In Go, the dependency injection (DI) pattern is implemented through function parameter passing, including value passing and pointer passing. In the DI pattern, dependencies are typically passed as pointers to improve decoupling, reduce lock contention, and support testability. By using pointers, the function is decoupled from the concrete implementation because it only depends on the interface type. Pointer passing also reduces the overhead of passing large objects, thereby reducing lock contention. Additionally, DI pattern makes it easy to write unit tests for functions that use DI pattern because dependencies can be easily mocked.
Function parameter passing dependency injection mode in Go language
Introduction
Dependency injection (DI) is a design pattern that allows an object to obtain its dependencies in a decoupled manner. In Go, DI is usually implemented through function parameter passing.
Types of parameter passing
There are two types of function parameter passing in Go:
Parameter passing in DI mode
In DI mode, dependencies are usually passed as pointers. The benefits of doing this are as follows:
Practical case
Consider a UserService, which needs to access the User Repository:
type UserService struct { userRepository UserRepository } func (s *UserService) CreateUser(user *User) error { return s.userRepository.Create(user) }
We can use the DI pattern to provide a UserRepository instance for the UserService :
func main() { // 创建 UserRepository 实例 userRepository := NewUserRepository() // 创建 UserService 实例并注入 UserRepository userService := UserService{ userRepository: userRepository, } // 使用 UserService user := &User{Name: "John"} err := userService.CreateUser(user) if err != nil { // 处理错误 } }
By using a pointer to pass UserRepository, UserService is decoupled from the specific implementation of UserRepository. We can easily create different implementations for UserRepository and inject them into UserService.
Conclusion
The DI pattern in function argument passing is a powerful and flexible technique in Go for managing dependencies between objects. It improves decoupling, reduces lock contention, and supports testability.
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