6. **Testing**:
   - Assume the submitter tested the code. If testing is unclear, ask for details (e.g., “How was this tested?”).
   - Reject untested PRs unless testing is infeasible, then assist with test setup.

## Tips for Success

- **Small PRs**: Easier to review, faster to merge. Split large changes logically.
- **Clear Commits**: Use `git rebase -i` to refine history before submitting.

/// info | 정보

Pydantic v1에서는 해당 메서드가 `.dict()`로 불렸으며, Pydantic v2에서는 `.model_dump()`로 이름이 변경되었습니다. `.dict()`는 여전히 지원되지만 더 이상 권장되지 않습니다.

여기에서 사용하는 예제는 Pydantic v1과의 호환성을 위해 `.dict()`를 사용하지만, Pydantic v2를 사용할 수 있다면 `.model_dump()`를 사용하는 것이 좋습니다.

///

### `**user_in.dict()` 에 대하여

#### Pydantic의 `.dict()`

`user_in`은 Pydantic 모델 클래스인 `UserIn`입니다.

Pydantic 모델은 모델 데이터를 포함한 `dict`를 반환하는 `.dict()` 메서드를 제공합니다.

## Response with arbitrary `dict` { #response-with-arbitrary-dict }

You can also declare a response using a plain arbitrary `dict`, declaring just the type of the keys and values, without using a Pydantic model.

This is useful if you don't know the valid field/attribute names (that would be needed for a Pydantic model) beforehand.

In this case, you can use `typing.Dict` (or just `dict` in Python 3.9 and above):

import static com.google.common.collect.testing.features.CollectionSize.ZERO;
import static com.google.common.collect.testing.google.ReflectionFreeAssertThrows.assertThrows;
import static java.util.Arrays.asList;
import static java.util.Collections.nCopies;
import static java.util.Collections.singletonList;
import static java.util.Collections.sort;

import com.google.common.annotations.GwtCompatible;

    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_LONGS);
  }

  public void testScale_index_compute_intVarargs() {
    int[] dataset = Ints.toArray(SIXTEEN_SQUARES_INTEGERS);
    assertThat(Quantiles.scale(10).index(1).compute(dataset))
        .isWithin(ALLOWED_ERROR)
        .of(SIXTEEN_SQUARES_DECILE_1);
    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_INTEGERS);
  }

    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_LONGS);
  }

  public void testScale_index_compute_intVarargs() {
    int[] dataset = Ints.toArray(SIXTEEN_SQUARES_INTEGERS);
    assertThat(Quantiles.scale(10).index(1).compute(dataset))
        .isWithin(ALLOWED_ERROR)
        .of(SIXTEEN_SQUARES_DECILE_1);
    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_INTEGERS);
  }

	"github.com/minio/minio/internal/logger/target/http"
	"github.com/minio/minio/internal/logger/target/kafka"
)

// Console logger target
type Console struct {
	Enabled bool `json:"enabled"`
}

// Audit/Logger constants
const (
	Endpoint      = "endpoint"
	AuthToken     = "auth_token"
	ClientCert    = "client_cert"
	ClientKey     = "client_key"
	BatchSize     = "batch_size"
	QueueSize     = "queue_size"

#### 用其它模型中的内容生成 Pydantic 模型

上例中 ，从 `user_in.dict()` 中得到了 `user_dict`，下面的代码：

```Python
user_dict = user_in.dict()
UserInDB(**user_dict)
```

等效于：

```Python
UserInDB(**user_in.dict())
```

……因为 `user_in.dict()` 是字典，在传递给 `UserInDB` 时，把 `**` 加在  `user_in.dict()` 前，可以让 Python 进行**解包**。

这样，就可以用其它 Pydantic 模型中的数据生成 Pydantic 模型。

#### 解包 `dict` 和更多关键字

import org.codelibs.fess.app.web.CrudMode;
import org.codelibs.fess.app.web.admin.dict.stopwords.UploadForm;
import org.codelibs.fess.app.web.api.ApiResult;
import org.codelibs.fess.app.web.api.admin.FessApiAdminAction;
import org.codelibs.fess.dict.stopwords.StopwordsFile;
import org.codelibs.fess.dict.stopwords.StopwordsItem;
import org.lastaflute.web.Execute;
import org.lastaflute.web.response.JsonResponse;

        int key1 = rand.nextInt();
        // flip input bit for key2
        int key2 = key1 ^ (1 << i);
        // get hashes
        int hash1 = function.hashInt(key1).asInt();
        int hash2 = function.hashInt(key2).asInt();
        // test whether the hash values have same output bits
        same |= ~(hash1 ^ hash2);
        // test whether the hash values have different output bits
        diff |= hash1 ^ hash2;