}
          };
      executor.execute(errorTask);
      service.execute(barrierTask); // submit directly to the service
      // the barrier task runs after the error task so we know that the error has been observed by
      // SequentialExecutor by the time the barrier is satisfied
      barrier.await(1, SECONDS);
      executor.execute(barrierTask);
      // timeout means the second task wasn't even tried

pkg net/http, method (*ClientConn) Err() error #75772
pkg net/http, method (*ClientConn) InFlight() int #75772
pkg net/http, method (*ClientConn) Release() #75772
pkg net/http, method (*ClientConn) Reserve() error #75772
pkg net/http, method (*ClientConn) RoundTrip(*Request) (*Response, error) #75772
pkg net/http, method (*ClientConn) SetStateHook(func(*ClientConn)) #75772

    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,

			writeResponse(w, http.StatusServiceUnavailable, nil, mimeNone)
		}
		return
	}
	writeResponse(w, http.StatusOK, nil, mimeNone)
}

// ReadinessCheckHandler checks whether MinIO is up and ready to serve requests.
// It also checks whether the KMS is available and whether etcd is reachable,
// if configured.
func ReadinessCheckHandler(w http.ResponseWriter, r *http.Request) {

* 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

    }

    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(

# FastAPI CLI { #fastapi-cli }

**FastAPI CLI** 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 includes a package called `fastapi-cli`, this package provides the `fastapi` command in the terminal.

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

<div class="termy">

```console

O FastAPI CLI recebe o caminho para o seu programa Python (por exemplo, `main.py`), detecta automaticamente a instância de `FastAPI` (comumente nomeada `app`), determina a forma correta de importação e então a serve.

Para produção, você usaria `fastapi run`. 🚀

    .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

    tensorflow::shape_inference::InferenceContext* ic, int num_dims,
    const int64_t* dims) {
  if (num_dims != -1) {
    std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec;
    dim_vec.reserve(num_dims);
    for (int i = 0; i < num_dims; ++i) {
      dim_vec.push_back(ic->MakeDim(dims[i]));
    }
    return ic->MakeShape(dim_vec);
  } else {
    return ic->UnknownShape();
  }
}