}
	}
	return path.Join(elem...) + trailingSlash
}

func concatNaive(ss ...string) string {
	rs := ss[0]
	for i := 1; i < len(ss); i++ {
		rs += ss[i]
	}
	return rs
}

func benchmark(b *testing.B, data []string) {
	b.Run("concat naive", func(b *testing.B) {
		b.ResetTimer()
		b.ReportAllocs()
		for b.Loop() {
			concatNaive(data...)
		}
	})
	b.Run("concat fast", func(b *testing.B) {

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package com.google.common.base;

import com.google.caliper.BeforeExperiment;
import com.google.caliper.Benchmark;
import com.google.caliper.Param;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import org.jspecify.annotations.NullUnmarked;

    checkNotNull(list);
    checkNotNull(presentBehavior);
    checkNotNull(absentBehavior);
    if (!(list instanceof RandomAccess)) {
      list = new ArrayList<>(list);
    }
    // TODO(lowasser): benchmark when it's best to do a linear search

    int lower = 0;
    int upper = list.size() - 1;

    while (lower <= upper) {
      int middle = (lower + upper) >>> 1;

			return cfg, err
		}
		if inlineBlock > 128*humanize.KiByte {
			configLogOnceIf(context.Background(), fmt.Errorf("inline block value bigger than recommended max of 128KiB -> %s, performance may degrade for PUT please benchmark the changes", inlineBlockStr), inlineBlockStr)
		}
		cfg.inlineBlock = int64(inlineBlock)
	} else {
		cfg.inlineBlock = 128 * humanize.KiByte
	}

	cfg.initialized = true

	return cfg, nil
}

// provide any API to calculate the profiler file path in the
// disk since the name of this latter is randomly generated.
type profilerWrapper struct {
	// Profile recorded at start of benchmark.
	records map[string][]byte
	stopFn  func() ([]byte, error)
	ext     string
}

// record will record the profile and store it as the base.

]

# 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(b.Context(), bucket, MakeBucketOptions{})

   * world. Figure out what sort of space-time tradeoff we're actually going to get here with the
   * *Map variants. This class is particularly hard to benchmark, because the benefit is not only in
   * less allocation, but also having the GC do less work to scan the heap because of fewer
   * references, which is particularly hard to quantify.
   */

   * world. Figure out what sort of space-time tradeoff we're actually going to get here with the
   * *Map variants. This class is particularly hard to benchmark, because the benefit is not only in
   * less allocation, but also having the GC do less work to scan the heap because of fewer
   * references, which is particularly hard to quantify.
   */

# Benchmarks { #benchmarks }

Los benchmarks independientes de TechEmpower muestran aplicaciones de **FastAPI** ejecutándose bajo 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 en sí mismos (utilizados internamente por FastAPI).