Let's say you only have a single `item` body parameter from a Pydantic model `Item`.

By default, **FastAPI** will then expect its body directly.

But if you want it to expect a JSON with a key `item` and inside of it the model contents, as it does when you declare extra body parameters, you can use the special `Body` parameter `embed`:

```Python
item: Item = Body(embed=True)
```

as in:

     of this section 3.

3.2 When the Program is Distributed as Source Code:

  a) it must be made available under this Agreement, or if the
  Program (i) is combined with other material in a separate file or
  files made available under a Secondary License, and (ii) the initial
  Contributor attached to the Source Code the notice described in
  Exhibit A of this Agreement, then the Program may be made available

Then, when it's your turn, you do actual "productive" work, you process the menu, decide what you want, get your crush's choice, pay, check that you give the correct bill or card, check that you are charged correctly, check that the order has the correct items, etc.

But to be honest its typically easier to wait until the console stops scrolling
and then run `curl` in another window like this:

    curl -u elastic:password localhost:9200


### Importing the project into IntelliJ IDEA

The minimum IntelliJ IDEA version required to import the Elasticsearch project is 2020.1
Elasticsearch builds using Java 16. When importing into IntelliJ you will need

   * When multiple elements are equivalent according to {@code compareTo()}, only the first one
   * specified is included. To create a copy of a {@code SortedSet} that preserves the comparator,
   * call {@link #copyOfSorted} instead. This method iterates over {@code elements} at most once.
   *
   * <p>Note that if {@code s} is a {@code Set<String>}, then {@code ImmutableSortedSet.copyOf(s)}

    }

    /**
     * Gets the delay time in milliseconds when there are no URLs in the queue.
     *
     * @return the delay time in milliseconds when no URLs are available
     */
    public long getDelayMillisAtNoUrlInQueue() {
        return delayMillisAtNoUrlInQueue;
    }

    /**
     * Sets the delay time in milliseconds when there are no URLs in the queue.
     *

It declares an optional query parameter `q` as a `str`, and then it just returns it.

This is quite simple (not very useful), but will help us focus on how the sub-dependencies work.

## Second dependency, "dependable" and "dependant" { #second-dependency-dependable-and-dependant }

automatically chooses 64 sets, which is *16* 64 = 1024* drives in total.

- *If total number of nodes are of odd number then GCD algorithm provides affinity towards odd number erasure sets to provide for uniform distribution across nodes*. This is to ensure that same number of drives are pariticipating in any erasure set. For example if you have 2 nodes with 180 drives then GCD is 15 but this would lead to uneven distribution, one of the nodes would participate more drives. To avoid this the affinity...

        if (inExample) {
            flagIfReversed(file, errors, currentSnippets);
        }
    }

    /**
     * Only flags when the first two detectable snippets in the block are GROOVY then KOTLIN.
     * Ignores blocks with fewer than two detectable snippets.
     */
    private void flagIfReversed(File file, Map<File, List<Error>> errors, List<Snippet> snippets) {

  /**
   * An object that can capture objects to be closed later, when a {@link ClosingFuture} pipeline is
   * done.
   */
  public static final class DeferredCloser {
    @RetainedWith private final CloseableList list;

    private DeferredCloser(CloseableList list) {
      this.list = list;
    }

    /**
     * Captures an object to be closed when a {@link ClosingFuture} pipeline is done.
     *