func HardLimitReader(r io.Reader, n int64) io.Reader { return &HardLimitedReader{r, n} }

// A HardLimitedReader reads from R but limits the amount of
// data returned to just N bytes. Each call to Read
// updates N to reflect the new amount remaining.
// Read returns EOF when N <= 0 or when the underlying R returns EOF.
type HardLimitedReader struct {
	R io.Reader // underlying reader

   *         .addNode(ICELAND)
   *         .build();
   * }</pre>
   *
   * <p>Builder instances can be reused; it is safe to call {@link #build} multiple times to build
   * multiple graphs in series. Each new graph contains all the elements of the ones created before
   * it.
   *
   * @since 28.0
   */
  public static class Builder<N> {

    private final MutableGraph<N> mutableGraph;

// a map (`tensorflow::eager::TensorTape`) from the wrapped tensor to the id of
// the op that produced it (or -1 if this tensor was watched using
// `GradientTape::Watch`.) The op_id is simply a unique index assigned to each
// op executed under the tape. A separate map (`tensorflow::eager::OpTape`)
// maintains the map from `op_id` to a `OpTapeEntry` which stores the `op_type`,

      if (!heapForIndex(i).verifyIndex(i)) {
        return false;
      }
    }
    return true;
  }

  /**
   * Each instance of MinMaxPriorityQueue encapsulates two instances of Heap: a min-heap and a
   * max-heap. Conceptually, these might each have their own array for storage, but for efficiency's
   * sake they are stored interleaved on alternate heap levels in the same array (MMPQ.queue).
   */

      long result = 1;
      for (int i = n1 + 1; i <= n2; i++) {
        result *= i;
      }
      return BigInteger.valueOf(result);
    }

    /*
     * We want each multiplication to have both sides with approximately the same number of digits.
     * Currently, we just divide the range in half.
     */
    int mid = (n1 + n2) >>> 1;

<img src="/img/tutorial/sub-applications/image02.png">

If you try interacting with any of the two user interfaces, they will work correctly, because the browser will be able to talk to each specific app or sub-app.

### Technical Details: `root_path`

var KafkaSHA512 scram.HashGeneratorFcn = sha512.New

// XDGSCRAMClient implements the client-side of an authentication
// conversation with a server.  A new conversation must be created for
// each authentication attempt.
type XDGSCRAMClient struct {
	*scram.Client
	*scram.ClientConversation
	scram.HashGeneratorFcn
}

// Begin constructs a SCRAM client component based on a given hash.Hash

   */
  Set<E> elementSet();

  /**
   * Returns a view of the contents of this multiset, grouped into {@code Multiset.Entry} instances,
   * each providing an element of the multiset and the count of that element. This set contains
   * exactly one entry for each distinct element in the multiset (thus it always has the same size
   * as the {@link #elementSet}). The order of the elements in the element set is unspecified.
   *

	Kubeconfig string
	Context    string
	Namespace  string
}

// Inherit the common kubernetes flags defined in the root package. This is a bit of a hack,
// but it allows us to directly get the final values for each of these flags without needing
// to pass pointers-to-flags through all of the (sub)commands.
func (o *KubeOptions) prepare(ctx cli.Context) {
	o.Namespace = ctx.Namespace()
	if o.Namespace == "" {

                excludedPackages.add(baseName);
            } else {
                excludedPackages.add(excludePattern);
            }
        }

        repository.each(new Action<ClassMetaData>() {
            @Override
            public void execute(ClassMetaData classMetaData) {
                if (classMetaData.getOuterClassName() != null) {
                    // Ignore inner classes