Debugging is an essential skill for any programmer, and it’s no different when working with Python. Even the most experienced developers encounter bugs in their code. The good news is that Python provides a range of tools and techniques to help you identify and fix issues efficiently. In this article, we’ll explore the art of debugging Python code and provide you with a toolkit to tackle bugs effectively.

1. Understand the Bug:

Before you start debugging, it’s crucial to understand the bug’s nature. What is the expected behavior, and what is the actual behavior? Try to reproduce the issue consistently so that you have a clear understanding of the problem.

2. Use Print Statements:

The simplest debugging technique is to insert print statements into your code to display variable values, function calls, and control flow. This allows you to track the program’s execution and identify the point at which something goes wrong.

def calculate_sum(a, b):
    result = a + b
    print("Debug: a =", a)
    print("Debug: b =", b)
    print("Debug: result =", result)
    return result

3. Leverage the Python Debugger (pdb):

Python comes with a built-in interactive debugger called pdb. You can insert breakpoints in your code and inspect variables, step through code, and more. To set a breakpoint, add:

import pdb; pdb.set_trace()

This will launch an interactive debugger session when your code reaches that point.

4. Use Exception Handling:

Wrap sections of your code in try-except blocks to catch and handle exceptions gracefully. This prevents your program from crashing and allows you to handle errors appropriately.

    # Code that might raise an exception
except Exception as e:
    # Handle the exception or print the error message

5. Logging:

Python’s logging module provides a powerful way to record information about your code’s execution. You can set different log levels and output log messages to files for more detailed debugging.

import logging

logging.basicConfig(filename='debug.log', level=logging.DEBUG)

6. Use IDEs and Editors with Debugging Support:

Integrated Development Environments (IDEs) like PyCharm, Visual Studio Code, and editors like Jupyter Notebook have built-in debugging tools that make it easier to set breakpoints, inspect variables, and step through code.

7. Unit Testing:

Writing unit tests for your code using frameworks like unittest or pytest can help catch and prevent bugs early in the development process. Automated tests make it easier to isolate issues and verify that your code behaves as expected.

8. Code Linters:

Use code linters like pylint or flake8 to catch common coding errors, style violations, and potential bugs in your code. These tools can provide insights into issues you might have missed.

9. Code Review:

Sometimes, a fresh pair of eyes can spot issues that you’ve overlooked. Regular code reviews with colleagues or peers can be an effective way to catch and fix bugs.

10. Online Resources and Forums:

Don’t hesitate to search for solutions online or ask questions on programming forums like Stack Overflow. Many developers have encountered and solved similar issues, and their insights can be invaluable.

11. Read the Documentation:

Python has excellent documentation. Often, the official Python documentation, along with documentation for third-party libraries, can provide solutions to common problems and help you understand how things work.

12. Take Breaks:

If you’re stuck on a bug and frustration sets in, take a break. Sometimes, stepping away from the problem for a while and returning with fresh eyes can help you see the issue more clearly.


Debugging is an essential part of the software development process. It’s a skill that improves with practice and experience. By using a combination of techniques, tools, and a methodical approach, you can become a proficient Python debugger and efficiently tackle any bugs that come your way. Remember that every bug you conquer is an opportunity to become a better programmer. Happy debugging!

Day 13 : Practice Problem Python Debugging

Day 13 : Solution Practice Problem Python Debugging

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