* `frozenset`:
    * In requests and responses, treated the same as a `set`:
        * In requests, a list will be read, eliminating duplicates and converting it to a `set`.
        * In responses, the `set` will be converted to a `list`.
        * The generated schema will specify that the `set` values are unique (using JSON Schema's `uniqueItems`).
* `bytes`:

		name string
		args args
		want []string
	}{
		{
			name: "No duplicates",
			args: args{ports: []string{"1234", "2345"}},
			want: []string{"1234", "2345"},
		},
		{
			name: "Sequential Duplicates",
			args: args{ports: []string{"1234", "1234", "2345", "2345"}},
			want: []string{"1234", "2345"},
		},
		{
			name: "Mixed Duplicates",
			args: args{ports: []string{"1234", "2345", "1234", "2345"}},

        try (FileReader reader = new FileReader(file)) {
            List<UpgradedProperty> upgradedProperties = new Gson().fromJson(reader, new TypeToken<List<UpgradedProperty>>() {}.getType());
            // FIXME There should be no duplicates, yet there are some
            return upgradedProperties.stream()
                .distinct()
                .collect(ImmutableList.toImmutableList());
        } catch (IOException e) {

```Python hl_lines="1  14"
{!> ../../docs_src/body_nested_models/tutorial003.py!}
```

////

With this, even if you receive a request with duplicate data, it will be converted to a set of unique items.

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

And it will be annotated / documented accordingly too.

## Nested Models

    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.
    # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates
    default_cc_opt_flags = '-Wno-sign-compare'
  question = ('Please specify optimization flags to use during compilation when'
              ' bazel option "--config=opt" is specified [Default is %s]: '

				break
			}
		}

		if requestedVersions > 0 && requestedVersions == nVersions {
			merged = append(merged, versions[0]...)
			break
		}
	}

	// Sanity check. Enable if duplicates show up.
	if false {
		found := make(map[[16]byte]struct{})
		for _, ver := range merged {
			if _, ok := found[ver.header.VersionID]; ok {
				panic("found dupe")
			}

"getById","getElementsByName","disconnectedMatch","cssHas","querySelector","filter","attrId","getAttributeNode","tag","className","input","innerHTML","compare","sortDetached","expr","elements","matchesSelector","attr","attrHandle","uniqueSort","duplicates","sortStable","createPseudo","relative",">"," ","+","~","preFilter","excess","unquoted","nodeNameSelector","expectedNodeName","pattern","operator","check","result","what","_argument","simple","forward","ofType","_context","xml","outerCache","no...

"getById","getElementsByName","disconnectedMatch","cssHas","querySelector","filter","attrId","getAttributeNode","tag","className","input","innerHTML","compare","sortDetached","expr","elements","matchesSelector","attr","attrHandle","uniqueSort","duplicates","sortStable","createPseudo","relative",">"," ","+","~","preFilter","excess","unquoted","nodeNameSelector","expectedNodeName","pattern","operator","check","result","what","_argument","simple","forward","ofType","_context","xml","outerCache","no...

```Python hl_lines="1  14"
{!../../docs_src/body_nested_models/tutorial003.py!}
```

Com isso, mesmo que você receba uma requisição contendo dados duplicados, ela será convertida em um conjunto de itens exclusivos.

E sempre que você enviar esses dados como resposta, mesmo se a fonte tiver duplicatas, eles serão gerados como um conjunto de itens exclusivos.

E também teremos anotações/documentação em conformidade.

## Modelos aninhados

///

## Duplicate headers

It is possible to receive duplicate headers. That means, the same header with multiple values.

You can define those cases using a list in the type declaration.

You will receive all the values from the duplicate header as a Python `list`.