var res *Checksum
		for _, header := range trailing {
			var duplicates bool
			switch {
			case strings.EqualFold(header, ChecksumCRC32C.Key()):
				duplicates = res != nil
				res = NewChecksumWithType(ChecksumCRC32C|ChecksumTrailing, "")
			case strings.EqualFold(header, ChecksumCRC32.Key()):
				duplicates = res != nil
				res = NewChecksumWithType(ChecksumCRC32|ChecksumTrailing, "")

				xhttp.AmzObjectAttributes: []string{"test1,test2"},
			},
			wantObjectAttrs: map[string]struct{}{
				"test1": {}, "test2": {},
			},
		},
		{
			name: "multiple header lines with some duplicates",
			headers: http.Header{
				xhttp.AmzObjectAttributes: []string{"test1,test2", "test3,test4", "test4,test3"},
			},
			wantObjectAttrs: map[string]struct{}{
				"test1": {}, "test2": {}, "test3": {}, "test4": {},

* `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

	if l <= 1 {
		return l
	}
	for i := 1; i < l; i++ {
		if !data.Less(p, i) {
			continue
		}
		p++
		if p < i {
			data.Swap(p, i)
		}
	}
	return p + 1
}

// Remove any duplicates and return unique entries.
func uniqueEntries(paths []string) []string {
	sort.Strings(paths)
	n := uniq(sort.StringSlice(paths))
	return paths[:n]
}

// Init sets the trimStrings to possible GOPATHs

    # 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]: '

			hi := lo
			if p.peek() == '-' {
				p.next()
				hi = p.registerNumber(p.next().String())
			}
			if hi < lo {
				lo, hi = hi, lo
			}
			// Check there are no duplicates in the register list.
			for i := 0; lo <= hi && i < maxReg; i++ {
				if bits&(1<<lo) != 0 {
					p.errorf("register R%d already in list", lo)
				}
				bits |= 1 << lo
				lo++
			}
		default:

				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")
			}