pyjwt` для генерации и проверки JWT-токенов на языке Python.

Убедитесь, что вы создали [виртуальное окружение](../../virtual-environments.md), активируйте его, а затем установите `pyjwt`:

<div class="termy">

```console
$ pip install pyjwt

---> 100%
```

</div>

/// info | Información

Para recibir archivos subidos y/o form data, primero instala [`python-multipart`](https://github.com/Kludex/python-multipart).

Asegúrate de crear un [entorno virtual](../virtual-environments.md), actívalo y luego instálalo, por ejemplo:

```console
$ pip install python-multipart
```

///

## Importa `File` y `Form` { #import-file-and-form }

## Utiliser `WSGIMiddleware` { #using-wsgimiddleware }

/// info

Cela nécessite l'installation de `a2wsgi`, par exemple avec `pip install a2wsgi`.

///

Vous devez importer `WSGIMiddleware` depuis `a2wsgi`.

Ensuite, enveloppez l'application WSGI (par ex. Flask) avec le middleware.

Puis, montez-la sous un chemin.

libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-headers-cuda-13=9.15.1.9-1
libcudnn9-static-cuda-13=9.15.1.9-1
libcudnn9-dev-cuda-13=9.15.1.9-1

libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.8.0.87-1

libcufft-12-1
libcurand-12-1
libcusolver-dev-12-1
libcusparse-dev-12-1
libcublas-12-1
libcublas-dev-12-1
libnccl-dev=2.18.3-1+cuda12.1
libnccl2=2.18.3-1+cuda12.1
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.1.1.17-1

일반적인 선택은 Jinja2로, Flask와 다른 도구에서도 사용됩니다.

설정을 쉽게 할 수 있는 유틸리티가 있으며, 이를 **FastAPI** 애플리케이션에서 직접 사용할 수 있습니다(Starlette 제공).

## 의존성 설치 { #install-dependencies }

[가상 환경](../virtual-environments.md)을 생성하고, 활성화한 후 `jinja2`를 설치해야 합니다:

<div class="termy">

```console
$ pip install jinja2

---> 100%
```

</div>

## `Jinja2Templates` 사용하기 { #using-jinja2templates }

* `Jinja2Templates`를 가져옵니다.