ChatGPT can be a powerful ally in all your Python projects, especially if you use GPT-4, its most sophisticated language model. But besides creating code with ChatGPT, can you also utilize the chat bot to debug code? The answer is a resounding yes.
Read on to learn more about ChatGPT’s ability to debug Python code.
How Does ChatGPT Debug Python Code?
Now that you know that you can, in fact, debug Python code with ChatGPT, the next logical question is: How does Python code debugging with ChatGPT work?
Basically, ChatGPT can debug Python code by answering questions about Python syntax and various concepts. If you’re not sure why a certain function doesn’t work or how to incorporate it correctly into your code, you can ask ChatGPT for an explanation. It’ll shed light on the issue and provide an example to help you debug the problem faster.
There’s also a more direct way of debugging Python code with ChatGPT. All you need to do is upload your code snippet into the platform and tell the AI that the code doesn’t work. Give it a few seconds, and ChatGPT will track down and replace any syntax mistakes with correct versions. This makes it perfect for mastering a particular programming language.
How to Use ChatGPT to Debug Python Code
Whether you have an IndexError, NameError, ImportError, or any other type of bug, you can take the following steps to resolve it with ChatGPT:
Step 1 – Identification
Identifying a bug in Python is straightforward if the program sends a readable error message. For example, if you have a syntax bug, Python will typically show the following message: SyntaxError: invalid syntax.
But this isn’t always the case. Python may have a subtler way of indicating a bug, such as unexpected behavior.
This is where your programming knowledge comes in. If the errors aren’t obvious, try to find instances of unwanted app behavior to pinpoint the problem.
Step 2 – Isolation
Once you identify the bug, you now need to isolate it. In other words, highlight the code snippet that’s caused the issue. You can do so yourself or ask ChatGPT to help you find the incorrect code line(s).
Step 3 – Understanding the Purpose
You can’t fix a buggy line of code unless you know its purpose. Find out why you need the problematic code and how it fits into the grand scheme of things. Who knows, you may come to learn that you didn’t even need the code in the first place.
If you’re having a hard time with this step, you can ask ChatGPT for expert insights. It’ll tap into its database to find similar code and help you understand its purpose.
Step 4 – Debugging
Depending on your input, ChatGPT will tell you to employ Python’s debugging tools or provide the correct version of the buggy code. The former approach is more complex, but it’ll help you learn more about various debuggers so you can use them on your own the next time you encounter a bug.
Step 5 – Testing
The last step is to test ChatGPT’s solution. Simply replace the original with the new code and make sure the app works. If the AI platform encourages you to use a debugger, ask for instructions on how to do so.
Example of ChatGPT Python Debug
Suppose you’re concatenating a string and an integer in Python, and the system gives you a TypeError. The error refers to the following lines:
mystr = “IronMan”
num = 4
print(mystr + num + mystr)
To use ChatGPT to debug this error, simply paste the lines into the prompt window and ask the system why the code is throwing a TypeError. ChatGPT will likely say that you’re seeing the error because you want to concatenate an integer (num) and string (mystr) with the + function. Python doesn’t support this. The + function can only concatenate multiple strings, not strings and integers. What you need to do instead is convert your integer to a string with the ‘str()’ operator.
From there, ChatGPT will probably give you the correct version of the code:
mystr = “IronMan”
num = 4
print (mystr + str(num) + mystr)
You should also receive an explanation why this code works: the ‘str(num)’ functions converts the number ‘num’ into a string, allowing you to concatenate the integer with the first string using the “+” function. The result of the code should be: IronMan4IronMan
What Are the Benefits of Debugging Python Code with ChatGPT?
If you’re tired of manual Python debugging, ChatGPT can be the light at the end of the tunnel. Here’s why you should consider using the AI to eliminate bugs:
Benefit No.1 – It’s Fast
If you’re an advanced Python programmer, there probably isn’t a line of code you can’t debug on your own. But think about how long it takes you to do so, especially if you’re working on a complex project.
This isn’t an issue if you use ChatGPT. The AI can debug complex code in seconds, especially if you use GPT-4.
Benefit No.2 – It’s Perfect for Beginners
The best way to master Python is to learn from your own mistakes. However, you’ll hardly make any progress if you don’t know what you’re doing wrong. Whenever you encounter a bug, you need to understand why it occurred to prevent future instances.
That’s where ChatGPT comes in. The tool provides detailed explanations of Python bugs to help you understand what went wrong. It can also supplement the explanation with a side-by-side comparison of the original and new code to further deconstruct the bug. The more you learn about the problem, the less likely you are to reproduce it.
Benefit No.3 – It’s Straightforward
ChatGPT isn’t the only platform that can debug Python bugs. There are many other solutions that can do the same, including IPython, and PDB. That said, these alternative options are time-consuming and often require advanced coding knowledge that may eclipse your current skills.
ChatGPT is superior because it simplifies the debug process. All it takes to use the AI is to copy/paste the code into your prompt field and ask the AI why it doesn’t work. Within seconds, ChatGPT will provide a relevant response with minimal input on your part.
Benefit No.4 – It’s an Easier Way to Follow Up the Debug with Documentation
Paperwork is the most tedious part of any programming project, but you can’t ignore it. Otherwise, the person analyzing your Python code won’t understand all the nuances, making it harder to keep the entire team on the same page.
The good news is that you can outsource paperwork to ChatGPT. Once the system debugs your code, you can ask it to generate the corresponding documents. It’ll analyze the code, contextualize the logic, and explain how it fits into the code’s functionality.
Another great thing about ChatGPT is that it can tailor the language of the documents to the readers. Whether your readers are fellow programmers or non-tech-savvy personnel, ChatGPT will ensure they understand the code.
Plus, ChatGPT produces paperwork in many different formats, including JSDoc, HTML, and Markdown, allowing you to integrate it with your code editor.
What Are the Downsides of Debugging Python Code with ChatGPT?
While debugging Python code using ChatGPT is fast and intuitive, it’s not perfect. You should be aware of a few drawbacks of this process before you proceed:
Downside No.1 – It Makes It Harder to Maintain the Entire Code
Let’s say you debugged extra-long code with ChatGPT, and it works. Reviewing it manually would be too time-consuming, so you go ahead and paste the new code directly into your Python application. Why is this a bad call? Because you don’t know what you’ve added to the original code.
With manual debugging, you’re always aware of the edits made to the code. Conversely, if you paste ChatGPT-modified code blindly, you can never know if the AI has introduced underlying changes to the code. And the unwanted tweaks may have unintended consequences later, requiring you to go back to the drawing board.
To avoid this, double-check every edit made by ChatGPT, no matter how time-consuming it might seem.
Downside No.2 – It Requires Accurate Prompts
ChatGPT is powerful, but it’s not almighty. The AI requires accurate, relevant prompts to generate the right answer. Unless you clarify what exactly you need the platform to do, it’ll likely provide a generic response.
Downside No.3 – It Might Ignore Your Security Practices
ChatGPT doesn’t know your organization’s security policies by default. As such, it won’t reflect those policies in the debugged Python code.
If you use the code, you risk information leaks. To keep this from happening, provide ChatGPT with a few lines of code that reflect your security practices and clarify that the fixed code should be in line with it.
Your Programming Skills Are Irreplaceable
Even though you can debug Python code with ChatGPT, don’t forget that ChatGPT can’t replace your skills. You still need to check the result to ensure it’s compatible with the rest of the code and doesn’t jeopardize the basic functionality of your app.
But if you use the AI responsibly, it’ll skyrocket your Python performance. You’ll be able to debug code faster than ever and focus on other, more important tasks.
