Postgraduate Certificate in Python Classes: Unit Testing and Debugging

This course is designed for postgraduate students and professionals aiming to enhance their Python programming skills, particularly in unit testing and debugging. You will gain proficiency in writing effective unit tests using frameworks like PyTest and unittest, and learn advanced debugging techniques to identify and resolve complex issues in Python code.

By the end of this course, you will be able to apply these skills to improve the reliability and maintainability of your Python applications, ensuring they meet high standards of quality and functionality.

1. 1. Introduction to Unit Testing: Learners will understand the importance of unit testing in software development, covering foundational concepts such as test cases, test suites, and test frameworks. They will gain practical skills in setting up testing environments and writing basic test cases using Python's unittest framework.
2. 2. Advanced Unit Testing Techniques: This module delves into more sophisticated testing techniques including parameterized tests, test case setup and teardown, and test isolation. Learners will learn to write efficient and maintainable test cases, enhancing their ability to debug and improve code quality.
3. 3. Debugging Fundamentals: Covering essential debugging tools and techniques, learners will study how to effectively use breakpoints, inspect variables, and step through code to identify and fix bugs. This module equips learners with the skills to systematically debug complex issues.
4. 4. Debugging Strategies and Best Practices: Learners will explore advanced debugging strategies, including logging, exception handling, and using external debuggers. They will learn best practices for writing robust and maintainable code, reducing the likelihood of bugs and improving overall software reliability.
5. 5. Python Debugging Tools and Environments: This module focuses on utilizing Python-specific debugging tools such as pdb, PyCharm, and Visual Studio Code. Learners will practice debugging real-world Python applications, gaining hands-on experience with multiple debugging environments.
6. 6. Testing Web Applications: Learners will learn to apply unit testing and debugging techniques to web applications, covering testing frameworks like Flask and Django. They will gain skills in testing web services, APIs, and ensuring web applications are secure and reliable.
7. 7. Automated Testing and Continuous Integration: This module introduces learners to automated testing and continuous integration (CI) practices, using tools like Jenkins and Travis CI. Learners will learn how to set up and maintain CI pipelines, ensuring that code changes are automatically tested and integrated into the main codebase.
8. 8. Performance Testing and Optimization: Focusing on performance testing, learners will learn how to identify and optimize bottlenecks in Python applications. They will gain skills in using profiling tools, analyzing performance metrics, and implementing optimization strategies to improve application speed and efficiency.
9. 9. Unit Testing for Data-Driven Applications: This module covers testing data-driven applications, including how to test databases, APIs, and data models. Learners will learn to write tests that validate data integrity and ensure that data-driven functionalities work as expected.
10. 10. Final Project: Comprehensive Testing and Debugging: In this capstone module, learners will apply all the skills and knowledge gained throughout the programme by working on a comprehensive project. They will develop a large-scale Python application, implement a robust testing strategy, and debug complex issues, demonstrating their ability to apply unit testing and debugging best practices in a real-world context.