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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

Optimization strategy

Let's say your program has a real speed problem you need to resolve. Do not try to guess how to make it faster. Bottlenecks are often hard to find by looking at the code, and a set of tools is needed to find the real problem.

A good optimization strategy can start with three steps:

  • Find another culprit: Make sure a third-party server or resource is not faulty
  • Scale the hardware: Make sure the resources are sufficient
  • Write a speed test: Create a scenario with speed objectives

Find another culprit

Often, a performance problem occurs at production level and the customer alerts you that it is not working as it used to when the software was being tested. Performance problems might occur because the application was not planned to work in the real world with a high number of users and an increase of data size.

But if the application interacts with other applications, the first thing to do is to check if the bottlenecks are located on those interactions. For instance, a database...

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