### Top-level application { #top-level-application }

First, create the main, top-level, **FastAPI** application, and its *path operations*:

{* ../../docs_src/sub_applications/tutorial001_py39.py hl[3, 6:8] *}

### Sub-application { #sub-application }

Then, create your sub-application, and its *path operations*.

This sub-application is just another standard FastAPI application, but this is the one that will be "mounted":

## Using the `jsonable_encoder` in a `Response` { #using-the-jsonable-encoder-in-a-response }

Because **FastAPI** doesn't make any changes to a `Response` you return, you have to make sure its contents are ready for it.

For example, you cannot put a Pydantic model in a `JSONResponse` without first converting it to a `dict` with all the data types (like `datetime`, `UUID`, etc) converted to JSON-compatible types.

  /** Maps a bucket to the "entry" of its first element. */
  private transient int[] hashTableKToV;

  /** Maps a bucket to the "entry" of its first element. */
  private transient int[] hashTableVToK;

  /** Maps an "entry" to the "entry" that follows it in its bucket. */
  private transient int[] nextInBucketKToV;

  /** Maps an "entry" to the "entry" that follows it in its bucket. */

  private LinkedHashMultiset(int distinctElements) {
    super(Maps.newLinkedHashMapWithExpectedSize(distinctElements));
  }

  /**
   * @serialData the number of distinct elements, the first element, its count, the second element,
   *     its count, and so on
   */
  @GwtIncompatible
  @J2ktIncompatible
    private void writeObject(ObjectOutputStream stream) throws IOException {
    stream.defaultWriteObject();

Even if they are all in `localhost`, they use different protocols or ports, so, they are different "origins".

## Steps { #steps }

So, let's say you have a frontend running in your browser at `http://localhost:8080`, and its JavaScript is trying to communicate with a backend running at `http://localhost` (because we don't specify a port, the browser will assume the default port `80`).

Each of those response `dict`s can have a key `model`, containing a Pydantic model, just like `response_model`.

**FastAPI** will take that model, generate its JSON Schema and include it in the correct place in OpenAPI.

For example, to declare another response with a status code `404` and a Pydantic model `Message`, you can write:

            }
        } catch (final IOException e) {
            throw new ThemeException("Failed to install " + artifact, e);
        }
    }

    /**
     * Uninstalls a theme by removing all its associated files and directories.
     *
     * @param artifact the theme artifact to uninstall
     */
    public void uninstall(final Artifact artifact) {
        final String themeName = getThemeName(artifact);

Keep existing translations as they are if the term is already translated.

    cm: AbstractContextManager[_T],
) -> AsyncGenerator[_T, None]:
    # blocking __exit__ from running waiting on a free thread
    # can create race conditions/deadlocks if the context manager itself
    # has its own internal pool (e.g. a database connection pool)
    # to avoid this we let __exit__ run without a capacity limit
    # since we're creating a new limiter for each call, any non-zero limit
    # works (1 is arbitrary)

  }

  @Override
  public final int size() {
    return Ints.saturatedCast(size);
  }

  /**
   * @serialData the number of distinct elements, the first element, its count, the second element,
   *     its count, and so on
   */
  @GwtIncompatible
  @J2ktIncompatible
    private void writeObject(ObjectOutputStream stream) throws IOException {
    stream.defaultWriteObject();