discussion_edges = get_graphql_question_discussion_edges(settings=settings)

    while discussion_edges:
        for discussion_edge in discussion_edges:
            discussion_nodes.append(discussion_edge.node)
        last_edge = discussion_edges[-1]
        discussion_edges = get_graphql_question_discussion_edges(
            settings=settings, after=last_edge.cursor
        )
    return discussion_nodes

    for (N node : graph.nodes()) {
      copy.addNode(node);
    }
    for (EndpointPair<N> edge : graph.edges()) {
      copy.putEdge(edge.nodeU(), edge.nodeV());
    }
    return copy;
  }

  /** Creates a mutable copy of {@code graph} with the same nodes, edges, and edge values. */
  public static <N, V> MutableValueGraph<N, V> copyOf(ValueGraph<N, V> graph) {
    MutableValueGraph<N, V> copy =

  @Override
  public Set<E> adjacentEdges(E edge) {
    EndpointPair<N> endpointPair = incidentNodes(edge); // Verifies that edge is in this network.
    Set<E> endpointPairIncidentEdges =
        Sets.union(incidentEdges(endpointPair.nodeU()), incidentEdges(endpointPair.nodeV()));
    return edgeInvalidatableSet(
        Sets.difference(endpointPairIncidentEdges, ImmutableSet.of(edge)), edge);
  }

  @Override

* Ein bestimmtes Programm, während es auf dem Betriebssystem **ausgeführt** wird.
    * Dies bezieht sich weder auf die Datei noch auf den Code, sondern **speziell** auf das, was vom Betriebssystem **ausgeführt** und verwaltet wird.
* Jedes Programm, jeder Code **kann nur dann Dinge tun**, wenn er **ausgeführt** wird, wenn also ein **Prozess läuft**.

        while (resultWithDoubleSelfLoop.hasNext()) {
          EndpointPair<N> edge = resultWithDoubleSelfLoop.next();
          if (edge.nodeU().equals(edge.nodeV())) {
            if (!alreadySeenSelfLoop.getAndSet(true)) {
              return edge;
            }
          } else {
            return edge;
          }
        }
        return endOfData();
      }
    };
  }

            "//tensorflow/core/common_runtime/eager:attr_builder",
            "//tensorflow/core/common_runtime/eager:context",
            "//tensorflow/core/common_runtime/eager:copy_to_device_node",
            "//tensorflow/core/common_runtime/eager:eager_executor",
            "//tensorflow/core/common_runtime/eager:eager_operation",
            "//tensorflow/core/common_runtime/eager:execute",

* `dependencies`: Sie alle benötigen die von uns erstellte `X-Token`-Abhängigkeit.

Anstatt also alles zu jeder *Pfadoperation* hinzuzufügen, können wir es dem `APIRouter` hinzufügen.

```Python hl_lines="5-10  16  21" title="app/routers/items.py"
{!../../../docs_src/bigger_applications/app/routers/items.py!}
```

Da der Pfad jeder *Pfadoperation* mit `/` beginnen muss, wie in:

```Python hl_lines="1"
@router.get("/{item_id}")

#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"
#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/c/tf_status.h"

#include "tensorflow/c/eager/dlpack.h"

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/framework/tensor.h"

#include <regex>  // NOLINT
#include <string>

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/common_runtime/function_optimization_registry.h"