Contents

Python environment

Python environment

The code you work on will run on a Python environment. Depending on what you installed (Conda, pyenv, nothing), the python command can be provided by a variety of sources.

A Python interpreter will also come with its own Python environment. Normally, VS Code will autodetect the Python environment suitable for your project. You can also tell VS Code what environment to use.

Typing which python in a UNIX-like system shows you where the Python interpreter is located.

Selecting a Python environment in VS Code

CTRL+SHIFT+P Python: Select interpreter should show a list of autodetected environments. O

ne can always select a venv that is not in the list.

This is the only VS Code setting that:

  • won’t be stored in the user settings.json file: indeed, the Python environment changes project by project

  • won’t be stored in the project .vscode/settings.json file: indeed, paths to Python environments change from computer to computer

Note that, sometimes, VS Code does not activate the proper Python environment in its Terminal tab. This is due to the Terminal sometimes initializing before the Python VS Code extension, see this issue.

Level 1

The easy option is to use Conda to manage Python environments. VS Code should detect Conda environments automatically. It will remember the Python environment you select for each project you open.

Then, use pip install to add the different tools we will discuss to your environment.

Level 2

In Level 2, we use Poetry, see Level 2: Use Poetry and Python virtual environments. The Poetry-managed virtual environment is detected by VS Code.

Installing Jupyter notebooks support

The Python VS Code extension installs support for Jupyter notebooks by default, see our explanation.

However, one needs to install the jupyterlab PyPI package to use that support.

pip install jupyterlab

or

poetry add --dev jupyterlab