Você não precisa declarar a anotação de tipo de retorno para transmitir dados binários.

Como o FastAPI não tentará converter os dados para JSON com Pydantic nem serializá-los de nenhuma forma, neste caso a anotação de tipo serve apenas para seu editor e ferramentas; ela não será usada pelo FastAPI.

{* ../../docs_src/stream_data/tutorial001_py310.py ln[32:35] hl[33] *}

# FastAPI CLI { #fastapi-cli }

**FastAPI <abbr title="command line interface">CLI</abbr>** is a command line program that you can use to serve your FastAPI app, manage your FastAPI project, and more.

When you install FastAPI (e.g. with `pip install "fastapi[standard]"`), it comes with a command line program you can run in the terminal.

To run your FastAPI app for development, you can use the `fastapi dev` command:

<div class="termy">

```console

* the schema definition
* Password Flow
* Mobile

* deprecated
* designed
* invalid
* on the fly
* standard
* default
* case-sensitive
* case-insensitive

* to serve the application
* to serve the page

* the app
* the application

* the request
* the response
* the error response

* the path operation
* the path operation decorator
* the path operation function

    server.requireClientAuth()
    val call = client.newCall(Request.Builder().url(server.url("/")).build())
    assertFailsWith<IOException> {
      call.execute()
    }

    // Observed Events are variable
    // JDK 14
    // CallStart, ProxySelectStart, ProxySelectEnd, DnsStart, DnsEnd, ConnectStart, SecureConnectStart,

    .build();

HeldCertificate serverCertificate = new HeldCertificate.Builder()
    .addSubjectAlternativeName("localhost")
    .signedBy(intermediateCertificate)
    .build();
```

To serve this configuration the server needs to provide its clients with a chain of certificates
starting with its own and including everything up-to but not including the root. We don't need to

## Deployment Concepts { #deployment-concepts }

Here you saw how to use multiple **workers** to **parallelize** the execution of the application, take advantage of **multiple cores** in the CPU, and be able to serve **more requests**.

From the list of deployment concepts from above, using workers would mainly help with the **replication** part, and a little bit with the **restarts**, but you still need to take care of the others:

# Run a Server Manually { #run-a-server-manually }

## Use the `fastapi run` Command { #use-the-fastapi-run-command }

In short, use `fastapi run` to serve your FastAPI application:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run <u style="text-decoration-style:solid">main.py</u>

  <span style="background-color:#009485"><font color="#D3D7CF"> FastAPI </font></span>  Starting production server 🚀

```
.
├── app
│   ├── __init__.py
│   ├── main.py
└── static
    ├── redoc.standalone.js
    ├── swagger-ui-bundle.js
    └── swagger-ui.css
```

### Обслуговуйте статичні файли { #serve-the-static-files }

- Імпортуйте `StaticFiles`.
- Змонтуйте екземпляр `StaticFiles()` у певному шляху.

{* ../../docs_src/custom_docs_ui/tutorial002_py310.py hl[7,11] *}

    }

    private void addUtilityTasks(TaskContainer tasks, GradleDocumentationExtension extension) {
        tasks.register("serveDocs", ServeDocs.class, task -> {
            task.setDescription("Runs a local webserver to serve generated documentation.");
            task.setGroup("documentation");

            int webserverPort = 8000;
            task.getJavaLauncher().set(

```
.
├── app
│   ├── __init__.py
│   ├── main.py
└── static
    ├── redoc.standalone.js
    ├── swagger-ui-bundle.js
    └── swagger-ui.css
```

### Предоставьте доступ к статическим файлам { #serve-the-static-files }

* Импортируйте `StaticFiles`.
* Смонтируйте экземпляр `StaticFiles()` в определённый путь.

{* ../../docs_src/custom_docs_ui/tutorial002_py310.py hl[7,11] *}