What are some common debugging tools and techniques for Python?

1 Built-in tools

Python has some built-in tools that can help you debug your code. For example, you can use the print() function to display the values of variables, expressions, or messages in the console. You can also use the assert() statement to check if a condition is true, and raise an exception if it is not. Another useful tool is the traceback module, which can show you the stack trace of an error, indicating where and why it occurred.

2 Debugging modes

Python also has two debugging modes that can change the way your code runs: interactive mode and debug mode. In interactive mode, you can run your code line by line in the Python shell, and inspect or modify the variables and objects in the current scope. You can enter interactive mode by typing python or python3 in your terminal, or by using the -i option when running a script. In debug mode, you can use the pdb module to set breakpoints, step through your code, and evaluate expressions. You can enter debug mode by using the -m pdb option when running a script, or by inserting the

import pdb; pdb.set_trace()        

statement in your code.

3 IDEs and editors

Another way to debug your Python code is to use an integrated development environment (IDE) or a code editor that supports debugging features. For example, you can use PyCharm, Visual Studio Code, or Spyder, which are popular IDEs for Python development. These IDEs can provide you with graphical interfaces to set breakpoints, watch variables, inspect objects, and control the execution flow. They can also integrate with other tools and frameworks, such as pytest, Django, or Flask, to help you debug your code in different contexts.

4 Logging and testing

Debugging is not only about finding errors, but also about preventing them. One way to do that is to use logging and testing tools to monitor and verify your code. Logging is the process of recording events and messages that occur during the execution of your code. You can use the logging module to create and configure loggers, handlers, formatters, and levels, and to output log messages to different destinations, such as files, consoles, or databases. Testing is the process of checking if your code meets the expected requirements and specifications. You can use the unittest or pytest modules to create and run test cases, suites, and fixtures, and to report the results and failures.

5 Debugging tips

Finally, here are some general tips that can help you debug your code more efficiently. It's important to use descriptive and consistent names for variables, functions, and classes, following the Python style guide (PEP 8) to make code more readable and maintainable. Comments and docstrings should be used to document the code and explain its purpose and logic. Version control systems, such as Git or Mercurial, can track the changes and history of the code and enable reverting or comparing different versions if needed. Additionally, online resources like Stack Overflow, Python documentation, or tutorials can be used to search for solutions or examples of similar problems or tasks. The rubber duck method can also be helpful; this involves explaining your code or problem out loud to a rubber duck (or any other object or person), which can clarify your thoughts and identify possible mistakes or gaps.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?