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Repository and Unit of Work in Domain-Driven Design

Repository and Unit of Work in Domain-Driven Design

Welcome to the fourth article in our Domain-Driven Design (DDD) series. In this installment, we'll...

Welcome to the fourth article in our Domain-Driven Design (DDD) series. In this installment, we'll explore the essential concepts of Repository and Unit of Work patterns and how they play a pivotal role in managing domain objects and transactions in DDD.

Understanding the Need for Repository and Unit of Work

In the previous articles, we discussed the importance of modeling your domain using entities, value objects, and aggregates. As your domain model becomes more complex, you'll likely need mechanisms to persist and retrieve these domain objects. This is where the Repository pattern comes into play.

The Repository Pattern

The Repository pattern is a design pattern that acts as an abstraction layer between your domain model and the data access code. It provides a set of methods for querying and manipulating domain objects without exposing the underlying data store (such as a database or web service). This separation allows your domain model to remain independent of the data access details, promoting maintainability and testability.

Consider a scenario where you have a User entity in your domain model. Without a repository, your code might look like this when fetching a user:

// Fetching a user without a repository
const user = database.query("SELECT * FROM users WHERE id = ?", userId);

However, with the Repository pattern, you can achieve the same functionality while keeping your domain code clean:

// Fetching a user using a repository
const user = userRepository.getById(userId);

The UserRepository abstracts away the data access details, making your code more readable and maintainable.

The Unit of Work Pattern

In many applications, transactions involve multiple operations on domain objects. Ensuring that these operations are atomic (either all succeed or all fail) is critical for data consistency. This is where the Unit of Work pattern comes into play.

The Unit of Work pattern tracks changes made to domain objects within a transaction and ensures that all changes are either committed together or rolled back if an error occurs. This pattern is particularly useful when dealing with complex business processes that involve multiple entities.

Implementing Repository and Unit of Work

Let's delve into some code examples to see how you can implement these patterns in TypeScript:

Repository Example

interface Repository {
 getById(id: string): T | null;
 save(entity: T): void;
 delete(entity: T): void;
 // Additional query methods
}

class UserRepository implements Repository {
 getById(id: string): User | null {
 // Database query logic here
 }

 save(user: User): void {
 // Save user logic here
 }

 delete(user: User): void {
 // Delete user logic here
 }

 // Additional query methods implementation
}

Unit of Work Example

class UnitOfWork {
 private unitOfWorkData: Map = new Map();

 registerNew(entity: Entity): void {
 // Add entity to unitOfWorkData as new
 }

 registerDirty(entity: Entity): void {
 // Mark entity in unitOfWorkData as dirty
 }

 registerDeleted(entity: Entity): void {
 // Mark entity in unitOfWorkData as deleted
 }

 commit(): void {
 // Commit changes in unitOfWorkData to the data store
 }

 rollback(): void {
 // Rollback changes in unitOfWorkData
 }
}

Benefits of Repository and Unit of Work

  • Separation of Concerns:Repository separates domain logic from data access logic, promoting a clean architecture.
  • Testability:With the repository, you can easily mock data access for unit testing.
  • Transaction Management:Unit of Work ensures that transactions involving multiple domain objects are managed effectively.

Conclusion

In this article, we explored the Repository and Unit of Work patterns in Domain-Driven Design. These patterns are invaluable when dealing with data access and transaction management in complex domain models. By implementing them, you can keep your domain logic clean, maintainable, and testable.

In the next article, we'll dive deeper into Domain Services and Factories, uncovering how they encapsulate domain logic and facilitate object creation. Stay tuned for more DDD insights!

Ресурс : dev.to


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