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Architecture Patterns with Python

Paperback Engels 2020 9781492052203
Verkooppositie 4524
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Samenvatting

As Python continues to grow in popularity, projects are becoming larger and more complex. Many Python developers are taking an interest in high-level software design patterns such as hexagonal/clean architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn’t always straightforward.

With this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity—and get the most value out of their test suites.

Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax.

Patterns include:
- Dependency inversion and its links to ports and adapters (hexagonal/clean architecture)
- Domain-driven design’s distinction between Entities, Value Objects, and Aggregates
- Repository and Unit of Work patterns for persistent storage
- Events, commands, and the message bus
- Command-query responsibility segregation (CQRS)
- Event-driven architecture and reactive microservices

Specificaties

ISBN13:9781492052203
Taal:Engels
Bindwijze:paperback
Aantal pagina's:280
Uitgever:O'Reilly
Druk:1
Verschijningsdatum:20-3-2020
Hoofdrubriek:IT-management / ICT

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Over Harry Percival

After an idyllic childhood spent playing with BASIC on French 8-bitcomputers like the Thomson T-07 whose keys go "boop" when you press them, Harry went on to study Economics and Philosophy at Cambridge University. He then spent a few years being deeply unhappy as a management consultant. Soon he rediscovered his true geek nature, and was lucky enough to fall in with a bunch of XP fanatics, working on the pioneering but sadly defunct Resolver One spreadsheet. He now works at PythonAnywhere LLP, and spreads the gospel of TDD world-wide at talks, workshops and conferences, with all the passion and enthusiasm of a recent convert.

Andere boeken door Harry Percival

Over Bob Gregory

Bob Gregory is a UK-based software architect with MADE.COM. He has been building event driven systems with domain-driven design for more than a decade.

Andere boeken door Bob Gregory

Inhoudsopgave

Preface
Managing Complexity, Solving Business Problems
Why Python?
TDD, DDD, and Event-Driven Architecture
Who Should Read This Book
A Brief Overview of What You’ll Learn
Part I, Building an Architecture to Support Domain Modeling
Part II, Event-Driven Architecture
Addtional Content
Example Code and Coding Along
License
Conventions Used in This Book
O’Reilly Online Learning
How to Contact O’Reilly
Acknowledgments
Introduction
Why Do Our Designs Go Wrong?
Encapsulation and Abstractions
Layering
The Dependency Inversion Principle
A Place for All Our Business Logic: The Domain Model

I. Building an Architecture to Support Domain Modeling
1. Domain Modeling
What Is a Domain Model?
Exploring the Domain Language
Unit Testing Domain Models
Dataclasses Are Great for Value Objects
Value Objects and Entities
Not Everything Has to Be an Object: A Domain Service Function
Python’s Magic Methods Let Us Use Our Models with Idiomatic Python
Exceptions Can Express Domain Concepts Too

2. Repository Pattern
Persisting Our Domain Model
Some Pseudocode: What Are We Going to Need?
Applying the DIP to Data Access
Reminder: Our Model
The “Normal” ORM Way: Model Depends on ORM
Inverting the Dependency: ORM Depends on Model
Introducing the Repository Pattern
The Repository in the Abstract
What Is the Trade-Off?
Building a Fake Repository for Tests Is Now Trivial!
What Is a Port and What Is an Adapter, in Python?
Wrap-Up

3. A Brief Interlude: On Coupling and Abstractions
Abstracting State Aids Testability
Choosing the Right Abstraction(s)
Implementing Our Chosen Abstractions
Testing Edge to Edge with Fakes and Dependency Injection
Why Not Just Patch It Out?
Wrap-Up

4. Our First Use Case: Flask API and Service Layer
Connecting Our Application to the Real World
A First End-to-End Test
The Straightforward Implementation
Error Conditions That Require Database Checks
Introducing a Service Layer, and Using FakeRepository to Unit Test It
A Typical Service Function
Why Is Everything Called a Service?
Putting Things in Folders to See Where It All Belongs
Wrap-Up
The DIP in Action

5. TDD in High Gear and Low Gear
How Is Our Test Pyramid Looking?
Should Domain Layer Tests Move to the Service Layer?
On Deciding What Kind of Tests to Write
High and Low Gear
Fully Decoupling the Service-Layer Tests from the Domain
Mitigation: Keep All Domain Dependencies in Fixture Functions
Adding a Missing Service
Carrying the Improvement Through to the E2E Tests
Wrap-Up

6. Unit of Work Pattern
The Unit of Work Collaborates with the Repository
Test-Driving a UoW with Integration Tests
Unit of Work and Its Context Manager
The Real Unit of Work Uses SQLAlchemy Sessions
Fake Unit of Work for Testing
Using the UoW in the Service Layer
Explicit Tests for Commit/Rollback Behavior
Explicit Versus Implicit Commits
Examples: Using UoW to Group Multiple Operations into an Atomic Unit
Example 1: Reallocate
Example 2: Change Batch Quantity
Tidying Up the Integration Tests
Wrap-Up

7. Aggregates and Consistency Boundaries
Why Not Just Run Everything in a Spreadsheet?
Invariants, Constraints, and Consistency
Invariants, Concurrency, and Locks
What Is an Aggregate?
Choosing an Aggregate
One Aggregate = One Repository
What About Performance?
Optimistic Concurrency with Version Numbers
Implementation Options for Version Numbers
Testing for Our Data Integrity Rules
Enforcing Concurrency Rules by Using Database Transaction Isolation Levels
Pessimistic Concurrency Control Example: SELECT FOR UPDATE
Wrap-Up
Part I Recap

II. Event-Driven Architecture
8. Events and the Message Bus
Avoiding Making a Mess
First, Let’s Avoid Making a Mess of Our Web Controllers
And Let’s Not Make a Mess of Our Model Either
Or the Service Layer!
Single Responsibility Principle
All Aboard the Message Bus!
The Model Records Events
Events Are Simple Dataclasses
The Model Raises Events
The Message Bus Maps Events to Handlers
Option 1: The Service Layer Takes Events from the Model and Puts Them on the Message Bus
Option 2: The Service Layer Raises Its Own Events
Option 3: The UoW Publishes Events to the Message Bus
Wrap-Up

9. Going to Town on the Message Bus
A New Requirement Leads Us to a New Architecture
Imagining an Architecture Change: Everything Will Be an Event Handler
Refactoring Service Functions to Message Handlers
The Message Bus Now Collects Events from the UoW
Our Tests Are All Written in Terms of Events Too
A Temporary Ugly Hack: The Message Bus Has to Return Results
Modifying Our API to Work with Events
Implementing Our New Requirement
Our New Event
Test-Driving a New Handler
Implementation
A New Method on the Domain Model
Optionally: Unit Testing Event Handlers in Isolation with a Fake Message Bus
Wrap-Up
What Have We Achieved?
Why Have We Achieved?

10. Commands and Command Handler
Commands and Events
Differences in Exception Handling
Discussion: Events, Commands, and Error Handling
Recovering from Errors Synchronously
Wrap-Up

11. Event-Driven Architecture: Using Events to Integrate Microservices
Distributed Ball of Mud, and Thinking in Nouns
Error Handling in Distributed Systems
The Alternative: Temporal Decoupling Using Asynchronous Messaging
Using a Redis Pub/Sub Channel for Integration
Test-Driving It All Using an End-to-End Test
Redis Is Another Thin Adapter Around Our Message Bus
Our New Outgoing Event
Internal Versus External Events
Wrap-Up

12. Command-Query Responsibility Segregation (CQRS)
Domain Models Are for Writing
Most Users Aren’t Going to Buy Your Furniture
Post/Redirect/Get and CQS
Hold On to Your Lunch, Folks
Testing CQRS Views
“Obvious” Alternative 1: Using the Existing Repository
Your Domain Model Is Not Optimized for Read Operations
“Obvious” Alternative 2: Using the ORM
SELECT N+1 and Other Performance Considerations
Time to Completely Jump the Shark
Updating a Read Model Table Using an Event Handler
Changing Our Read Model Implementation Is Easy
Wrap-Up

13. Dependency Injection (and Bootstrapping)
Implicit Versus Explicit Dependencies
Aren’t Explicit Dependencies Totally Weird and Java-y?
Preparing Handlers: Manual DI with Closures and Partials
An Alternative Using Classes
A Bootstrap Script
Message Bus Is Given Handlers at Runtime
Using Bootstrap in Our Entrypoints
Initializing DI in Our Tests
Building an Adapter “Properly”: A Worked Example
Define the Abstract and Concrete Implementations
Make a Fake Version for Your Tests
Figure Out How to Integration Test the Real Thing
Wrap-Up
Epilogue
What Now?
How Do I Get There from Here?
Separating Entangled Responsibilities
Identifying Aggregates and Bounded Contexts
An Event-Driven Approach to Go to Microservices via Strangler Pattern
Convincing Your Stakeholders to Try Something New
Questions Our Tech Reviewers Asked That We Couldn’t Work into Prose
Footguns
More Required Reading
Wrap-Up

A. Summary Diagram and Table

B. A Template Project Structure
Env Vars, 12-Factor, and Config, Inside and Outside Containers
Config.py
Docker-Compose and Containers Config
Installing Your Source as a Package
Dockerfile
Tests
Wrap-Up

C. Swapping Out the Infrastructure: Do Everything with CSVs
Implementing a Repository and Unit of Work for CSVs

D. Repository and Unit of Work Patterns with Django
Repository Pattern with Django
Custom Methods on Django ORM Classes to Translate to/from Our Domain Model
Unit of Work Pattern with Django
API: Django Views Are Adapters
Why Was This All So Hard?
What to Do If You Already Have Django
Steps Along the Way

E. Validation
What Is Validation, Anyway?
Validating Syntax
Postel’s Law and the Tolerant Reader Pattern
Validating at the Edge
Validating Semantics
Validating Pragmatics

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