Global Certificate in Python Testing: Debugging and Troubleshooting Techniques

This course is designed for software developers, quality assurance engineers, and Python enthusiasts looking to enhance their skills in debugging and troubleshooting. Participants will gain proficiency in using Python's built-in tools and third-party libraries to identify and resolve issues efficiently, ensuring reliable and robust software development.

By the end of the course, attendees will master essential debugging techniques, including setting breakpoints, inspecting variables, and understanding exception handling. They will also learn how to write effective test cases and use automation tools to streamline the debugging process, reducing development time and improving code quality.

1. 1. Introduction to Python Testing: Learners will be introduced to the importance of testing in Python development and cover foundational concepts such as unit testing, integration testing, and test automation. By the end, they will have practical skills in setting up testing environments and understanding basic testing frameworks.
2. 2. Debugging Fundamentals: This module covers essential debugging techniques and tools in Python, including using print statements, debugging with IDEs, and understanding stack traces. Learners will gain the ability to effectively identify and fix errors in their code.
3. 3. Exception Handling: Learners will delve into Python’s exception handling mechanisms, including try-except blocks and custom exceptions. Practical skills include writing robust code that can handle errors gracefully and recover from unexpected conditions.
4. 4. Automated Testing with PyTest: This module focuses on using PyTest for automated testing. Learners will gain skills in writing tests, organizing test files, and running tests with PyTest. They will also learn about fixtures, markers, and plugins to enhance their testing strategies.
5. 5. Debugging Complex Systems: Building on foundational skills, this module explores debugging techniques for complex systems, including multithreaded and distributed applications. Learners will understand how to trace issues across multiple components and use logging effectively.
6. 6. Performance Testing with Python: This module introduces learners to performance testing in Python, including profiling and benchmarking. They will learn to identify bottlenecks, optimize code, and ensure applications perform efficiently under load.
7. 7. Troubleshooting Common Issues: Learners will tackle common issues faced in Python development, such as memory leaks, race conditions, and performance bottlenecks. They will gain practical skills to diagnose and resolve these issues systematically.
8. 8. Debugging in CI/CD Pipelines: This module covers debugging techniques in continuous integration and continuous deployment (CI/CD) pipelines. Learners will understand how to integrate debugging tools into CI/CD processes and handle issues that arise during automated builds and deployments.
9. 9. Advanced Debugging Tools and Techniques: Building on earlier modules, this advanced module explores cutting-edge debugging tools and techniques in Python. Topics include using Python’s built-in debugger (pdb), static code analysis, and debugging with virtual machines.
10. 10. Best Practices in Python Testing: In this final module, learners will learn best practices for maintaining high-quality testing processes in Python. Topics include test maintenance, regression testing, and ensuring tests remain up-to-date with code changes.