
Finally, it is less risky to mess with your other projects when you work with virtual environments. This is because with the virtual environments, the project is reproducible, and we will need to install only the required libraries as stated in the requirements.txt. Moreover, it is more efficient to work with the necessary only libraries. When we work on a Data Science project, which can include a Flask API, it is better to have full control over the libraries used in the project.

In this post, we will provide you a walk-through example of how to work with VS Code and virtual environments. Now, you’re ready to develop the first program in Python.We have provided examples of how to work with conda environments.

Once the installation completes, you can launch the VS code application: Install Python Extension Second, launch the setup wizard and follow the steps. To set up the VS Code, you follow these steps:įirst, navigate to the VS Code official website and download the VS code based on your platform (Windows, macOS, or Linux).

This tutorial teaches you how to set up Visual Studio Code for a Python environment so that you can edit, run, and debug Python code. The best part is that the VS Code is open-source and free.īesides the desktop version, VS Code also has a browser version that you can use directly in your web browser without installing it. VS Code comes with many features such as IntelliSense, code editing, and extensions that allow you to edit Python source code effectively. It’s available for Windows, macOS, and Linux. The Visual Studio Code is often called VS Code. Visual Studio Code is a lightweight source code editor. A quick introduction to the Visual Studio Code Summary: in this tutorial, you’ll learn how to set up Visual Studio Code for Python.
