```

就会生成如下结果：

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

或更精准，直接把可能会用到的内容与 `user_dict` 一起使用：

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

#### 用其它模型中的内容生成 Pydantic 模型

//
//	// assign an email if the record is not found
//	db.Where(User{Name: "non_existing"}).Attrs(User{Email: "******@****.***"}).FirstOrInit(&user)
//	// user -> User{Name: "non_existing", Email: "******@****.***"}
//
//	// assign email regardless of if record is found
//	db.Where(User{Name: "jinzhu"}).Assign(User{Email: "******@****.***"}).FirstOrInit(&user)

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

Oder, präziser, `user_dict` wird direkt verwendet, welche Werte es auch immer haben mag:

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

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

もっと正確に言えば、`user_dict`を将来的にどんな内容であっても直接使用することになります:

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

#### 別のモデルからつくるPydanticモデル

package tests_test

import (
	"testing"
	"time"

	"gorm.io/gorm"
)

func TestDefaultValue(t *testing.T) {
	type Harumph struct {
		gorm.Model
		Email   string    `gorm:"not null;index:,unique"`
		Name    string    `gorm:"notNull;default:foo"`
		Name2   string    `gorm:"size:233;not null;default:'foo'"`
		Name3   string    `gorm:"size:233;notNull;default:''"`
		Age     int       `gorm:"default:18"`

# TODO: pv2 add version with Pydantic v2
@needs_pydanticv1
def test_create_user(client):
    test_user = {"email": "******@****.***", "password": "secret"}
    response = client.post("/users/", json=test_user)
    assert response.status_code == 200, response.text
    data = response.json()
    assert test_user["email"] == data["email"]
    assert "id" in data
    response = client.post("/users/", json=test_user)

	}
}

// RMetricName - name of replication metric
type RMetricName string

const (
	// Large - objects larger than 128MiB
	Large RMetricName = "Large"
	// Small - objects smaller than 128MiB
	Small RMetricName = "Small"
	// Total - metric pertaining to totals
	Total RMetricName = "Total"
)

// ReplQNodeStats holds queue stats for replication per node
type ReplQNodeStats struct {

                        ["username", "email", "full_name", "disabled"],
                        # TODO: remove when deprecating Pydantic v1
                        ["username"],
                    ),
                    "type": "object",
                    "properties": {
                        "username": {"title": "Username", "type": "string"},
                        "email": IsDict(
                            {

    "johndoe": {
        "username": "johndoe",
        "full_name": "John Doe",
        "email": "******@****.***",
        "hashed_password": "$2b$12$EixZaYVK1fsbw1ZfbX3OXePaWxn96p36WQoeG6Lruj3vjPGga31lW",
        "disabled": False,
    },
    "alice": {
        "username": "alice",
        "full_name": "Alice Chains",
        "email": "******@****.***",

	stmt := dryRunDB.Where(
		DB.Where("pizza = ?", "pepperoni").Where(DB.Where("size = ?", "small").Or("size = ?", "medium")),
	).Or(
		DB.Where("pizza = ?", "hawaiian").Where("size = ?", "xlarge"),
	).Find(&Pizza{}).Statement

	execStmt := dryRunDB.Exec("WHERE (pizza = ? AND (size = ? OR size = ?)) OR (pizza = ? AND size = ?)", "pepperoni", "small", "medium", "hawaiian", "xlarge").Statement