}
    Range<C> span = span().canonical(domain);
    if (!span.hasLowerBound()) {
      // according to the spec of canonical, neither this ImmutableRangeSet nor
      // the range have a lower bound
      throw new IllegalArgumentException(
          "Neither the DiscreteDomain nor this range set are bounded below");
    } else if (!span.hasUpperBound()) {
      try {
        domain.maxValue();
      } catch (NoSuchElementException e) {

        // Test getter and setter for newInput
        StopwordsItem item = new StopwordsItem(1, "or");
        assertNull(item.getNewInput());

        item.setNewInput("nor");
        assertEquals("nor", item.getNewInput());

        item.setNewInput("");
        assertEquals("", item.getNewInput());

        item.setNewInput(null);
        assertNull(item.getNewInput());
    }

    @Test

    }
    Range<C> span = span().canonical(domain);
    if (!span.hasLowerBound()) {
      // according to the spec of canonical, neither this ImmutableRangeSet nor
      // the range have a lower bound
      throw new IllegalArgumentException(
          "Neither the DiscreteDomain nor this range set are bounded below");
    } else if (!span.hasUpperBound()) {
      try {
        domain.maxValue();
      } catch (NoSuchElementException e) {

        # possibly modified.
        #
        # NB: a `for` loop captures its iteration list before it begins, so
        # changing the positional parameters here affects neither the number of
        # iterations, nor the values presented in `arg`.
        shift                   # remove old arg
        set -- "$@" "$arg"      # push replacement arg
    done
fi

When using a `response_model` or return type, FastAPI won't use the `jsonable_encoder` to convert the data (which would be slower) nor the `JSONResponse` class.

Instead it takes the JSON bytes generated with Pydantic using the response model (or return type) and returns a `Response` with the right media type for JSON directly (`application/json`).

And you could do this even if the data type in the request is not JSON.

For example, in this application we don't use FastAPI's integrated functionality to extract the JSON Schema from Pydantic models nor the automatic validation for JSON. In fact, we are declaring the request content type as YAML, not JSON:

{* ../../docs_src/path_operation_advanced_configuration/tutorial007_py310.py hl[15:20, 22] *}

URLs are abstract:

   * passes through both {@code (x1, y1)} and {@code (x1 + xDelta, y1 + yDelta)}. Includes
   * assertions about all the public instance methods of {@link LinearTransformation} (on both
   * {@code transformation} and its inverse). Since the transformation is expected to be diagonal,
   * neither {@code xDelta} nor {@code yDelta} may be zero.
   */

This is probably not as important or necessary if you use `Annotated`.

///

Here's a **small trick** that can be handy, but you won't need it often.

If you want to:

* declare the `q` query parameter without a `Query` nor any default value
* declare the path parameter `item_id` using `Path`
* have them in a different order
* not use `Annotated`

...Python has a little special syntax for that.

   * passes through both {@code (x1, y1)} and {@code (x1 + xDelta, y1 + yDelta)}. Includes
   * assertions about all the public instance methods of {@link LinearTransformation} (on both
   * {@code transformation} and its inverse). Since the transformation is expected to be diagonal,
   * neither {@code xDelta} nor {@code yDelta} may be zero.
   */