// tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the

  @BeforeExperiment
  void setUp() {
    Random random = new Random(randomSeed);
    xInts = new int[SAMPLE_SIZE];
    yInts = new int[SAMPLE_SIZE];
    xLongs = new long[SAMPLE_SIZE];
    yLongs = new long[SAMPLE_SIZE];
    constant = new int[SAMPLE_SIZE];
    for (int i = 0; i < SAMPLE_SIZE; i++) {
      xInts[i] = random.nextInt(Integer.MAX_VALUE);
      yInts[i] = random.nextInt(Integer.MAX_VALUE);

import java.math.BigInteger;
import java.util.Random;
import org.jspecify.annotations.NullUnmarked;

/**
 * Utilities for benchmarks.
 *
 * <p>In many cases, we wish to vary the order of magnitude of the input as much as we want to vary
 * the input itself, so most methods which generate values use an exponential distribution varying
 * the order of magnitude of the generated values uniformly at random.
 *
 * @author Louis Wasserman
 */

  }

  @Test
  public void undirectedGraph() {
    testGraphMutation(GraphBuilder.undirected());
  }

  private static void testGraphMutation(GraphBuilder<? super Integer> graphBuilder) {
    Random gen = new Random(42); // Fixed seed so test results are deterministic.

    for (int trial = 0; trial < NUM_TRIALS; ++trial) {
      MutableGraph<Integer> graph = graphBuilder.allowsSelfLoops(true).build();

  private Queue<Integer> queue;

  private final Random random = new Random();

  @BeforeExperiment
  void setUp() {
    queue = heap.create(comparator.get());
    for (int i = 0; i < size; i++) {
      queue.add(random.nextInt());
    }
  }

  @Benchmark
  void pollAndAdd(int reps) {
    for (int i = 0; i < reps; i++) {
      // TODO(kevinb): precompute random #s?
      queue.add(queue.poll() ^ random.nextInt());

  private Queue<Integer> queue;

  private final Random random = new Random();

  @BeforeExperiment
  void setUp() {
    queue = heap.create(comparator.get());
    for (int i = 0; i < size; i++) {
      queue.add(random.nextInt());
    }
  }

  @Benchmark
  void pollAndAdd(int reps) {
    for (int i = 0; i < reps; i++) {
      // TODO(kevinb): precompute random #s?
      queue.add(queue.poll() ^ random.nextInt());

Primeiro, é claro, você pode misturar `Path`, `Query` e declarações de parâmetro no corpo da requisição livremente e o **FastAPI** saberá o que fazer.

E você também pode declarar parâmetros de corpo como opcionais, definindo o valor padrão com `None`:

{* ../../docs_src/body_multiple_params/tutorial001_an_py310.py hl[18:20] *}

/// note | Nota

    sink.assertBytes(new byte[] {1, 2, 0, 0}); // padded with zeros
  }

  public void testString() {
    Random random = new Random();
    for (int i = 0; i < 100; i++) {
      byte[] bytes = new byte[64];
      random.nextBytes(bytes);
      String s = new String(bytes, UTF_16LE); // so all random strings are valid
      assertEquals(
          new Sink(4).putUnencodedChars(s).hash(),

  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);
  static AtomicLong misses = new AtomicLong(0);

  @BeforeExperiment
  void setUp() {
    // random integers will be generated in this range, then raised to the

// the given io.Reader. If random is nil, crypto/rand.Reader is used.
// If length <= 0, the access key length is chosen automatically.
//
// GenerateAccessKey returns an error if length is too small for a valid
// access key.
func GenerateAccessKey(length int, random io.Reader) (string, error) {
	if random == nil {
		random = rand.Reader
	}
	if length <= 0 {
		length = accessKeyMaxLen