}

type UserWithTableNamer struct {
	gorm.Model
	Name string
}

func (UserWithTableNamer) TableName(namer schema.Namer) string {
	return namer.TableName("user")
}

func TestTableWithNamer(t *testing.T) {
	db, _ := gorm.Open(tests.DummyDialector{}, &gorm.Config{
		NamingStrategy: schema.NamingStrategy{
			TablePrefix: "t_",
		},
	})

	sql := db.ToSQL(func(tx *gorm.DB) *gorm.DB {

    name: str
    age: int


@strawberry.type
class Query:
    @strawberry.field
    def user(self) -> User:
        return User(name="Patrick", age=100)


schema = strawberry.Schema(query=Query)


graphql_app = GraphQLRouter(schema)

app = FastAPI()

}

// TableType table type interface
type TableType interface {
	Schema() string
	Name() string
	Type() string
	Comment() (comment string, ok bool)
}

// Migrator migrator interface
type Migrator interface {
	// AutoMigrate
	AutoMigrate(dst ...interface{}) error

	// Database
	CurrentDatabase() string
	FullDataTypeOf(*schema.Field) clause.Expr
	GetTypeAliases(databaseTypeName string) []string

	// Tables

package callbacks

import (
	"fmt"
	"reflect"
	"sort"
	"strings"

	"gorm.io/gorm"
	"gorm.io/gorm/clause"
	"gorm.io/gorm/schema"
	"gorm.io/gorm/utils"
)

// parsePreloadMap extracts nested preloads. e.g.
//
//	// schema has a "k0" relation and a "k7.k8" embedded relation
//	parsePreloadMap(schema, map[string][]interface{}{
//		clause.Associations: {"arg1"},
//		"k1":                {"arg2"},
//		"k2.k3":             {"arg3"},

	Priority   int
}

// ParseIndexes parse schema indexes
func (schema *Schema) ParseIndexes() []*Index {
	indexesByName := map[string]*Index{}
	indexes := []*Index{}

	for _, field := range schema.Fields {
		if field.TagSettings["INDEX"] != "" || field.TagSettings["UNIQUEINDEX"] != "" {
			fieldIndexes, err := parseFieldIndexes(field)
			if err != nil {
				schema.err = err
				break
			}

import (
	"sync"
	"testing"

	"gorm.io/gorm"
	"gorm.io/gorm/clause"
	"gorm.io/gorm/schema"
	"gorm.io/gorm/utils/tests"
)

func BenchmarkSelect(b *testing.B) {
	user, _ := schema.Parse(&tests.User{}, &sync.Map{}, db.NamingStrategy)

	for i := 0; i < b.N; i++ {
		stmt := gorm.Statement{DB: db, Table: user.Table, Schema: user, Clauses: map[string]clause.Clause{}}

你可以在 `Field`、`Query`、`Body` 等中宣告額外資訊。這些資訊會被包含在產生的 JSON Schema 中。

你會在後續文件中學到更多關於加入額外資訊的內容，特別是在宣告範例時。

/// warning

傳入 `Field` 的額外鍵也會出現在你的應用程式所產生的 OpenAPI schema 中。
由於這些鍵不一定屬於 OpenAPI 規格的一部分，一些 OpenAPI 工具（例如 [OpenAPI 驗證器](https://validator.swagger.io/)）可能無法處理你產生的 schema。

///

## 回顧 { #recap }

你可以使用 Pydantic 的 `Field` 為模型屬性宣告額外的驗證與中繼資料。

from fastapi.openapi.models import Schema, SchemaType


@pytest.mark.parametrize(
    "type_value",
    [
        "array",
        ["string", "null"],
        None,
    ],
)
def test_allowed_schema_type(
    type_value: SchemaType | list[SchemaType] | None,
) -> None:
    """Test that Schema accepts SchemaType, List[SchemaType] and None for type field."""
    schema = Schema(type=type_value)
    assert schema.type == type_value

### Générer le schéma OpenAPI { #generate-the-openapi-schema }

Ensuite, utilisez la même fonction utilitaire pour générer le schéma OpenAPI, dans une fonction `custom_openapi()` :

{* ../../docs_src/extending_openapi/tutorial001_py310.py hl[2,15:21] *}

### Modifier le schéma OpenAPI { #modify-the-openapi-schema }

* Adicionar um **JSON Schema** para a resposta, na *operação de rota* do OpenAPI.
    * Isso será usado pela **documentação automática**.
    * Também será usado por ferramentas de geração automática de código do cliente.