During the course of this tutorial, you learned how to create a Python project, create a virtual environment, run and debug your Python code, and install Python packages.

To ensure the environment is properly set up from a shell perspective, use an Anaconda prompt and activate the desired environment. Then, you can launch VS Code by entering the code . …

A quick start guide to get you up and coding with the Python extension in Visual Studio Code.

VS Code comes with great debugging support for Python via the Python Debugger extension, allowing you to set breakpoints, inspect variables, and use the debug console for an in-depth …

To work with Python in Jupyter Notebooks, you must activate an Anaconda environment in VS Code, or another Python environment in which you've installed the Jupyter package.

Let's install a language extension to add support for Python, or any other programming language you are interested in. Select the Extensions view in the Activity Bar.

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Linting highlights semantic and stylistic problems in your Python source code, which often helps you identify and correct subtle programming errors or coding practices that can lead to errors.

Editing Python in Visual Studio Code Visual Studio Code is a powerful editing tool for Python source code. The editor includes various features to help you be productive when writing code. …

In this section, we will create a folder to open as a workspace in VS Code, set up a Python virtual environment, and install the project's dependencies. In your file system, create a project folder …