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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

Profiling basics

Profiling is a dynamic analysis that instruments code to understand how it runs. This information is extracted and compiled in a way that can be used to get a better knowledge of a particular behavior based on a real case, as the code is running as usual. This information can be used to improve the code.

Certain static analysis tools, as opposed to dynamic, can provide insight into aspects of the code. For example, they can be used to detect if certain code is dead code, meaning it's not called anywhere in the whole code. Or, they can detect some bugs, like the usage of variables that haven't been defined before, like when having a typo. But they don't work with the specifics of code that's actually being run. Profiling will bring specific data based on the use case instrumented and will return much more information on the flow of the code.

The normal application of profiling is to improve the performance of the code under analysis...

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