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If you are looking to improve your workflow, speed up development, and minimize bugs, the GPT-4o model is your go-to AI tool. By integrating this advanced AI into your Python projects, you can streamline your process, resolve issues faster, and focus on what truly matters. Even if you are new to coding, you can create Python projects using tools like ChatGPT, VSCode with GPTCode extension, and Cursor IDE. These tools are essential for realizing the full potential of the GPT-4o model in the development environment.
1. ChatGPT
We are all familiar with ChatGPT and its ability to generate Python code. In the latest update from OpenAI, the new GPT-4o model has been made free for everyone to use. I use ChatGPT for code generation, troubleshooting issues, and brainstorming. It truly understands the goals we aim to achieve with our applications.
For instance, I asked it to build a sample Python project. It provided all the necessary code and instructions to build it, including the project structure with files and folders. You can ask follow-up questions to modify the project and even request it to run scripts to test if they work.
Screenshot from ChatGPT
ChatGPT comes with a Python environment, meaning it can generate and run code for you, displaying the output as a result.
Screenshot from ChatGPT
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. CodeGPT
CodeGPT VSCode AI coding assistant extension that lets you write code more efficiently. It comes with AI chat assistance, auto-completion, code explanation, refactoring, documentation, unit-testing, and much more.
The CodeGPT extension also lets you try various AI models from different providers. You can even run your own AI model locally using Ollama and use it with the CodeGPT extension. It is an all-in-one solution for software development.
In this blog, we will learn how to set it up to use GPT-4o with it. First, you need to generate an OpenAI API key by going to the OpenAI API. After 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.
Screenshot from VSCode
When everything is set up, you can start using GPT-4o to generate code, debug, document, and improve your code source.
Screenshot from VSCode
CodeGPT has many limitations and is slow when it comes to autocomplete. You can get a paid subscription to access better autocomplete models and AI agents, but it is still not enough when it comes to integrating AI tools into the software development environment. It is still an extension that is dependent on the code editor.
3. Cursor IDE
The Cursor AI IDE is a perfect tool for hard-core coders, senior software engineers, and data professionals. It is a fork of VSCode designed for AI-assisted software development. This means it is not just an extension but an ecosystem with built-in functionalities to help you write better code.
Cursor understands your code source to provide you with better code suggestions and even helps you write entire Python projects from scratch. I have completely switched my workflow from VSCode to Cursor because it is easy to use and has fast response times compared to VSCode extensions. And I am not missing out on anything – it is basically like using VSCode. I can still install VSCode extensions that I love and use the same environment. Nothing has changed.
In the example below, I asked GPT-4o to improve my code, and it did a really good job.
Screenshot from Cursor
It also comes with inline chat, the ability to understand images and documents, the ability to select the code to edit or improve it, and the ability to save the history of previous chats, just like ChatGPT.
Screenshot from Cursor
I highly recommend data professionals switch to Cursor and enjoy the two-week free trial to experience its amazing features. It feels natural when you write the code or ask questions from GPT-4o.
Conclusion
All of the data professionals that I know use AI in their workflow to increase productivity and accuracy. Before AI assistant tools, it used to take 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 building and running Python code. We also learned about the VSCode 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 that I use for my day-to-day job in data analysis, machine learning, and even web development. I hope you can also benefit from them.
Abid Ali Awan (@1abidaliawan) is a certified data scientist professional who loves building machine learning models. Currently, he is focusing 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 build an AI product using a graph neural network for students struggling with mental illness.
