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Table of Contents
What does DIP says exactly?
Why Should You Care About Abstraction?
How to Apply Dependency Inversion in Real Code
Common Mistakes When Applying DIP
Home Java javaTutorial What is the dependency inversion principle? (Rephrased)

What is the dependency inversion principle? (Rephrased)

Jun 29, 2025 am 12:34 AM

The two core views of DIP are: high-level modules should not rely on low-level modules, both should rely on abstraction; abstraction should not rely on details, details should rely on abstraction. Specifically, 1. High-level modules (such as service classes) should not directly rely on specific low-level components (such as database tools), but should be decoupled through interfaces or abstract classes; 2. Abstract (such as interfaces) should be the core of dependencies, and specific implementations should be adapted based on abstractions. This design can improve code testability, enable more flexible replacement and clear separation of concerns. When applying, you need to: 1. Identify key components that have direct dependencies in the system; 2. Define interfaces for these dependencies; 3. Modify dependency classes to use interfaces instead of specific types; 4. Implement interfaces in actual classes. Common misunderstandings include: abstracting for abstraction, forgetting dependency injection, over-dependence on frameworks, and over-designing of invariant parts. Following DIP can improve system flexibility and maintainability, but avoid unnecessary complexity.

What is the dependency inversion principle? (Rephrased)

The Dependency Inversion Principle (DIP) is a design guideline in object-oriented programming that helps make systems more flexible and easier to maintain. At its core, it's about reducing tight coupling between classes by depending on abstractions rather than concrete implementations.

What does DIP says exactly?

The principle is often summarized with two main statements:

  • High-level modules should not depend on low-level modules. Both should depend on abstractions.
  • Abstractions should not depend on details. Details should depend on abstractions.

In practice, this means instead of having your high-level logic (like a service class) directly using a specific low-level component (like a database helper), you define an interface or abstract class that both can rely on.


Why Should You Care About Abstraction?

Let's break down the first part: both high-level and low-level modules should depend on abstractions .

This might sound abstract (pun intended), but here's why it matters:

Imagine you're building an app where payments are processed. If your payment processor class directly uses a PayPal implementation, then switching to Stripe later would mean changing a lot of code. That's fragile and hard to scale.

Instead, if both the payment processor and the payment method (PayPal, Stripe) depends on a common interface like PaymentGateway , swapping out providers become much easier.

So, abstraction gives you:

  • Better testability (you can mock interfaces)
  • Easier swapping of implementations
  • Cleaner separation of concerns

How to Apply Dependency Inversion in Real Code

Here's how you can start applying DIP in your projects:

  • Identify the key components in your system that currently have direct dependencies.
  • Define interfaces for those dependencies.
  • Modify the dependent classes to use the interfaces instead of concrete types.
  • Implement the interface in the actual classes you want to plug in.

For example:

 class EmailService:
    def send(self, message):
        print("Sending email:", message)

class Notification:
    def __init__(self, service):
        self.service = service

    def alert(self, msg):
        self.service.send(msg)

Right now, Notification depends directly on EmailService . But if we want to switch to SMS or push notifications later, this won't work well.

Instead, define an interface:

 from abc import ABC, abstractmethod

class MessageService(ABC):
    @abstractmethod
    def send(self, message):
        pass

class EmailService(MessageService):
    def send(self, message):
        print("Sending email:", message)

class SMSService(MessageService):
    def send(self, message):
        print("Sending SMS:", message)

class Notification:
    def __init__(self, service: MessageService):
        self.service = service

    def alert(self, msg):
        self.service.send(msg)

Now, Notification doesn't care what kind of service it gets — as long as it implements MessageService .


Common Mistakes When Applying DIP

People often get tripped up when trying to follow DIP. Here are a few common pitfalls:

  • Creating unnecessary interfaces just to "follow the rules" — only abstract things that vary or need decoupling.
  • Forgetting to inject dependencies — even if you define an interface, if your class instantiates a concrete type internally, you're still tightly coupled.
  • Overusing dependency injection frameworks without understanding the underlying pattern — they help, but aren't magic.

Also, don't over-engineer. If something is unlikely to change, it may not be worth abstracting.


It's not complicated once you see the pattern, but it's easy to miss small coupling points that defeat the purpose. Keep your interfaces focused, inject dependencies properly, and you'll find your codebase becomes more adaptable.

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