El servidor web principal para ejecutar aplicaciones **FastAPI**.

También puedes usar la opción de línea de comandos `--workers` para tener un servidor multiproceso asíncrono.

Revisa más detalles en la sección [Despliegue](deployment/index.md){.internal-link target=_blank}.

///

## Benchmarks y velocidad { #benchmarks-and-speed }

You are logged in to FastAPI Cloud 🚀
```

</div>

Luego despliega tu app:

<div class="termy">

```console
$ fastapi deploy

Deploying to FastAPI Cloud...

✅ Deployment successful!

🐔 Ready the chicken! Your app is ready at https://myapp.fastapicloud.dev
```

</div>

¡Eso es todo! Ahora puedes acceder a tu app en esa URL. ✨

You are logged in to FastAPI Cloud 🚀
```

</div>

Depois, implemente sua aplicação:

<div class="termy">

```console
$ fastapi deploy

Deploying to FastAPI Cloud...

✅ Deployment successful!

🐔 Ready the chicken! Your app is ready at https://myapp.fastapicloud.dev
```

</div>

É isso! Agora você pode acessar sua aplicação nesse URL. ✨

     *
     * @param repository the repository where to deploy artifacts
     * @param artifacts the artifacts to deploy
     * @throws org.apache.maven.api.services.ArtifactDeployerException if the artifacts deployment failed
     *
     * @see org.apache.maven.api.services.ArtifactDeployer#deploy(Session, RemoteRepository, Collection)
     */

- ReplicaSets and Deployments should always count `.status.availableReplicas` at the correct time without a delay. This results in faster reconciliation of Deployment conditions and faster, unblocked Deployment rollouts. ([#132121](https://github.com/kubernetes/kubernetes/pull/132121), [@atiratree](https://github.com/atiratree)) [SIG Apps]

You are logged in to FastAPI Cloud 🚀
```

</div>

Then deploy your app:

<div class="termy">

```console
$ fastapi deploy

Deploying to FastAPI Cloud...

✅ Deployment successful!

🐔 Ready the chicken! Your app is ready at https://myapp.fastapicloud.dev
```

</div>

That's it! Now you can access your app at that URL. ✨

#### About FastAPI Cloud

但你也可以利用平行與多行程 (multiprocessing)（讓多個行程同時運行） 的優勢來處理機器學習系統中的 **CPU 密集型**工作。

這一點，再加上 Python 是 **資料科學**、機器學習，尤其是深度學習的主要語言，讓 **FastAPI** 成為資料科學/機器學習 Web API 和應用程式（以及許多其他應用程式）的絕佳選擇。

想了解如何在生產環境中實現這種平行性，請參見 [部屬](deployment/index.md){.internal-link target=_blank}。

## `async` 和 `await`

現代 Python 版本提供一種非常直觀的方式定義非同步程式碼。這使得它看起來就像正常的「順序」程式碼，並在適當的時機「等待」。

當某個操作需要等待才能回傳結果，並且支援這些新的 Python 特性時，你可以像這樣編寫程式碼：

```Python

		if err != nil {
			return nil, err
		}

		if deploymentID == "" {
			// all pools should have same deployment ID
			deploymentID = formats[i].ID
		}

		// Validate if users brought different DeploymentID pools.
		if deploymentID != formats[i].ID {
			return nil, fmt.Errorf("all pools must have same deployment ID - expected %s, got %s for pool(%s)", deploymentID, formats[i].ID, humanize.Ordinal(i+1))
		}

Quando você passa o arquivo para `fastapi run` ele detecta automaticamente que é um arquivo único e não parte de um pacote e sabe como importá-lo e servir sua aplicação FastAPI. 😎

## Conceitos de Implantação { #deployment-concepts }

Vamos falar novamente sobre alguns dos mesmos [Conceitos de Implantação](concepts.md){.internal-link target=_blank} em termos de contêineres.

* Deployment will stop adding pod-template-hash labels/selector to ReplicaSets and Pods it adopts. Resources created by Deployments are not affected (will still have pod-template-hash labels/selector).  ([#61615](https://github.com/kubernetes/kubernetes/pull/61615), [@janetkuo](https://github.com/janetkuo))