private final long seed;

  public SpecialRandom() {
    this.hasSeed = false;
    this.seed = 0;
  }

  public SpecialRandom(long seed) {
    super(seed);
    this.hasSeed = true;
    this.seed = seed;
  }

  @Override
  public String toString() {
    return hasSeed ? "(seed:" + seed : "(default seed)";
  }

  private static final long serialVersionUID = 0;

    }
    
    public static class FileInfo {
        private final String name;
        private final long size;
        private final long lastModified;
        private final boolean isDirectory;
        private final long attributes;
        private final long creationTime;
        private final long lastAccessTime;
        
        public FileInfo(String name, SmbFileAttributes attrs) {
            this.name = name;

) {
  /** The total number of bytes consumed. */
  var total: Long = 0L
    private set

  /** The total number of bytes acknowledged by outgoing `WINDOW_UPDATE` frames. */
  var acknowledged: Long = 0L
    private set

  val unacknowledged: Long
    @Synchronized get() = total - acknowledged

  @Synchronized
  fun update(
    total: Long = 0,
    acknowledged: Long = 0,
  ) {
    check(total >= 0)

          negativeToMaxValue(evictionCount.sum()));
    }

    /** Returns {@code value}, if non-negative. Otherwise, returns {@link Long#MAX_VALUE}. */
    private static long negativeToMaxValue(long value) {
      return (value >= 0) ? value : Long.MAX_VALUE;
    }

    /** Increments all counters by the values in {@code other}. */
    public void incrementBy(StatsCounter other) {

   * Returns a nonempty contiguous set containing all {@code long} values from {@code lower}
   * (inclusive) to {@code upper} (inclusive). (These are the same values contained in {@code
   * Range.closed(lower, upper)}.)
   *
   * @throws IllegalArgumentException if {@code lower} is greater than {@code upper}
   * @since 23.0
   */
  public static ContiguousSet<Long> closed(long lower, long upper) {

      // attributes are declared in the cookie string.
      if (deltaSeconds == Long.MIN_VALUE) {
        expiresAt = Long.MIN_VALUE
      } else if (deltaSeconds != -1L) {
        val deltaMilliseconds =
          if (deltaSeconds <= Long.MAX_VALUE / 1000) {
            deltaSeconds * 1000
          } else {
            Long.MAX_VALUE
          }
        expiresAt = currentTimeMillis + deltaMilliseconds

  }

  fun writeBigInteger(value: BigInteger) {
    sink().write(value.toByteArray())
  }

  fun writeLong(v: Long) {
    val sink = sink()

    val lengthBitCount: Int =
      if (v < 0L) {
        65 - java.lang.Long.numberOfLeadingZeros(v xor -1L)
      } else {
        65 - java.lang.Long.numberOfLeadingZeros(v)
      }

    val lengthByteCount = (lengthBitCount + 7) / 8

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

To see how to achieve this parallelism in production see the section about [Deployment](deployment/index.md).

## `async` and `await` { #async-and-await }

   */
  public abstract ComparisonChain compare(int left, int right);

  /**
   * Compares two {@code long} values as specified by {@link Long#compare}, <i>if</i> the result of
   * this comparison chain has not already been determined.
   */
  public abstract ComparisonChain compare(long left, long right);

  /**
   * Compares two {@code float} values as specified by {@link Float#compare}, <i>if</i> the result

    } catch (Throwable e) {
      throw closer.rethrow(e);
    } finally {
      closer.close();
    }
  }

  private static long countBySkipping(Reader reader) throws IOException {
    long count = 0;
    long read;
    while ((read = reader.skip(Long.MAX_VALUE)) != 0) {
      count += read;
    }
    return count;
  }

  /**