Implementing the Clean Architecture
Implementing the Clean Architecture
Python Edition
About the Book
Neither database nor framework should shape your application. Business needs should. Unfortunately, it might have got out of sight due to years spent on writing Django- or Rails-like web applications with Active Record ORMs.
The Clean Architecture is an approach that puts your customer’s concerns in the centre of software. All other issues, such as persistence are treated as implementation details. This is achieved thanks to a careful layering of the project.
As a result, business rules are decoupled from frameworks and 3rd party services. Therefore you can rapidly prototype and test core value. Everything has its place, which makes i.e. onboarding new team members a breeze. Last, but certainly not least – as time passes and project grows the Clean Architecture lets you maintain order and remain flexible.
About the Author
Table of Contents
-
Foreword
- Why I wrote this book?
- Tools-driven era
- Who is this book for?
- What will you find in this book?
-
1. The Clean Architecture
- 1.1 What is it all for?
-
1.2 Code layers - horizontal slicing
- 1.2.1 External world
- 1.2.2 Infrastructure
- 1.2.3 Application
- 1.2.4 Domain
- 1.2.5 The Dependency Rule
- 1.2.6 Boundaries
- 1.3 Chapter summary
-
2. Referential implementation
- 2.1 Control flow in the Clean Architecture
- 2.2 Business requirements
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2.3 Implementation
- 2.3.1 Sequence diagram
- 2.3.2 Input Boundary
- 2.3.3 Output Boundary
- 2.3.4 Presenter
- 2.3.5 View model
- 2.3.6 Use Case
- 2.3.7 Data Access Interface
- 2.3.8 Data Access
- 2.3.9 Entities - Bid
- 2.3.10 Entities - Auction
- 2.4 Chapter summary
-
3. The Clean Architecture modifications
- 3.1 Presenter dillema
- 3.2 Getting rid of Input Boundary
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3.3 Alternative design of Use Cases
- 3.3.1 Application Facade
- 3.3.2 Mediator (Command Bus)
- 3.4 Resigning from Entities in favour of ORM models
- 3.5 Chapter summary
-
4. Dependency Injection
- 4.1 Abstractions & classes everywhere!
- 4.2 Abstractions in the Clean Architecture
- 4.3 Inversion of Control
- 4.4 IoC Container versus Service Locator
- 4.5 Dependency Injection versus configuration
- 4.6 Chapter summary
-
5. CQRS
- 5.1 Introduction
- 5.2 What does it have to do with the Clean Architecture?
- 5.3 Separate read stack - why?
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5.4 Separate read stack - how?
- 5.4.1 Query as DTO
- 5.4.2 Query as separate classes
- 5.4.3 Read model facade
- 5.5 CQRS vs REST API
- 5.6 CQRS vs GraphQL
- 5.7 Chapter summary
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6. Sharp boundary
- 6.1 A word on complexity
- 6.2 Two worlds
- 6.3 Boundary between Application and External World
- 6.4 Writing Input DTOs
- 6.5 Value Objects
- 6.6 Chapter summary
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7. End-to-end example
- 7.1 Where to start?
- 7.2 Walking skeleton
- 7.3 Placing Bid Use Case / Interactor
- 7.4 Auction and Bid Entities
- 7.5 Data Access Intreface (Abstract Repository)
- 7.6 Data Access (Repository)
- 7.7 Finishing PlacingBid Use Case
- 7.8 Packaging code
- 7.9 Implementing EndingAuction Use Case
- 7.10 Read-only operations
- 7.11 Inverting control with Events
- 7.12 Dealing with other cross-cutting concerns
- 7.13 Chapter summary
-
8. Modularity
- 8.1 The burden of success - growth & continuous changes
- 8.2 Cohesion and modules
- 8.3 Packaging code by feature
- 8.4 Modules and flexibility of interior design
- 8.5 Modules versus microservices
- 8.6 Modules versus user
- 8.7 Modules vs Bounded Contexts
- 8.8 Modules implementation
- 8.9 Modules depending on each other
- 8.10 Case study - auctioning platform
- 8.11 Chapter summary
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9. Testing
- 9.1 Testing strategy and feature flavours
- 9.2 Rediscovering unit-testing
- 9.3 Unit-testing of an entire module
- 9.4 Chapter summary
- Final words
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Appendix A: Migrating from legacy
- Should I even migrate?
- How to do it?
- I cannot stop delivering new features
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Appendix B: Introduction to Event Sourcing
- What is Event Sourcing?
- Simple example of an Event Sourcing Aggregate
- Persistence in Event Sourcing
- Projections
- Event Sourcing in the landscape of a modular application
- Bibliography
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