But you don't have to worry about them either, incoming dicts are converted automatically and your output is converted automatically to JSON too.

## Bodies of arbitrary `dict`s { #bodies-of-arbitrary-dicts }

You can also declare a body as a `dict` with keys of some type and values of some other type.

Apart from all the fancy words used here, the **Dependency Injection** system is quite simple.

Just functions that look the same as the *path operation functions*.

But still, it is very powerful, and allows you to declare arbitrarily deeply nested dependency "graphs" (trees).

/// tip

All this might not seem as useful with these simple examples.

But you will see how useful it is in the chapters about **security**.

#    -X prop       set non-standard JAVA system property
#   --prop=val
#   --prop val     set fess property (i.e.  -Des.<prop>=<val>)

CDPATH=""
SCRIPT="$0"

# SCRIPT may be an arbitrarily deep series of symlinks. Loop until we have the concrete path.
while [ -h "$SCRIPT" ] ; do
  ls=`ls -ld "$SCRIPT"`
  # Drop everything prior to ->
  link=`expr "$ls" : '.*-> \(.*\)$'`

Mas você também não precisa se preocupar com eles, os dicts de entrada são convertidos automaticamente e sua saída é convertida automaticamente para JSON também.

## Corpos de `dict`s arbitrários

Você também pode declarar um corpo como um `dict` com chaves de algum tipo e valores de outro tipo.

Sem ter que saber de antemão quais são os nomes de campos/atributos válidos (como seria o caso dos modelos Pydantic).

Pero tampoco tienes que preocuparte por ellos, los `dicts` entrantes se convierten automáticamente y tu salida se convierte automáticamente a JSON también.

## Cuerpos de `dict`s arbitrarios

También puedes declarar un cuerpo como un `dict` con claves de algún tipo y valores de algún otro tipo.

{* ../../docs_src/extra_models/tutorial004_py39.py hl[18] *}


## Response with arbitrary `dict` { #response-with-arbitrary-dict }

You can also declare a response using a plain arbitrary `dict`, declaring just the type of the keys and values, without using a Pydantic model.

      return method.invoke(delegate, args);
    }

    @Override
    public String toString() {
      return "some arbitrary string";
    }
  }

  private static class DelegatingInvocationHandlerWithEquals extends DelegatingInvocationHandler {

    DelegatingInvocationHandlerWithEquals(Object delegate) {
      super(delegate);

     *
     * @throws CIFSException if an error occurs during authentication
     *
     */
    boolean close() throws CIFSException;

    /**
     * Authenticate arbitrary credentials represented by the
     * <code>NtlmPasswordAuthentication</code> object against the domain controller
     * specified by the <code>UniAddress</code> parameter. If the credentials are

{* ../../docs_src/extra_models/tutorial004_py39.py hl[18] *}


## Response con `dict` arbitrario

También puedes declarar un response usando un `dict` arbitrario plano, declarando solo el tipo de las claves y valores, sin usar un modelo Pydantic.

 */

package com.google.common.base;

import com.google.common.annotations.GwtCompatible;

/**
 * A time source; returns a time value representing the number of nanoseconds elapsed since some
 * fixed but arbitrary point in time. Note that most users should use {@link Stopwatch} instead of
 * interacting with this class directly.
 *
 * <p><b>Warning:</b> this interface can only be used to measure elapsed time, not wall time.
 *