* 먼저, 해당 pull request가 해결하려는 **문제를 이해하는지** 확인하세요. GitHub Discussion 또는 이슈에서 더 긴 논의가 있었을 수도 있습니다.

* Pull request가 실제로 필요하지 않을 가능성도 큽니다. 문제가 **다른 방식**으로 해결될 수 있기 때문입니다. 그런 경우 그 방법을 제안하거나 질문할 수 있습니다.

### 스타일에 너무 신경 쓰지 않기 { #dont-worry-about-style }

* 커밋 메시지 스타일 같은 것에 너무 신경 쓰지 마세요. 저는 커밋을 수동으로 조정해서 squash and merge를 할 것입니다.

* 코드 스타일 규칙도 걱정할 필요 없습니다. 이미 자동화된 도구들이 이를 검사하고 있습니다.

        QueryBuilder initialQuery = QueryBuilders.termQuery("field", "value");
        queryContext.setQueryBuilder(initialQuery);

        queryContext.addQuery(boolQuery -> {
            // Don't add any clauses
        });

        // When no clauses are added to a non-MatchAllQuery, it still wraps in BoolQuery
        QueryBuilder result = queryContext.getQueryBuilder();

   * Table entries are of class Cell; a variant of AtomicLong padded
   * to reduce cache contention on most processors. Padding is
   * overkill for most Atomics because they are usually irregularly
   * scattered in memory and thus don't interfere much with each
   * other. But Atomic objects residing in arrays will tend to be
   * placed adjacent to each other, and so will most often share
   * cache lines (with a huge negative performance impact) without

   * {@code lexicographical(Collections.reverseOrder(comparator))} (consider how each would order
   * {@code [1]} and {@code [1, 1]}).
   */
  // Note: 90% of the time we don't add type parameters or wildcards that serve only to "tweak" the
  // desired return type. However, *nested* generics introduce a special class of problems that we
  // think tip it over into being worthwhile.

considered a vulnerability in TensorFlow.

### Resource allocation

A denial of service caused by one model could bring down the entire server, but
we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

Outre les types singuliers normaux comme `str`, `int`, `float`, etc. vous pouvez utiliser des types singuliers plus complexes qui héritent de `str`.

Pour voir toutes les options dont vous disposez, consultez [l’aperçu des types de Pydantic](https://docs.pydantic.dev/latest/concepts/types/). Vous verrez quelques exemples au chapitre suivant.

            return ((Integer) object) % 5; // fake tons of collisions!
          }
        };

    // Don't let the elements be in such a predictable order
    list = shuffledCopy(list, new Random(1));

    sort(list, arbitrary);

    // Now we don't care what order it's put the list in, only that
    // comparing any pair of elements gives the answer we expect.
    testComparator(arbitrary, list);

            return ((Integer) object) % 5; // fake tons of collisions!
          }
        };

    // Don't let the elements be in such a predictable order
    list = shuffledCopy(list, new Random(1));

    sort(list, arbitrary);

    // Now we don't care what order it's put the list in, only that
    // comparing any pair of elements gives the answer we expect.
    testComparator(arbitrary, list);

Il en serait de même si vous aviez quelque chose comme une <dfn title="Une union entre plusieurs types signifie « n'importe lequel de ces types ».">union</dfn> entre différents types dont un ou plusieurs ne sont pas des types Pydantic valides, par exemple ceci échouerait 💥 :

{* ../../docs_src/response_model/tutorial003_04_py310.py hl[8] *}

Il est également conçu pour servir de référence ultérieure, afin que vous puissiez revenir voir exactement ce dont vous avez besoin.

## Exécuter le code { #run-the-code }

Tous les blocs de code peuvent être copiés et utilisés directement (il s'agit en fait de fichiers Python testés).