Running Jupyter Notebooks with Remote Conda Environments via Visual Studio Code Simplifying your development workflow across environments Working with Jupyter notebooks across different environments can be tricky, especially when you want the convenience of your preferred local editor with the power of remote compute resources. At EMBL we provide a Visual Studio Code (VSCode) server instance on demand that can be helpful to handle this situation. The Challenge Imagine you have a Jupyter notebook stored on a remote server and want to run it using VSCode on your local laptop.

Jupyter kernels Jupyter is a server but also an ecosystem of tools for data exploration. JupyterLab is a web interface to notebooks which can be used to document, visualize and perform computations. Computations in Jupyter are performed by a kernel, a separate component that understands how to perform calculations on request and return the result back to Jupyter. As such, a single JupyterLab installation can have multiple kernels with different configurations for different needs.