There was a time when everyone was gushing about software development, and then slowly people began understanding the technology and started giving importance to software testing, and now it's time for us to welcome debugging. Debugging is one of the most crucial aspects of the entire software development process, which includes spotting errors as well as resolving them in the meantime in a specific program’s code.
Debugging is a very important process that is not just limited to identifying errors and issues, but also a sure-shot way to ensure that the overall program’s functionality is not at all disrupted. Debugging is a proper systematic approach considered regarding problem-solving. Debugging in the right manner enables programmers to isolate issues, also they gain a proper understanding of the why part, and implement necessary solutions.
So basically, this one is a highly systematic process considered by developers to identify as well as correct the issues so that the developed software behaves as intended or operates most reliably.
Apart from this, debugging can be beneficial in many ways, such as:
Improved code quality - Debugging assists developers in spotting and fixing errors within the code. This does enhance the overall quality of code. Detecting errors at a very early stage can prevent them from becoming more significant issues, which leads to a severe reduction in numerous kinds of bugs and vulnerabilities.
It has been observed that one of the common reasons for software crashes is due to high-quality code. And this can definitely hinder user experience as well. By debugging in the right manner, you can ensure that the developed code is severely compliant with ongoing coding practices and best practices.
Enhanced productivity - Debugging can enhance overall productivity in the software development realm. You see, when developers began spending less time fixing bugs and errors, the efficiency and productivity automatically increased. In addition, it is feasible for them to focus on developing new features and enhancing the user interface. Debugging certainly reduces the number of support tickets and bug reports, which means it is possible to complete projects at a much faster rate.
Appropriate cost savings - It is possible to save money in the long run, all thanks to debugging. As mentioned earlier, by identifying errors early, it is possible to prevent more significant issues right from the very beginning. Meanwhile, this also reduces the risk of project delays and costly rework. As a result, lots and lots of money can be saved from debugging.
What is Python Debugging?
Python has been one of the most popular technologies since it was released in 1991, and the mastermind behind the tech was Guido van Rossum. Over the years, the tech has gone through several changes and has been considered the best object-oriented programming language. With the severe gain in popularity, the need for Python debugging tools and techniques has increased.
What does Python debugging mean? It refers to successfully identifying, fixing errors within the code. Some of the errors that can prevent code from functioning include syntax, semantic, and runtime errors. So what is Python debugging all about?
Identify the error - This is possible by simply reading the error message and keeping tabs on the log file, testing the code, and see in case if there is something off or not.
Reproduce the error - To successfully debug the code, it is very important to reproduce the error consistently.
Isolate the source of the error - As soon as the error is reproduced, it is very important to isolate the source of the problem, and this is possible by incorporating different techniques such as adding print statements, using a debugger, and examining stack traces.
Forming a hypothesis - Once all the information is successfully gathered, make sure you form a hypothesis regarding what might be causing the error.
Testing- The next aspect is to use the hypothesis to guide the debugging procedure by making small changes to the code and then seeing what the end result is.
Repeating the process - In case the hypothesis is incorrect, keep repeating the process to isolate the error.
Verifying the fix - As soon as you have fixed the error, make sure the code is working in the correct manner.
Documenting well - Lastly, make sure to document the error and fix it so that there is no scope for any miscommunications in the future.
So now you must be wondering whether it is worth performing Python debugging or not? Well, it is always worth considering Python debugging after all, a successful development project is said to be absolutely free from errors and issues. I mean, finding bugs now and then can be pretty overwhelming, time-consuming, and daunting, especially when the code begins to grow in size as well as complexity.
It may quite interest to you to know that a debugger can assist in pausing the execution of the code as well as inspecting variables, expressions. And do you know what the best part here is? This is possible at any given point. So fret not, it becomes pretty easy to isolate the source of an error and understand how the code is behaving. Much like any debugging technique, Python debugging offers several benefits, such as saving ample time, enhancing code quality, better understanding of the code, and debugging complex and complicated errors.
Top Debugging Tools for Python
PDB
The first and foremost debugging tool offered by Python is PDB. This one is a built-in Python debugger, one of the finest powerful tools that ensures an interactive debugging experience. And do you know what is an amazing aspect here? You are bound to receive an interactive debugging experience. Moreover, it is possible to pause the program’s execution and inspect its state; as a result, everything becomes easy to understand, so if you become clueless at any point in time, the debugging tool can work wonders. Moreover, it is possible to set breakpoints by stepping through code line by line and evaluating variables in real-time.
import pdb;
pdb.set_trace()
So by doing so, the execution will be paused, and you are bound to have instant access to the PDB command-line interface. Down below, I would like to mention certain commands that must be taken into consideration:
- To execute the next line of code - n (next)
- If you want to continue execution until the next breakpoint - c (continue)
- If you want to step into a function call - s (step)
- If you want to print the value of the specified variable - p variable_name
- If you want to exit the debugger - q (quit)
Also, it is feasible to use he pdb.set_trace() method;
import pdb
def add(a, b):
answer = a+b
return answer
pdb.set_trace()
sum = add(1,2)
print(sum)
Right from offering accurate breakpoints to ensuring step-by-step execution, variable inspection, and of course, conditional breakpoints, the PDB offers it all.
PyDebugger
The next interesting Python debugging tool to take into consideration is PyDebugger. This one is a third-party tool which is created to offer a more visual as well as user-friendly debugging experience, especially in comparison to PDB. This Python debugging tool must be considered by developers who prefer a graphical interface in comparison to a command-line experience. When integrating the tool with Python, everything is simplified, right from identifying to inspection to fixing bugs in real time.
If you type;
From pydebugger. Debug import debug
debug(variable1="data1", debug=True)
Then the output will be:
$ python debugger.py
2024:10:22~12:09:18:573544 debugger.py -> variable1: data1 -> TYPE: -> LEN:5 -> [debugger.py:debugger.py] [3] PID:60855
Much like PDB, even PyDebugger offers a wide range of benefits such as breakpoint management, call stack visibility, variable inspection, exception handling, and the list goes on.
Visual Studio Code Python Extension
The Visual Studio Code Python extension is another interesting, versatile tool mainly used by Python developers. This tool ensures seamless integration with other Python-based tools, so this debugging tool turns out to be everyone’s favourite, including both novice and experienced developers.
To ensure successful debugging, the Python debugger must be successfully installed in Visual Studio Code. By doing so, you can make the most of some of the most extraordinary features, including real-time variable inspection, step-by-step debugging, and breakpoints.
Moreover, this debugging tool highly supports the latest debugging modes, such as ‘debug-test’ or ‘debug-in-terminal’; no wonder it is easy to get things configured in the launch.json file.
Here is the key for successful outcomes: try setting breakpoints on expressions and hit counts. By doing this, you are offering a flexible debugging environment that can handle different subprocesses as well as other advanced debugging capabilities.
IPython
Another interesting debugging tool, which offers an interactive shell for Python and comprises some of the most powerful features, especially to ease debugging and data exploration. The Python debugging tool ensures a highly robust environment, which turns out to be quite fruitful for interactive computing and enhances the debugging experience.
IPython features a quite rich toolkit where it is possible for developers to execute code snippets and visualise outputs that too, in real-time; no wonder it is an excellent choice when it comes to learning and development.
The Python debugging tool supports a wide range of debugging techniques, such as exclusive use of magic commands like %debug, so nothing can stop you from gaining a post-mortem debugging interface, especially after an exception occurs. The command line enables developers to successfully inspect the stack frame as well as evaluate different variables during the time of the error, so it becomes pretty easy to identify issues.
IPython successfully integrates well with Jupyter notebooks, by doing so it enables end users to mix code execution with rich text documentation and visualisations. No wonder data science and exploratory programming ensure a more comprehensive understanding of code behaviour.
Some of the most crucial benefits offered by IPython include - interactive shell, Post-mortem debugging with %debug, magic commands, real-time variable inspection, easy integration with Jupyter Notebooks, and absolute support for Rich Output visualisation.
Sentry
This one is an error-tracking and performance monitoring tool that has the potential to diagnose and fix relevant Python issues. With the help of the following tool, it is possible to break down detected errors and opt for more significant insights, especially when you get full access to the space where the code produces lots and lots of bugs.
Some of its prominent features include error detection, absolute performance monitoring, stack tracing for error insights, event log reader, free version available with limited user capacity. Since it is easy to diagnose and fix Python issues efficiently, you are bound to gain detailed insights into detected errors. It is possible to identify as well as address bugs quickly, leading to enhanced code quality as well as enhanced project stability.
So error detection, performance monitoring, stack tracing for error insights, and event log reading everything is available here.
Sentry is highly recommended for projects that prioritise open-source solutions and require support for multiple programming languages, and this needs to go beyond Python, be it Go, JavaScript, and Ruby.
So if you are looking for a Python debugging tool that is an open source solution, ensures high transparency, flexibility, offers support for querying multidimensional data structures, facilitates root causes, ensures seamless integration with different logging and PSA tools, this is it! Your search needs to end here.
Further below, I would like to mention certain factors on which Python debugging tools must be evaluated:
- Easy to use
- Seamless integration with the development environment
- Absolute debugging capabilities
- Quick support and active community
- Cost-effective
- Seamless compatibility
Conclusion
And we are done for now! In short, debugging is one of the most popular and vital skills for Python developers to succeed. Whether they want to perform basic command-line debugging or advanced methods such as remote and post-mortem debugging, the tools and techniques mentioned above can definitely make things easy for you.
By now, I hope you realize that the significance of debugging and monitoring tools cannot be overstated. Since these tools are meant to enhance the quality of code and the developed app can perform successfully under varying conditions. So what are you waiting for? Time to create a cleaner and highly reliable Python code. Last piece of advice I would love to offer is that being a successful developer means you need to foster a culture of continuous improvement, which means the app has not just met user expectations but also is capable enough to adapt to the ever-evolving technological landscape.
So developing high-quality Python applications might seem to be a tricky venture, but it is definitely a doable job. All you need to do is consider a reputable and reliable development company that carries immense knowledge with Python and has enough experience as well.
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