Jupyter team: Congrats on the 5.0 release. The new notebook is sooooo nice. All of the hard work is very much appreciated.
I'm curious what folks (users and devs alike) have settled on as their best practices for managing jupyter and ipykernels when you have many conda environments. At the moment I see two general approaches: 1) install everything into every conda environment where they are needed, and launch the notebook server from that environment or 2) only install jupyter and notebook into the root (default) conda environment, install ipykernel into the remaining environments, and launch jupyter from the default env, selecting the kernel as necessary. Is either one of those a particularly bad idea? Is there a different approach I missed? -Paul -- You received this message because you are subscribed to the Google Groups "Project Jupyter" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/jupyter/CADT3MEDT4Qx7sqFo6CnHrwzcTwS1MBSYtnouVT5ku-BqSW9-kw%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
