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Software Architecture with Python

You're reading from   Software Architecture with Python Design and architect highly scalable, robust, clean, and high performance applications in Python

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781786468529
Length 556 pages
Edition 1st Edition
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Author (1):
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 Balachandran Pillai Balachandran Pillai
Author Profile Icon Balachandran Pillai
Balachandran Pillai
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Table of Contents (18) Chapters Close

Software Architecture with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Principles of Software Architecture FREE CHAPTER 2. Writing Modifiable and Readable Code 3. Testability – Writing Testable Code 4. Good Performance is Rewarding! 5. Writing Applications That Scale 6. Security – Writing Secure Code 7. Design Patterns in Python 8. Python – Architectural Patterns 9. Deploying Python Applications 10. Techniques for Debugging Index

Metrics – tools for static analysis


Static code analysis tools can provide a rich summary of information on the static properties of your code, which can provide insights into aspects like complexity and modifiability/readability of the code.

Python has a lot of third-party tool support, which helps in measuring the static aspects of Python code such as these:

  • Conformance to coding standards like PEP-8

  • Code complexity metrics like the McCabe metric

  • Errors in code such as syntax errors, indentation issues, missing imports, variable overwrites, and others

  • Logic issues in code

  • Code smells

The following are some of the most popular tools in the Python ecosystem which can perform such static analysis:

  • Pylint: Pylint is a static checker for Python code, which can detect a range of coding errors, code smells, and style errors. Pylint uses a style close to PEP-8. The newer versions of Pylint also provide statistics about code complexity, and can print reports. Pylint requires the code to be executed before...

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