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Expert Python Programming

You're reading from   Expert Python Programming Write professional, efficient and maintainable code in Python

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Product type Paperback
Published in May 2016
Publisher Packt
ISBN-13 9781785886850
Length 536 pages
Edition 2nd Edition
Languages
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Author (1):
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Michał Jaworski Michał Jaworski
Author Profile Icon Michał Jaworski
Michał Jaworski
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Toc

Table of Contents (16) Chapters Close

Preface 1. Current Status of Python FREE CHAPTER 2. Syntax Best Practices – below the Class Level 3. Syntax Best Practices – above the Class Level 4. Choosing Good Names 5. Writing a Package 6. Deploying Code 7. Python Extensions in Other Languages 8. Managing Code 9. Documenting Your Project 10. Test-Driven Development 11. Optimization – General Principles and Profiling Techniques 12. Optimization – Some Powerful Techniques 13. Concurrency 14. Useful Design Patterns Index

Finding bottlenecks

Finding bottlenecks is done by:

  • Profiling CPU usage
  • Profiling memory usage
  • Profiling network usage

Profiling CPU usage

The first source of bottlenecks is your code. The standard library provides all the tools needed to perform code profiling. They are based on a deterministic approach.

A deterministic profiler measures the time spent in each function by adding a timer at the lowest level. This introduces a bit of overhead but provides a good idea on where the time is consumed. A statistical profiler, on the other hand, samples the instruction pointer usage and does not instrument the code. The latter is less accurate but allows running the target program at full speed.

There are two ways to profile the code:

  • Macro-profiling: This profiles the whole program while it is being used and generates statistics
  • Micro-profiling: This measures a precise part of the program by instrumenting it manually

Macro-profiling

Macro-profiling is done by running the application in a special mode where...

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