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Python Architecture Patterns

You're reading from   Python Architecture Patterns Master API design, event-driven structures, and package management in Python

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801819992
Length 594 pages
Edition 1st Edition
Languages
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Author (1):
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Jaime Buelta Jaime Buelta
Author Profile Icon Jaime Buelta
Jaime Buelta
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Toc

Table of Contents (23) Chapters Close

Preface 1. Introduction to Software Architecture 2. Part I: Design FREE CHAPTER
3. API Design 4. Data Modeling 5. The Data Layer 6. Part II: Architectural Patterns
7. The Twelve-Factor App Methodology 8. Web Server Structures 9. Event-Driven Structures 10. Advanced Event-Driven Structures 11. Microservices vs Monolith 12. Part III: Implementation
13. Testing and TDD 14. Package Management 15. Part IV: Ongoing operations
16. Logging 17. Metrics 18. Profiling 19. Debugging 20. Ongoing Architecture 21. Other Books You May Enjoy
22. Index

Celery

Celery is the most popular task queue created in Python. It allows us to create new tasks easily and can handle the creation of the events that trigger new tasks.

Celery requires to work to set up a broker, which will be used as a queue to handle the messages.

In Celery parlance, the broker is the message queue, while the backend is reserved for interacting with a storage system to return information.

The code that creates the message will add it to the broker, and the broker will pass it to one of the connected workers. When everything happens with Python code, where the celery package can be installed, it's simple to operate. We'll see later how to operate it in other cases.

Celery can use multiple systems as brokers. The most popular are Redis and RabbitMQ.

In our examples, we will use Redis as it can be used for the broker and the backend, and it's widely available in cloud systems. It's also quite scalable and...

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