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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

Memory profiling

Sometimes, applications use too much memory. The worst-case scenario is that they use more and more memory as time goes by, normally due to what's called a memory leak, maintaining memory that is no longer used, due to some mistake in the coding. Other problems can also include the fact that the usage of memory may be improved, as it's a limited resource.

To profile memory and analyze what the objects are that use the memory, we need first to create some example code. We will generate enough Leonardo numbers.

Leonardo numbers are numbers that follow a sequence defined as the following:

  • The first Leonardo number is one
  • The second Leonardo number is also one
  • Any other Leonardo number is the two previous Leonardo numbers plus one

Leonardo numbers are similar to Fibonacci numbers. They are actually related to them. We use them instead of Fibonacci to show more variety. Numbers are fun!

We present the first 35 Leonardo...

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