Clean Architecture & Design Patterns in Practice · レッスン

Data MapperとDTO

データベースやAPIとのやり取りに備え、内部のEntitiesと外部のデータ構造（DTOs）の間でデータをマッピングする方法を学びます。

「Data MapperとDTO」はCoddyKit上の無料Clean Architecture & Design Patterns in Practiceレッスンです。これはレッスン3/4です。下記で完全なレッスンを無料で読むことができます。その後、ブラウザ内の組み込みコードエディタと24時間対応のAIチューターでハンズオン演習できます。これはClean Architecture & Design Patterns in Practice学習パスの一部であり、ウェブとCoddyKitアプリ全体で進捗が同期されます。 Clean Architecture & Design Patterns in Practiceコースには全4レッスンが含まれています。

このレッスンの一部はまだ翻訳されておらず、英語で表示されています。

Mapping Data: Why We Need It

In Clean Architecture, your core business logic (Entities and Use Cases) should be independent of external details like databases or web frameworks.

But how do your internal data structures communicate with the outside world? This is where Data Mappers and Data Transfer Objects (DTOs) come in.

Entities vs. External Data

Your Entities contain crucial business rules and are designed for your domain logic. They often have methods and complex relationships.

Exposing these entities directly to external layers (like a database or an API) can lead to:

Tight Coupling: Changes in your database or API might force changes in your core entities.
Security Risks: You might expose sensitive internal data.
Data Shape Mismatch: External systems often need data in a different format than your internal domain model.

Introducing Data Transfer Objects (DTOs)

A Data Transfer Object (DTO) is a simple object used to transfer data between different layers or processes. Think of it as a plain data container.

Key characteristics of DTOs:

They only hold data, typically public fields or simple getters/setters.
They contain no business logic.
They are designed for specific external communication needs (e.g., API request/response, database record).

DTOs in Action: An Example

Let's imagine a Product entity in our core domain and a ProductDto for communicating with an external API.

Notice how the DTO fields might be named differently or represent a subset of the entity's data.

class Product { // Internal Entity
  private String id;
  private String name;
  private double price;
  // ... business methods
}

class ProductDto { // External DTO
  public String productId;
  public String productName;
  public double productPrice;
  // No business logic here
}

The Role of Data Mappers

A Data Mapper is an object responsible for converting data between your internal Entities and external DTOs (and vice-versa).

It acts as a translator, ensuring your core domain remains clean and isolated. Mappers protect your entities from changes in external data formats.

Implementing a Simple Data Mapper

A data mapper typically has methods to convert from an entity to a DTO, and from a DTO back to an entity.

This allows controlled data flow and transformation.

class ProductMapper {
  public ProductDto toDto(Product product) {
    if (product == null) return null;
    return new ProductDto(
      product.getId(),
      product.getName(),
      product.getPrice()
    );
  }

  public Product toEntity(ProductDto dto) {
    if (dto == null) return null;
    return new Product(
      dto.productId,
      dto.productName,
      dto.productPrice
    );
  }
}

Using the Data Mapper

Here's how you'd use a ProductMapper to convert between your internal Product entity and its external ProductDto representation.

Try running this example!

public class Main {
  // Product Entity (simplified for demo)
  static class Product {
    private String id;
    private String name;
    private double price;

    public Product(String id, String name, double price) {
      this.id = id;
      this.name = name;
      this.price = price;
    }
    public String getId() { return id; }
    public String getName() { return name; }
    public double getPrice() { return price; }
  }

  // Product DTO (simplified for demo)
  static class ProductDto {
    public String productId;
    public String productName;
    public double productPrice;

    public ProductDto(String productId, String productName, double productPrice) {
      this.productId = productId;
      this.productName = productName;
      this.productPrice = productPrice;
    }
  }

  // Data Mapper
  static class ProductMapper {
    public ProductDto toDto(Product product) {
      if (product == null) return null;
      return new ProductDto(
        product.getId(),
        product.getName(),
        product.getPrice()
      );
    }

    public Product toEntity(ProductDto dto) {
      if (dto == null) return null;
      return new Product(
        dto.productId,
        dto.productName,
        dto.productPrice
      );
    }
  }

  public static void main(String[] args) {
    Product originalProduct = new Product("A101", "Keyboard", 75.00);
    ProductMapper mapper = new ProductMapper();

    ProductDto productDto = mapper.toDto(originalProduct);
    System.out.println("DTO Name: " + productDto.productName);

    Product convertedProduct = mapper.toEntity(productDto);
    System.out.println("Entity Name: " + convertedProduct.getName());
  }
}

DTOs for Different Contexts

You don't just need one DTO per entity! Different external interactions might require different data shapes:

ProductRequestDto: For creating or updating a product via an API.
ProductResponseDto: For sending product details back from an API.
ProductSummaryDto: For a list view, only showing ID, name, and a short description.

Each DTO serves a specific purpose, keeping data transfer lean and relevant.

Benefits of Mappers and DTOs

Using Data Mappers and DTOs offers significant advantages in Clean Architecture:

Decoupling: Protects your core domain from external changes.
Flexibility: Easily adapt to new external data formats without altering entities.
Security: Control exactly what data is exposed or accepted.
Clear Contracts: DTOs define explicit contracts for external communication.
Testability: Mappers are simple to unit test in isolation.

Test Your Knowledge

Which of the following best describes the primary purpose of a Data Transfer Object (DTO) in Clean Architecture?

Recap: Mappers & DTOs

You've learned how Data Mappers and Data Transfer Objects (DTOs) are vital for maintaining the independence of your core domain in Clean Architecture.

DTOs are plain data structures for external communication.
Data Mappers translate between your internal Entities and these external DTOs.

This pattern ensures your business logic remains pure, flexible, and decoupled from external concerns.

よくある質問

「Data MapperとDTO」レッスンは無料ですか？

はい。「Data MapperとDTO」の完全なテキストはこのウェブで無料で読めます。インタラクティブに演習し（組み込みコードエディタと24時間対応のAIチューター）、Clean Architecture & Design Patterns in Practiceコースの残りをアンロックするには、CoddyKit PROにアップグレードしてください。 Clean Architecture & Design Patterns in Practiceコースには全4レッスンが含まれています。

「Data MapperとDTO」で何を学びますか？

データベースやAPIとのやり取りに備え、内部のEntitiesと外部のデータ構造（DTOs）の間でデータをマッピングする方法を学びます。ブラウザで直接実行するハンズオンコードでClean Architecture & Design Patterns in Practiceを演習し、24時間対応のAIチューターがレッスンを進める中での質問に答えます。

Clean Architecture & Design Patterns in Practiceを始めるのに経験は必要ですか？

事前経験は必要ありません。CoddyKitのClean Architecture & Design Patterns in Practiceは初級者から上級者向けに構成されているため、ここから始めるか最初から始めて、自分のペースで進むことができます。これはレッスン3/4です。

「Data MapperとDTO」レッスンにはどのくらい時間がかかりますか？

ほとんどのCoddyKitレッスンは約5～10分かかります。各レッスンはコンパクトでインタラクティブなので、着実に進歩し、ウェブとアプリ全体で正確に前回の場所から再開できます。

このClean Architecture & Design Patterns in Practiceレッスンでコードを書いて実行できますか？

はい。すべてのClean Architecture & Design Patterns in Practiceレッスンに組み込みコードエディタが含まれているため、ブラウザでリアルコードを書いて実行し、即座のAIフィードバックを取得できます。ローカル設定は不要です。

このコースのすべてのレッスン

← Clean Architecture & Design Patterns in Practiceに戻る