Book Image

Hands-On Reactive Programming with Python

By : Romain Picard
Book Image

Hands-On Reactive Programming with Python

By: Romain Picard

Overview of this book

Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices.

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Table of Contents (16 chapters)
Preface
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Free Chapter
1
An Introduction to Reactive Programming
An Introduction to Reactive Programming
What is reactive programming?
Introduction to ReactiveX and RxPY
A reactive echo application
Marble diagrams
Flow diagrams
Summary
Questions
Further reading
2
Asynchronous Programming in Python
Asynchronous Programming in Python
What is asynchronous programming?
The history of asynchronous programming in Python
Introduction to AsyncIO
An HTTP echo server
Summary
Questions
Further reading
3
Functional Programming with ReactiveX
Functional Programming with ReactiveX
What is functional programming?
Observable cycles
Structuring functional and reactive code
The HTTP echo server with an HTTP driver
Summary
Questions
Further reading
4
Exploring Observables and Observers
Exploring Observables and Observers
Creating observables
Hot and cold observables
Subscription and disposal
Error handling
Observables and AsyncIO
Summary
Questions
5
Concurrency and Parallelism in RxPY
Concurrency and Parallelism in RxPY
Concurrency and schedulers
Available schedulers
Summary
Questions
6
Implementation of an Audio Transcoding Server
Implementation of an Audio Transcoding Server
Technical requirements
Structuring the project
Introduction to Cyclotron
Operators used in this application
Implementation of the encoding server
Summary
Questions
Further reading
7
Using Third-Party Services
Using Third-Party Services
Technical requirements
An introduction to S3 storage
Installing Docker and Minio
Using S3 as storage
Dealing with blocking API and CPU-bound operations
Summary
Questions
Further reading
8
Dynamic Reconfiguration and Error Management
Dynamic Reconfiguration and Error Management
Monitoring file changes
Operators used for dynamic configuration
Encode driver reconfiguration
Error management
Summary
Questions
9
Operators in RxPY
Operators in RxPY
Transforming observables
Filtering observables
Combining observables
Utility operators
Conditional operators
Mathematical operators
Summary
Questions
Further reading
10
Testing and Debugging
Testing and Debugging
Testing
Logging
Debugging
Summary
Questions
Further reading
11
Deploying and Scaling Your Application
Deploying and Scaling Your Application
Technical requirements
Introduction to Traefik
Packaging a service with Docker Compose
Adding TLS support with Let's Encrypt
Summary
Questions
Further reading
12
Reactive Streams for Remote Communication
Reactive Streams for Remote Communication
Communication patterns and observables
Observable multiplexing
Implementing publish/subscribe
Summary
Questions
Further reading
13
A Checklist of Best Practices
A Checklist of Best Practices
The observable creation decision tree
Keeping side-effects as small as possible
What to do when nothing happens
Miscellaneous recommendations
Summary
Questions
Further reading
14
Assessments
Assessments
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Chapter 11
Chapter 12
Chapter 13
15
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Concurrency and schedulers

Chapter 2, Asynchronous Programming in Python, explained the principles of concurrency, and its two categories:

  • I/O concurrency
  • CPU concurrency

An asynchronous framework is designed to deal with I/O concurrency by multiplexing all I/O requests on a single process and thread. The AsyncIO framework and ReactiveX are both tools in this category. As such, they are a perfect fit for applications that are I/O bound, such as network-based applications and tasks involving interactions with databases. However, there are situations where a full asynchronous design cannot be applied. This can occur in two cases:

  • When doing CPU-intensive actions
  • When using blocking APIs

Both of them break the behavior of an asynchronous system because they block the event loop for a very long time, and prevent other tasks from executing. On some asynchronous frameworks, handling...

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