* a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Note that this implementation is not synchronized. If multiple threads access this table

    `Headers` class offers full access to the HTTP headers.

 *  **Okio dependency added.** OkHttp now depends on
    [Okio](https://github.com/square/okio), an I/O library that makes it easier
    to access, store and process data. Using this library internally makes OkHttp
    faster while consuming less memory. You can write a `RequestBody` as an Okio
    `BufferedSink` and a `ResponseBody` as an Okio `BufferedSource`. Standard

     *
     * <p>If this returns false, then no query can take more than O(log n).
     *
     * <p>Note that for a RegularImmutableSet with elements with truly random hash codes, contains
     * operations take expected O(1) time but with high probability take O(log n) for at least some
     * element. (https://en.wikipedia.org/wiki/Linear_probing#Analysis)
     *

   * is polled. This amortizes the sorting cost over the iteration and requires less memory than
   * sorting all elements at once.
   *
   * <p>Retrieving a single element takes approximately O(log(M)) time, where M is the number of
   * iterators. (Retrieving all elements takes approximately O(N*log(M)) time, where N is the total
   * number of elements.)
   */
  private static final class MergingIterator<T extends @Nullable Object>

 *
 * <p>The time taken to compute multiple quantiles on the same dataset using {@link Scale#indexes
 * indexes} is generally less than the total time taken to compute each of them separately, and
 * sometimes much less. For example, on a large enough dataset, computing the 90th and 99th
 * percentiles together takes about 55% as long as computing them separately.
 *

 *
 * <p>To implement a multimap, a subclass must define the method {@link #createCollection()}, which
 * creates an empty collection of values for a key.
 *
 * <p>The multimap constructor takes a map that has a single entry for each distinct key. When you
 * insert a key-value pair with a key that isn't already in the multimap, {@code

    }
  }


  @J2ktIncompatible // slow enough to cause flakiness
  @GwtIncompatible // far too slow
  public void testSqrtOfPerfectSquareAsDoubleIsPerfect() {
    // This takes just over a minute on my machine.
    for (long n = 0; n <= LongMath.FLOOR_SQRT_MAX_LONG; n++) {
      long actual = (long) Math.sqrt((double) (n * n));
      assertTrue(actual == n);
    }
  }

  }

  @GwtIncompatible // Shorts.fromByteArray, Shorts.toByteArray
  public void testByteArrayRoundTrips() {
    Random r = new Random(5);
    byte[] b = new byte[Shorts.BYTES];

    // total overkill, but, it takes 0.1 sec so why not...
    for (int i = 0; i < 10000; i++) {
      short num = (short) r.nextInt();
      assertThat(Shorts.fromByteArray(Shorts.toByteArray(num))).isEqualTo(num);

      r.nextBytes(b);

Handle all the data validation, data serialization and automatic model documentation (based on JSON Schema).

**FastAPI** then takes that JSON Schema data and puts it in OpenAPI, apart from all the other things it does.

///

### <a href="https://www.starlette.io/" class="external-link" target="_blank">Starlette</a> { #starlette }

        .isEqualTo(0xFFEEDDCC);
  }

  public void testByteArrayRoundTrips() {
    Random r = new Random(5);
    byte[] b = new byte[Ints.BYTES];

    // total overkill, but, it takes 0.1 sec so why not...
    for (int i = 0; i < 10000; i++) {
      int num = r.nextInt();
      assertThat(Ints.fromByteArray(Ints.toByteArray(num))).isEqualTo(num);

      r.nextBytes(b);