Python Debugging

Python Debugging: A Comprehensive Guide

Debugging is an essential process in the development of any software system. Python debugging refers to the process of identifying and fixing errors or bugs in Python code. Debugging is a crucial skill for any Python programmer because it aids in identifying and correcting errors before they become severe issues. In this article, we will take a close look at Python debugging, its various techniques, and tools to debug your Python code and make it more efficient.

Types of Debugging

Debugging is of two types-
Interactive debugging: as the name suggests, interactive debugging allows you to interact with the program being run and halt it at certain points in order to inspect the state of the program at that point. In Python, the `pdb` module provides interactive debugging support.
static debugging: Static debugging is the process of identifying and fixing issues in code that have been identified without running it. Static analysis tools like `pylint`, `pyflakes`, and `flake8` can assist in identifying issues with your code without needing to run the code.

Python Debugging Techniques

Python debugging techniques are helpful to identify the bugs and debugging errors. Let’s dive into a few of Python’s most effective debugging techniques.

Print Debugging

The print debugging method is the oldest and most used technique in Python for debugging. By including statements in the code, we can output critical variables, function returns, and other data to the console or file. The print function is simple to use in Python for debugging.

`print(“variable_name”, variable_name)`


Logging is an alternative to the print debugging method. Logging provides a more sophisticated approach and can be thought of as a much more flexible version of print debugging. In Python, `logging` is the built-in module to use to produce logs. The `logging` module includes various options to log different log levels such as debug, info, warning, error, and critical.


Debuggers are another powerful Python debugging tool. Debuggers provide a large number of features such as tracing the execution flow, stopping code execution, stepping into functions, and so on. The `pdb` module, PyCharm, and Visual Studio Code are a few examples of integrated development environments (IDEs) that include debugging tools.

Python Debugging Tools

Python comes with several debugging tools that assist in detecting and fixing errors in your Python code. Let’s have a look at some of the essential Python debugging tools.

1. The Python Debugger pdb

The `pdb` module is a simple yet effective way to debug Python scripts interactively. The `pdb` module can be used in a script like this:

import pdb

Once execution reaches the place where pdb.set_trace() is called, the debugger will stop and show you a prompt where you can investigate the state of the program.

2. PyCharm Debugger

PyCharm debugger is a versatile tool that supports interactive debugging, debugging Django Framework applications, and debugging multiple threads or asyncio applications. The PyCharm debugger includes a variety of advanced features, such as setting breakpoints on specific lines of code, callstack inspection, and conditional breakpoints.

3. Visual Studio Code Debugger

One of the most widely used Python IDEs is Visual Studio Code, and it includes a built-in debugging tool. The debugger can be accessed via the VS Code editor, and it includes features such as set breakpoints, investigate issues in a variety of formats, debug multiple threads or async applications, and inspect complex data structures.


Python debugging is a critical skill for any Python programmer, and debugging tools like `pdb`, PyCharm, and Visual Studio Code provide significant assistance. When debugging, consider techniques such as print debugging, logging, and debugging to identify issues with your code. Incorporating Python debugging into your workflow is a great approach to improve your code quality and productivity. Therefore, you must master these Python debugging techniques and tools to develop your code confidently.

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