package tests_test

import (
	"database/sql"
	"errors"
	"testing"

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

func TestNamedArg(t *testing.T) {
	type NamedUser struct {
		gorm.Model
		Name1 string
		Name2 string
		Name3 string
	}

	DB.Migrator().DropTable(&NamedUser{})
	DB.AutoMigrate(&NamedUser{})

	namedUser := NamedUser{Name1: "jinzhu1", Name2: "jinzhu2", Name3: "jinzhu3"}
	DB.Create(&namedUser)

 * under the License.
 */
package org.apache.maven.lifecycle.internal;

import java.util.ArrayList;
import java.util.List;

import org.apache.maven.lifecycle.internal.builder.BuilderCommon;
import org.apache.maven.model.Plugin;
import org.apache.maven.plugin.MojoExecution;
import org.apache.maven.plugin.descriptor.MojoDescriptor;
import org.apache.maven.project.MavenProject;

/**
 * <p>

	if updatedAt1.Format(time.RFC3339Nano) == animal.UpdatedAt.Format(time.RFC3339Nano) {
		t.Errorf("UpdatedAt should be updated")
	}

	var animals []Animal
	DB.Find(&animals)
	if count := DB.Model(Animal{}).Where("1=1").Update("CreatedAt", time.Now().Add(2*time.Hour)).RowsAffected; count != int64(len(animals)) {
		t.Error("RowsAffected should be correct when do batch update")
	}

import java.io.InputStream;
import java.io.Reader;
import java.nio.file.Files;
import java.util.Map;
import java.util.Objects;

import org.apache.maven.api.toolchain.InputSource;
import org.apache.maven.toolchain.model.PersistedToolchains;
import org.apache.maven.toolchain.v4.MavenToolchainsStaxReader;

/**
 * Handles deserialization of toolchains from the default textual format.
 *
 * @since 3.3.0

/// note | Nota

Esto es compatible desde la versión `0.115.0` de FastAPI. 🤓

///

## Parámetros de Header con un Modelo Pydantic { #header-parameters-with-a-pydantic-model }

Declara los **parámetros de header** que necesitas en un **modelo Pydantic**, y luego declara el parámetro como `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

/// note | Nota

Isso é possível desde a versão `0.115.0` do FastAPI. 🤓

///

## Parâmetros do Cabeçalho com um Modelo Pydantic { #header-parameters-with-a-pydantic-model }

Declare os **parâmetros de cabeçalho** que você precisa em um **modelo do Pydantic**, e então declare o parâmetro como `Header`:

{* ../../docs_src/header_param_models/tutorial001_an_py310.py hl[9:14,18] *}

如果你有一组具有相关性的**查询参数**，你可以创建一个 **Pydantic 模型**来声明它们。

这将允许你在**多个地方**去**复用模型**，并且一次性为所有参数声明验证和元数据。😎

/// note | 注意

FastAPI 从 `0.115.0` 版本开始支持这个特性。🤓

///

## 使用 Pydantic 模型的查询参数 { #query-parameters-with-a-pydantic-model }

在一个 **Pydantic 模型**中声明你需要的**查询参数**，然后将参数声明为 `Query`：

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** 将会从请求的**查询参数**中**提取**出**每个字段**的数据，并将其提供给你定义的 Pydantic 模型。

///

/// tip | Tipp

Diese gleiche Technik gilt für `Query`, `Cookie` und `Header`. 😎

///

## Cookies mit einem Pydantic-Modell { #cookies-with-a-pydantic-model }

Deklarieren Sie die **Cookie**-Parameter, die Sie benötigen, in einem **Pydantic-Modell**, und deklarieren Sie dann den Parameter als `Cookie`:

{* ../../docs_src/cookie_param_models/tutorial001_an_py310.py hl[9:12,16] *}

Ancak elinizde zaten bir sürü dataclass varsa, bunları FastAPI ile bir web API'yi beslemek için kullanmak güzel bir numaradır. 🤓

///

## `response_model` İçinde Dataclass'lar { #dataclasses-in-response-model }

`response_model` parametresinde `dataclasses` da kullanabilirsiniz:

{* ../../docs_src/dataclasses_/tutorial002_py310.py hl[1,6:12,18] *}

Dataclass otomatik olarak bir Pydantic dataclass'ına dönüştürülür.

		// these dialects do not support the "returning" clause
		return
	default:
		// This user struct will leverage the existing users table, but override
		// the Name field to default to null.
		type user struct {
			gorm.Model
			Name string `gorm:"default:null"`
		}
		u1 := user{}

		if results := DB.Create(&u1); results.Error != nil {
			t.Fatalf("errors happened on create: %v", results.Error)
		} else if results.RowsAffected != 1 {