Best Python Debuggers in the wild


Never miss a post!

Sign up for our newsletter and get FREE Development Trends delivered directly to your inbox.

You can unsubscribe any time. Terms & Conditions.

What is Debugging? Debug, as the word suggests, it is a process of finding bugs. So, you are finding bugs in your code, and you are fixing them. Bug in any programming language is a problem you have in your program, and things are not working as you expect them to work. So, you do a thorough analysis of your code, and you find out that particular problem area, and you fix it, so that is what is called fixing a bug or debugging. There are multiple python debuggers used by programmers on a daily basis. In this article, I will talk about the best python debuggers to use.


Python Debugger (pdb)

The Python debugger is a built-in Python module that helps you debug your code. Now I am sure your favourite debugging tool is the print statement, you just insert print statements everywhere to see what is going on in your code, and that helps debug. But with the Python debugger, you are able to set breakpoints in the code where you can examine different variable values, and you can see if X is equal to 5 like you think it is at various points in the code. You can step forward line by line, in other words, execute one line of code at a time and see what is happening inside the program. As each line executes, it is a lot easier to figure out what is going wrong in the code, and you can show each line of code as it executes. So, the debugger is pretty easy to use, and it is a useful tool in debugging code.

The Python debugger tool or PDB is a tool that will save you an incredible amount of time. It is really useful and when I used to debug my Python applications when I first got started. If there was a problem and I wanted to know what kind of variable was set to what value, I would just simply print that out on the screen by literally putting print commands in my code. And I would get to the point where I would have to put print with tons of equal signs or something like that, so I could actually see the output amongst all of the logs of the code that I was running, or I could actually identify where my output was so that I could inspect which variable was set to which value. This all changed when I discovered the Python debugger tool. It saves me so much time, and I use it all day, pretty much every day, when I am debugging my code. Anytime I have any issue with my code, or I want to see what is going on. I use the Python debugger tool, and it helps me figure out how to fix the bug. Breaking into the debugger can be achieved with just a single line of python code. You just need to insert a single line of code:

import pdb; pdb.set_trace()

When execution reaches this point in the program, the program stops, and you are dropped into the pdb debugger. This is the same as inserting a breakpoint on the line below, where we call set_trace() which means execution will stop right before that line of code is executed. If you are using Python 3.7 or later, there is an even easier way simply calling the breakpoint function works in the exact same way that will automatically import pdb and call set_trace() for you. The advantage to using the breakpoint function instead of the set_trace function is that you can modify its behaviour by changing your environment variables. This allows you to enable or disable all the breakpoints before your script even runs, instead of having to comment all your breakpoint function calls out manually. Finally, the python debugger supports what is called post-mortem debugging. This allows you to break into the debugger without modifying the code, no breakpoint function, or no set trace calls. This is useful when you want to debug a program that you do not have write access to that looks like this:

python3 – m pdb


PyCharm Debugger

Using a debugger on PyCharm IDE is much simpler because it is easy to use when compared to the command line debugger pdb. Visually, debugging and testing python code on PyCharm IDE is very efficient. PyCharm is an IDE developed by JetBrains and used by millions of python developers. PyCharm is a complete integrated development environment that has debugging features. You would need some time to get used to python debugger in the beginning. You can use dialogue boxes in PyCharm to get the guidance for code execution process and also to allow you to choose various debugging parameters. Suppose you are using debugging mode in PyCharm. In that case, you are either allowed to insert breakpoints on some specific code lines (this can be achieved by left mouse click on a specific code line), or you can use exception breakpoints, which is set by the debugger when a specific exception occurs.

PyCharm can help you debug your code and save you a lot of time and a lot of headaches while coding. The PyCharm debug tool is extremely useful and extremely powerful. When I first found out about it, it kind of blew my mind because it was allowing me to do things that I would never have been able to do in idle and save me tons of time. So first of all, the debug tool is at the top right-hand corner of the PyCharm ide, it is right beside the run option, and it looks like a little bug that makes sense as per its name. So, if you click on debug sign, it will bring up your basic console, and it will run the program just like it would before. The only difference is you get a debugger tab that has a lot of cool tools in it. You can hover over some of the options and kind of play with it for yourself.


Visual Studio Debugger

You get a comprehensive debugging experience or Python in Visual Studio, which includes attaching to running processes, evaluating expressions in the Watch and Immediate windows, inspecting local variables, breakpoints, step in/out/over statements, set next statement, etc. You can perform debugging in Visual Studio without a project. With a stand-alone Python file open, right-click in the editor, select Start with Debugging, and Visual Studio will launch the script with the global default environment and without any arguments.

A debugging session in visual Studio starts with the Debug > Start Debugging command, the F5 key or the Start button on the toolbar. Breakpoints in debugging stops the execution of code at a marked point so you can inspect the program state. You can set breakpoints in your python code by clicking in the left margin of the code editor or by right-clicking a line of code and selecting Breakpoint > Insert Breakpoint. A red dot will appear on each line with a breakpoint. When you click on the red dot or right-click the line of code and select Breakpoint > Delete Breakpoint, it will remove the breakpoint. You can also disable it without removing it using the Breakpoint > Disable Breakpoint command. Once stopped at a breakpoint, you have multiple options to step through code or run blocks of code before breaking again.

During a debugging session, you can use two interactive windows: the standard Visual Studio Immediate window and the Python Debug Interactive window. The Immediate window (Debug > Windows > Immediate) is used for quick evaluation of Python expressions and inspection or assignment of variables within the running program. The Python Debug Interactive window (Debug > Windows > Python Debug Interactive) is richer as it makes the full Interactive REPL experience available while debugging, including writing and running code. It automatically connects to any process started in the debugger using the Standard Python launcher (including processes attached through Debug > Attach to Process).


Jupyter Visual Debugger

By default, JupyterLab 3.0 now ships with a debugger front-end. The Jupyter notebooks, code consoles and files can now be debugged from JupyterLab directly. Jupyter users like to use the notebook as an interactive communication tool and experiment in the notebook.

To enable the debugger and make it visible, a kernel is required with support for debugging. Here is a list of kernels that are known to be supporting the Jupyter Debug Protocol:

  • xeus-python: Jupyter kernel for the Python programming language
  • xeus-robot: Jupyter kernel for Robot Framework

There are other Jupyter Kernels also that support debugging and are compatible with the JupyterLab debugger by implementing the Jupyter Debugger Protocol.

xeus-python can be selected from the JupyterLab launcher, or it is also possible to switch to the xpython kernel using the kernel selection dialog. Then you can enable the debugger, set breakpoints and step into the code.


Komodo Debugger

You can easily debug Python programs locally or remotely in Komodo, including debugging in CGI environments. The Komodo debugger is a tool that analyses the python programs on a line-by-line basis, monitors and alters the variables, and checks output as it is generated. Komodo debugger offers many debugging features like breakpoint and spawnpoint control, stepping, watching variables, remote debugging, viewing the call stack, adding command-line arguments, sending input, interactive shell.

Komodo provides debugging support for Python, and other programming languages like Perl, PHP, Ruby, XSLT, Tcl, and JavaScript (via Google Chrome). You can access the debugger commands from the debug menu, by shortcut keys, or from the debug toolbar. When debugging a Python program remotely, the program is executed on the remote machine, and the debug output is sent to Komodo. Komodo controls the debugging session once the session starts on the remote machine. Komodo also supports the concurrent debugging of multiple applications or multi-session debugging. With multi-session debugging, Komodo can debug more than one project at a time, regardless of the supported languages used in the programs being debugged. When debugging multiple sessions, each session has a unique debug tab (located in the Bottom Pane) for controlling the debug actions specific to that process.


Final Thoughts

Debugger plays a vital part in a programmer’s life. You might not use it daily as a beginner, but you would use a debugger every day after gaining some experience and working on some live projects. So, choose one of the python debuggers mentioned in this article and start debugging your python code.



Our website uses cookies that help it to function, allow us to analyze how you interact with it, and help us to improve its performance. By using our website you agree by our Terms and Conditions and Privacy Policy.