Debugging in Python

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Introduction to Python Python is a widely used language in machine learning and web development, and debugging is a crucial aspect of coding.

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1. Good Coding Practices Using good coding practices is crucial for efficient debugging. Commenting, descriptive variable names, and clean, organized code all help prevent errors.

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2. Proactive Approach Prevent bugs before they occur by using automated testing, validation tools, and writing unit tests. This will help you catch errors early in development.

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3. Keep Up to Date Stay up-to-date with the latest Python debugging tools & methods. Explore advanced techniques like profiling & debugging multi-threaded apps & use third-party tools like PyCharm & VS Code.

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4. Profiling Profiling helps identify potential bottlenecks in code and makes it more efficient. cProfile and pycharm’s profiler are two Python tools that can be used for profiling.

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5. Unit Testing It checks each part of your code to ensure it works as intended & catches errors early in development process. Unittest & pytest are libraries for unit testing in Python.

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6. General Principles Debugging is both an art and a science. Starting with the simplest solution & breaking the issue down into smaller pieces are two best practices for efficient debugging.

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7. Methodical Approach Work methodically when debugging by checking inputs and outputs, then logic, and finally syntax. A systematic approach will help you identify issues more effectively.

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8. Team Sport Debugging is a team sport. Communicate with coworkers about the problem, steps taken, and assumptions made. Fresh eyes often see a problem in a new light.

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Ready to become an expert in Python?

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