# Dependencies in path operation decorators

In some cases you don't really need the return value of a dependency inside your *path operation function*.

Or the dependency doesn't return a value.

But you still need it to be executed/solved.

For those cases, instead of declaring a *path operation function* parameter with `Depends`, you can add a `list` of `dependencies` to the *path operation decorator*.

The key factor is that a dependency should be a "callable".

A "**callable**" in Python is anything that Python can "call" like a function.

So, if you have an object `something` (that might _not_ be a function) and you can "call" it (execute it) like:

```Python
something()
```

or

```Python
something(some_argument, some_keyword_argument="foo")
```

then it is a "callable".

## Classes as dependencies

      implements Serializable {
    private final Function<? super A, ? extends B> forwardFunction;
    private final Function<? super B, ? extends A> backwardFunction;

    private FunctionBasedConverter(
        Function<? super A, ? extends B> forwardFunction,
        Function<? super B, ? extends A> backwardFunction) {
      this.forwardFunction = checkNotNull(forwardFunction);

// aggregation.
//
// Aggregation functions - An expression that involves aggregation of
// rows in some manner. Requires all input rows to be processed,
// before a result is returned.
//
// Row function - An expression that depends on a value in the
// row. They have an output for each input row.
//
// Some types of a queries are not valid. For example, an aggregation

      }
    }
  }

  /**
   * Returns a function that delegates to the {@link Interner#intern} method of the given interner.
   *
   * @since 8.0
   */
  public static <E> Function<E, E> asFunction(Interner<E> interner) {
    return new InternerFunction<>(checkNotNull(interner));
  }

  private static class InternerFunction<E> implements Function<E, E> {

    private final Interner<E> interner;

    assertSame(not, pool.intern(not));
  }

  public void testAsFunction_simplistic() {
    String canonical = "a";
    String not = new String("a");

    Function<String, String> internerFunction =
        Interners.asFunction(Interners.<String>newStrongInterner());

    assertSame(canonical, internerFunction.apply(canonical));
    assertSame(canonical, internerFunction.apply(not));
  }

      }
    }
  }

  /**
   * Returns a function that delegates to the {@link Interner#intern} method of the given interner.
   *
   * @since 8.0
   */
  public static <E> Function<E, E> asFunction(Interner<E> interner) {
    return new InternerFunction<>(checkNotNull(interner));
  }

  private static class InternerFunction<E> implements Function<E, E> {

    private final Interner<E> interner;

/// note | "Technical Details"

When you import `Query`, `Path` and others from `fastapi`, they are actually functions.

That when called, return instances of classes of the same name.

So, you import `Query`, which is a function. And when you call it, it returns an instance of a class also named `Query`.

These functions are there (instead of just using the classes directly) so that your editor doesn't mark errors about their types.

    }
    return nodeConnections.buildOrThrow();
  }

  @SuppressWarnings("unchecked")
  private static <N> GraphConnections<N, Presence> connectionsOf(Graph<N> graph, N node) {
    Function<N, Presence> edgeValueFn =
        (Function<N, Presence>) Functions.constant(Presence.EDGE_EXISTS);
    return graph.isDirected()
        ? DirectedGraphConnections.ofImmutable(node, graph.incidentEdges(node), edgeValueFn)

#include "tensorflow/core/common_runtime/eager/attr_builder.h"

namespace tensorflow {
namespace gradients {

// =============== Experimental C++ API for computing gradients ===============

// Sample gradient function:
//
// class AddGradientFunction : public GradientFunction {
//  public:
//   Status Compute(Context* ctx,
//                  absl::Span<AbstractTensorHandle* const> grad_inputs,