Image by the author
If you are looking to improve your workflow, speed up development, and minimize errors, the GPT-4o model is your go-to ai tool. By integrating this advanced ai into your Python projects, you can streamline your process, solve problems faster, and focus on what really matters. Even if you are new to coding, you can build Python projects using tools like ChatGPT, VSCode with the GPTCode extension, and Cursor IDE. These tools are essential to harness the full potential of the GPT-4o model in your development environment.
1. ChatGPT
We are all familiar with ChatGPT and its ability to generate Python code. In the latest update to OpenAI, the new GPT-4o model has been made available to everyone for free. I use ChatGPT to generate code, troubleshoot problems, and brainstorm ideas. It really understands the goals we want to achieve with our applications.
For example, I asked him to create a sample Python project. He provided me with all the code and instructions needed to create it, including the project structure with files and folders. You can ask follow-up questions to modify the project and even ask him to run scripts to test if they work.
ChatGPT Screenshot
ChatGPT comes with a Python environment, meaning it can generate and run code for you, displaying the result.
ChatGPT Screenshot
In short, ChatGPT is the only coding assistant you need if you are a beginner. But if you are a developer or software engineer, you need something that is integrated with your workspace. That is where CodeGPT comes in.
2. GPT code
GPTCode VSCode ai coding assistant extension that allows you to write code more efficiently. Includes ai chat assistance, auto-completion, code explanation, refactoring, documentation, unit testing, and more.
The CodeGPT extension also allows you to test multiple ai models from different vendors. You can even run your own ai model locally with Ollama and use it with the CodeGPT extension. It is a one-stop solution for software development.
In this blog, we will learn how to configure it to use GPT-4o with it. First, you need to generate an OpenAI API key by going to the Open ai APIAfter that, install the CodeGPT extension by searching for it in the VSCode extension marketplace. Next, click on the CodeGPT tab and select OpenAI as the provider and GPT-4o as the model. It will ask you to paste the OpenAI API key to access the model.
VSCode screenshot
Once everything is set up, you can start using GPT-4o to generate code, debug, document, and improve your source code.
VSCode screenshot
CodeGPT has many limitations and is slow when it comes to autocompletion. You can get a paid subscription to access better autocompletion models and ai agents, but it still falls short when it comes to integrating ai tools into the software development environment. It is still an extension that relies on the code editor.
3. Cursor IDE
He ai IDE Cursor is a perfect tool for expert programmers, senior software engineers, and data professionals. It is a fork of VSCode designed for ai-assisted software development. This means that it is not just an extension, but an ecosystem with built-in functionalities to help you write better code.
Cursor understands source code to give you better code suggestions, and even helps you write entire Python projects from scratch. I’ve completely switched my workflow from VSCode to Cursor because it’s easy to use and has fast response times compared to VSCode extensions. And I’m not missing anything—it’s basically just like using VSCode. I can still install VSCode extensions that I love and use the same environment. Nothing has changed.
In the following example, I asked GPT-4o to improve my code and it did a very good job.
Screenshot of the cursor
It also comes with online chat, the ability to understand images and documents, the ability to select code to edit or enhance it, and the ability to save the history of previous chats, just like ChatGPT.
Screenshot of the cursor
I highly recommend data professionals to switch to Cursor and take advantage of the two-week free trial to experience its amazing features. It feels natural when you write code or ask questions from GPT-4o.
Conclusion
Every data professional I know uses ai in their workflow to increase productivity and accuracy. Before ai assistance tools, it took them hours to build and test Python applications, but now they can accomplish the same tasks in minutes. All they have to do is review and run the code.
In this blog, we learned about ChatGPT’s new features for creating and running Python code. We also learned about VSCode’s ai assistant extension, CodeGPT, which allows you to use various ai models to generate and improve your Python code. Finally, we learned about Cursor IDE, a fork of VSCode built for ai-assisted software development. These are the tools I use for my daily work in data analysis, machine learning, and even web development. I hope you can benefit from them too.
Abid Ali Awan (@1abidaliawan) is a certified data scientist who loves building machine learning models. Currently, he focuses on content creation and writing technical blogs on machine learning and data science technologies. Abid holds a Master's degree in technology Management and a Bachelor's degree in Telecommunication Engineering. His vision is to create an ai product using a graph neural network for students struggling with mental illness.
