* test molto facili basati su `requests` e `pytest`
    * **CORS**
    * **Cookie Sessions**
    * ...e altro ancora.

## Prestazioni

]

# List of files to configure when building Bazel on Apple platforms.
APPLE_BAZEL_FILES = [
    'tensorflow/lite/ios/BUILD', 'tensorflow/lite/objc/BUILD',
    'tensorflow/lite/swift/BUILD',
    'tensorflow/lite/tools/benchmark/experimental/ios/BUILD'
]

# List of files to move when building for iOS.
IOS_FILES = [
    'tensorflow/lite/objc/TensorFlowLiteObjC.podspec',
    'tensorflow/lite/swift/TensorFlowLiteSwift.podspec',
]

	return obj
}

// BenchmarkListObjects - Run ListObject Repeatedly and benchmark.
func BenchmarkListObjects(b *testing.B) {
	// Make a temporary directory to use as the obj.
	directory := b.TempDir()

	// Create the obj.
	obj := initFSObjectsB(directory, b)

	bucket := "ls-benchmark-bucket"
	// Create a bucket.
	err := obj.MakeBucket(context.Background(), bucket, MakeBucketOptions{})

			t.Errorf("test %d, unexpected error: %v", i, err)
		}
		if (formats == FormatUnknown) && (err == nil) {
			t.Errorf("test %d, got nil-error, want non-nil error", i)
		}
	}
}

func Benchmark(b *testing.B) {
	type file struct {
		hdr  *Header
		body []byte
	}

	vectors := []struct {
		label string
		files []file
	}{{
		"USTAR",
		[]file{{

 *
 * @author Jared Levy
 * @author Louis Wasserman
 * @since 2.0 (implements {@code NavigableSet} since 12.0)
 */
// TODO(benyu): benchmark and optimize all creation paths, which are a mess now
@GwtCompatible(serializable = true, emulated = true)
@SuppressWarnings("serial") // we're overriding default serialization
@ElementTypesAreNonnullByDefault

 *
 * @author Jared Levy
 * @author Louis Wasserman
 * @since 2.0 (implements {@code NavigableSet} since 12.0)
 */
// TODO(benyu): benchmark and optimize all creation paths, which are a mess now
@GwtCompatible(serializable = true, emulated = true)
@SuppressWarnings("serial") // we're overriding default serialization
@ElementTypesAreNonnullByDefault

# Benchmarks

Los benchmarks independientes de TechEmpower muestran aplicaciones de **FastAPI** que se ejecutan en Uvicorn como <a href="https://www.techempower.com/benchmarks/#section=test&runid=7464e520-0dc2-473d-bd34-dbdfd7e85911&hw=ph&test=query&l= zijzen-7" class="external-link" target="_blank">uno de los frameworks de Python más rápidos disponibles</a>, solo por debajo de Starlette y Uvicorn (utilizados internamente por FastAPI). (*)

# Benchmarks

Independent TechEmpower benchmarks show **FastAPI** applications running under Uvicorn as <a href="https://www.techempower.com/benchmarks/#section=test&runid=7464e520-0dc2-473d-bd34-dbdfd7e85911&hw=ph&test=query&l=zijzen-7" class="external-link" target="_blank">one of the fastest Python frameworks available</a>, only below Starlette and Uvicorn themselves (used internally by FastAPI).

# Benchmarks

Unabhängige TechEmpower-Benchmarks zeigen, **FastAPI**-Anwendungen, die unter Uvicorn ausgeführt werden, gehören zu <a href="https://www.techempower.com/benchmarks/#section=test&runid=7464e520-0dc2-473d-bd34-dbdfd7e85911&hw=ph&test=query&l=zijzen-7" class="external-link" target="_blank">den schnellsten existierenden Python-Frameworks</a>, nur Starlette und Uvicorn selbst (intern von FastAPI verwendet) sind schneller.

# Benchmarks

Benchmarks independentes da TechEmpower mostram que aplicações **FastAPI** rodando com o Uvicorn como <a href="https://www.techempower.com/benchmarks/#section=test&runid=7464e520-0dc2-473d-bd34-dbdfd7e85911&hw=ph&test=query&l=zijzen-7" class="external-link" target="_blank">um dos frameworks Python mais rápidos disponíveis</a>, ficando atrás apenas do Starlette e Uvicorn (utilizado internamente pelo FastAPI).