1. Introduction: Why Do We Need Best Practices? -- 2. Exceptions in Python -- 3. Semantic Errors in Python -- 4. Debugging with the Scientific Method -- 5. Debugging with print Statements -- 6. Debugging with Introspection Functions -- 7. Using an Interactive Debugger -- 8. Writing Automated Tests -- 9. Organizing Test Data -- 10. Writing a Test Suite -- 11. Testing Best Practices -- 12. Version Control -- 13. Setting Up a Python Project -- 14. Cleaning Up Code -- 15. Decomposing Programming Tasks -- 16. Static Typing in Python -- 17. Documentation. div></div></div></div>.

Learn software engineering and coding best practices to write Python code right and error free. In this book you’ll see how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding. Software engineering is difficult. Programs of any substantial length are inherently prone to errors of all kinds. The development cycle is full of traps unknown to the apprentice developer. Yet, in Python textbooks little attention is paid to this aspect of getting your code to run. At most, there is a chapter on debugging or unit testing in your average basic Python book. However, the proportion of time spent on getting your code to run is much higher in the real world. Pro Python Best Practices aims to solve this problem. You will: Learn common debugging techniques that help you find and eliminate errors Gain techniques to detect bugs more easily ver best="" practices="" to="" prevent="" bugscarry="" out="" automated="" testing="" discover="" problems="" faster Use best practices to maintain a project over a long time Learn techniques to keep your project under control.

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