if (parent.containsKey(LANG_KEY)) {
            final List<java.util.Map.Entry<String, Object>> list = new ArrayList<>(parent.entrySet());
            Collections.sort(list, (o1, o2) -> {
                final String k1 = o1.getKey();
                if (LANG_KEY.equals(k1)) {
                    return -1;
                }
                final String k2 = o2.getKey();

                }
                buckets.add(new StringTerms.Bucket(term, rand.nextInt(10000), subAggs, true, 0L, DocValueFormat.RAW));
            }

            Collections.sort(buckets, (a, b) -> a.compareKey(b));
            return new StringTerms(
                "terms",
                BucketOrder.key(true),
                BucketOrder.count(false),
                topNSize,

 *     <li><code>sp</code></li>
 *     </ol>
 *     Unknown qualifiers are considered after known qualifiers,
 *     with lexical order (case-insensitive in the English locale).
 *     <code>ga</code> and <code>final</code> sort the same as not having a qualifier.
 *   </li>
 * <li>A hyphen usually precedes a qualifier, and is always less important than digits/number. For example

    "docs_src/pydantic_v1_in_v2/tutorial003_an_py310.py",
    "docs_src/pydantic_v1_in_v2/tutorial004_an_py310.py",
]

[tool.coverage.report]
show_missing = true
sort = "-Cover"

[tool.coverage.html]
show_contexts = true

[tool.ruff.lint]
select = [
    "E",  # pycodestyle errors
    "W",  # pycodestyle warnings
    "F",  # pyflakes
    "I",  # isort

			}
			f.Close()
		}

		bs, err := os.ReadFile(goldenFile)
		if err != nil {
			t.Fatalf("opening golden.txt for package %q: %v", fi.Name(), err)
		}
		wanted := strings.Split(string(bs), "\n")
		slices.Sort(wanted)
		for _, feature := range wanted {
			if feature == "" {
				continue
			}
			_, ok := w.features[feature]
			if !ok {
				t.Errorf("package %s: missing feature %q", fi.Name(), feature)
			}

///

## Utiliser plusieurs modèles { #multiple-models }

Voici une idée générale de l'apparence des modèles avec leurs champs de mot de passe et les endroits où ils sont utilisés :

{* ../../docs_src/extra_models/tutorial001_py310.py hl[7,9,14,20,22,27:28,31:33,38:39] *}

### À propos de `**user_in.model_dump()` { #about-user-in-model-dump }

import static com.google.common.collect.SortedLists.KeyAbsentBehavior.NEXT_LOWER;
import static com.google.common.collect.SortedLists.KeyPresentBehavior.ANY_PRESENT;
import static java.util.Collections.sort;
import static java.util.Objects.requireNonNull;

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import com.google.common.collect.SortedLists.KeyAbsentBehavior;

import static com.google.common.base.Preconditions.checkNotNull;
import static java.lang.Math.max;
import static java.util.Arrays.asList;
import static java.util.Collections.singletonMap;
import static java.util.Collections.sort;
import static junit.framework.Assert.assertEquals;
import static junit.framework.Assert.assertFalse;
import static junit.framework.Assert.assertTrue;
import static junit.framework.Assert.fail;

  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }
  std::sort(grads.begin(), grads.end());
  return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();

                    list.add(new BindingToBeanEntry<>(key).toBeanEntry(bean).prioritize(bean.getRank()));
                }
            }
            if (!list.isEmpty()) {
                list.sort(getPriorityComparator());
                //noinspection unchecked
                return () -> (Q) getInstance(list.iterator().next());
            } else if (dep.optional()) {
                return () -> null;