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Why Vertical Slice Architecture Beats Onion Architecture

Why Vertical Slice Architecture Beats Onion Architecture

From outside the system, data goes in from the view, goes through the controllers and databases into the use cases and heads towards the center of the system, which is the entities. The intended layout of the packages in clean architecture is what Robert Martin calls ‘Screaming Architecture’. The idea here is that your package structure screams the intent of the app without looking at the individual classes or lines of code.

With this approach, most abstractions melt away and we don’t need any kind of “shared” layer abstractions like repositories, services, controllers. Sometimes these are still required by our tools (like controllers or ORM units-of-work) but we keep our cross-slice logic sharing to a minimum. The flow of control in the corner shows how each object within the system has 3 parts. It has the input port, the output port, and the interactor that converts the two. These parts can be interfaces or objects or properties, depending on the complexity, language, and level of abstraction, but all cross-boundary communication happens in these ports.

Inputs go INTO a region, and outputs come out of a region. It’s very easy and tempting to have the repository be an input to the generatePaySlip UseCase, and just grab the data directly. But instead, we make sure our Entity classes are the only source of data going INTO the UseCase, being their own output. However, in the third view, all the Entities are off to the side.

onion architecture example

In this layer, the service interface is separated from the implementation to achieve decoupling and focus separation. If you don’t have an enterprise, and are just writing a single application, then these entities are the business objects of the application. They encapsulate the most general and high-level rules. They are the least likely to change when something external changes. For example, you would not expect these objects to be affected by a change to page navigation, or security.

The idea is to first define an interface for the repository operations. The interface can be put together with the domain layer, while its implementation stays in the infrastructure. If you just work from the first two images, you will likely make the classes tightly coupled, and will often get confused on how to keep the layers separate. This is because there isn’t enough information in these two diagrams to properly understand the role and purpose of ports and adapters between the layers. The internal flow of data between business domains isn’t as clear as it could be.

Unit Of Work Pattern

The assumption is that you are familiar with Eric Evans’ book and Onion architecture, so I will not explain them. In the following, I will explain how you can implement each DDD component in the Python world. The variety of interfaces that make up DDD is not necessarily compatible with the dynamically typed language. However, it is achievable using the standard features provided by Python. For users familiar with MVC through prominent frameworks such as Django, this codebase may seem bizarre.

onion architecture example

At the lower right of the diagram is an example of how we cross the circle boundaries. It shows the Controllers and Presenters communicating with the Use Cases in the next layer. It begins in the controller, moves through the use case, and then winds up executing in the presenter.

We then need our router class, that will specify the HTTP endpoints that will call the controller methods created above. First, let’s define a controller class, that will have our use cases injected as dependencies and pass data received from the HTTP requests to them. The infrastructure layer is responsible for every communication with external systems such as the system state . The second image is how we organize our files and packages into business domains, so developers know exactly where to go when making a change.

When looking at the diagram as a traffic cone, then you have the tip which is the most pure and abstract, having zero dependencies and rarely changing. The wide, bottom layer is then the most concrete and most likely to change. Each layer of the cone has dependencies on the layer above it. If you are lazy here, the connection string will be written directly into the code.

What Is The Onion Architecture?

It can be said that onion architecture perfectly solves the difficulties and problems of three-tier or n-tier architecture. Onion architecture, sometimes called clean architecture, exists for high quality software. By the same token, data formats used in an outer circle should not be used by an inner circle, especially if those formats are generate by a framework in an outer circle. We don’t want anything in an outer circle to impact the inner circles.

onion architecture example

This ensures that the code in any particular layer knows nothing about code in the other layers. The inner core is called from the use cases, which are called from the controllers, presenters, or gateways, which are called from the public shell. The usual way is interface, which is used to describe the read and write operations involved in data access.

Interface Adapters

While the project used for this example is just an introduction point, you might feel comfortable enhancing it by introducing other concepts inside this architecture such as CQRS. Working with incomplete data often leads to an incomplete understanding. Whenever you talk to others about clean architecture, make sure you are able to provide all three images, to reduce confusion. If you wish to learn more about various architecture techniques and when to use them, join us or follow this blog.

  • In this article, we are going to learn about Onion architecture and what are its advantages.
  • An entity can be an object with methods, or it can be a set of data structures and functions.
  • If we need anything from an external system or service, we can just create an interface for it and consume it.
  • This rule says that source code dependencies can only point inwards.
  • It encapsulates and implements all of the use cases of the system.
  • The packages make no reference to the layer concepts; those only show up in the individual files.

He’s worked as a Software Architect at OnceHub since September 2019, where he focuses on Cloud Native Automated workflows and improving team practices. In his free time, he enjoys playing games, Dungeons & Dragons, Brazilian jujitsu, and historical European sword fighting. At OnceHub, we recently had a whirlwind tour of different architecture concepts and techniques. Scanning the two-dimensional code, paying attention to the official account, can get the latest personal articles and content push.

This is the true beauty of the Onion architecture. We moved all of the important business logic into the Service layer. There are more examples, but hopefully, you get the idea. We are hiding all the implementation details in the Infrastructure layer because it is at the top of the Onion architecture, while all of the lower layers depend on the interfaces . This layer is responsible only for operating the application.

The Clean Code Blog

While the internet might move from desktop to mobile, or from mobile to virtual assistant, the core business remains the same. The outer layers of the architecture implement these interfaces. This means that in the Domain layer, we are not concerning ourselves with infrastructure details such as the database or external services.

Dotnet Onion Architecture Practice

We have connected all of our Onion architecture implementation layers, and our application is now ready for use. We are using a Web API built with ASP.NET Core to create a set of RESTful API endpoints for modifying the domain entities and allowing consumers to get back the data. The flow of dependencies dictates what a certain layer in the Onion architecture can do. Because it depends on the layers below it in the hierarchy, it can only call the methods that are exposed by the lower layers.

This means that the code is violating the rule of having high cohesion. Swagger’s settings are not the focus of this article. This is my habit, and this project is a webapi, it’s convenient to install a swagger. The diagram at the top of this article is an attempt at integrating all these architectures into a single actionable idea.

What Is The Motivation For Splitting The Service Layer?

The architecture does not depend on the existence of some library of feature laden software. This allows you to use such frameworks as tools, rather than having to cram your system into their limited constraints. Notice that we create a switch expression around the exception instance and then perform a pattern matching based on the exception type.

We keep these things on the outside where they can do little harm. The concentric circles represent different areas of software. In general, the further in you go, the higher level the software becomes. In this short project, the missing piece is transaction management. For the gap, the Unit of Work pattern fits almost entirely.

This means that our service instances are only going to be created when we access them for the first time, and not before that. Contracts project to define the Data Transfer Objects that we are going to consume with the service interfaces. Presentation project will be the Presentation layer implementation.

Whats Wrong With Onion Architecture?

This is because we have a very high and a very low level of abstraction, without the complex glue to bring it all together. There is a third diagram which is needed to complete the picture, and this is the information/data flow diagram. In a word, onion architecture is an excellent architecture in terms of application. With my experience, I have a great advantage in many joint development projects.

The Domain layer does not have any direct dependencies on the outside layers. The outer layers are all allowed to reference the layers that are directly below them in the hierarchy. The Onion architecture is a form of layered architecture and we can visualize these layers as concentric circles.

It doesn’t know any other layer, therefore, has no dependencies, and is the easiest to test. We are building a simple shopping cart application, where there are products that can be added to a shopping cart. The cart may have some business rules, like the minimum/maximum quantity of a unique item.

No operational change to any particular application should affect the entity layer. The overriding rule that makes this architecture work is The Dependency Rule. This rule says that source code dependencies can only point inwards.

These architectures also tend to be mock-heavy, with rigid rules around dependency management. In practice, I’ve found these rules rarely useful, and you start to get onion structure many abstractions around concepts that really shouldn’t be abstracted . Later, we will use the data tables created by the customer and baseentity entity classes.

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