"user": {"username": "johndoe", "full_name": "John Doe"},
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 5,
        "item": {
            "name": "Foo",
            "price": 50.5,
            "description": "Some Foo",
            "tax": 0.1,
        },
        "user": {"username": "johndoe", "full_name": "John Doe"},
    }

func getSource(level int) string {
	pc, file, lineNumber, ok := runtime.Caller(level)
	if ok {
		// Clean up the common prefixes
		file = trimTrace(file)
		_, funcName := filepath.Split(runtime.FuncForPC(pc).Name())
		return fmt.Sprintf("%v:%v:%v()", file, lineNumber, funcName)
	}
	return ""
}

// getTrace method - creates and returns stack trace
func getTrace(traceLevel int) []string {
	var trace []string

	var fileName string
	switch {
	case j.Replicate != nil:
		fileName = batchReplName
	case j.KeyRotate != nil:
		fileName = batchKeyRotationName
	case j.Expire != nil:
		fileName = batchExpireName
	default:
		return "", errors.New("unknown job type")
	}
	return pathJoin(batchJobReportsPrefix, j.ID, fileName), nil
}

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

А точніше, використовуючи безпосередньо `user_dict`, з будь-яким його вмістом у майбутньому:

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

from pydantic import BaseModel, EmailStr

app = FastAPI()


class UserIn(BaseModel):
    username: str
    password: str
    email: EmailStr
    full_name: str | None = None


class UserOut(BaseModel):
    username: str
    email: EmailStr
    full_name: str | None = None


@app.post("/user/", response_model=UserOut)
async def create_user(user: UserIn) -> Any:

    password="secret",
    email="******@****.***",
    full_name=None,
)
```

Ou plus exactement, en utilisant `user_dict` directement, quels que soient ses contenus futurs :

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

from pydantic import BaseModel

fake_users_db = {
    "johndoe": {
        "username": "johndoe",
        "full_name": "John Doe",
        "email": "******@****.***",
        "hashed_password": "fakehashedsecret",
        "disabled": False,
    },
    "alice": {
        "username": "alice",
        "full_name": "Alice Wonderson",
        "email": "******@****.***",
        "hashed_password": "fakehashedsecret2",

```Python
UserInDB(
    username="john",
    password="secret",
    email="******@****.***",
    full_name=None,
)
```

或更精准，直接使用 `user_dict`（无论它将来包含什么字段）：

```Python
UserInDB(
    username = user_dict["username"],
    password = user_dict["password"],
    email = user_dict["email"],
    full_name = user_dict["full_name"],
)
```

#### 用另一个模型的内容生成 Pydantic 模型 { #a-pydantic-model-from-the-contents-of-another }

     */
    @Test
    void testWriteBytesWireFormat_NoUnicode() {
        smbComOpenAndX = new SmbComOpenAndX(fileName, access, 0, andx);
        smbComOpenAndX.useUnicode = false;
        byte[] dst = new byte[fileName.length() + 1];
        int result = smbComOpenAndX.writeBytesWireFormat(dst, 0);
        assertEquals(fileName.length() + 1, result);
    }

    /**
     * Test readParameterWordsWireFormat method.
     */

    void testWriteParametersWireFormat() {
        // Given
        String filename = "a\\test\\path.txt";
        int informationLevel = 0x0102;
        Trans2QueryPathInformation trans = new Trans2QueryPathInformation(filename, informationLevel);
        // Expected size: 2 (info level) + 4 (reserved) + filename length + 1 (null terminator)
        byte[] dst = new byte[2 + 4 + filename.length() + 1];

        // When