Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Expert Python Programming – Fourth Edition

You're reading from   Expert Python Programming – Fourth Edition Master Python by learning the best coding practices and advanced programming concepts

Arrow left icon
Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781801071109
Length 630 pages
Edition 4th Edition
Languages
Arrow right icon
Authors (3):
Arrow left icon
Michał Jaworski Michał Jaworski
Author Profile Icon Michał Jaworski
Michał Jaworski
Tarek Ziade Tarek Ziade
Author Profile Icon Tarek Ziade
Tarek Ziade
Tarek Ziadé Tarek Ziadé
Author Profile Icon Tarek Ziadé
Tarek Ziadé
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Current Status of Python 2. Modern Python Development Environments 3. New Things in Python 4. Python in Comparison with Other Languages 5. Interfaces, Patterns, and Modularity FREE CHAPTER 6. Concurrency 7. Event-Driven Programming 8. Elements of Metaprogramming 9. Bridging Python with C and C++ 10. Testing and Quality Automation 11. Packaging and Distributing Python Code 12. Observing Application Behavior and Performance 13. Code Optimization 14. Other Books You May Enjoy
15. Index

Quality automation

There is no arbitrary scale that can say definitely if some code's quality is bad or good. Unfortunately, the abstract concept of code quality cannot be measured and expressed in the form of numbers. Instead, we can measure various metrics of the software that are known to be highly correlated with the quality of code. The following are a few:

  • The percentage of code covered by tests
  • The number of code style violations
  • The amount of documentation
  • Complexity metrics, such as McCabe's cyclomatic complexity
  • The number of static code analysis warnings

Many projects use code quality testing in their continuous integration workflows. A good and popular approach is to test at least the basic metrics (test coverage, static code analysis, and code style violations) and not allow the merging of any code to the main branch that scores poorly on these metrics.

In the following sections, we will discuss some interesting...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime