![]() ![]() ![]() These can be short lived (minutes or hours) or hang around forever.įor my persistent Jupyter Lab installation I’m going to create a new conda environment called jupyter, which will probably hang around forever. ![]() I generally create new conda environments for each project or task I am working on. I tend to avoid the base environment in conda as I often end up accidentally installing things here. You can set up conda on your own machine quickly and easily using the miniconda installers. I use conda to manage my local Python environments and install packages. In this post I’m going to walk through my Jupyter Lab setup on my MacBook and how I have it set to run automatically on startup. I also find them useful for exploring Python objects with tab completion and viewing docstrings. Jupyter notebooks are my preferred Python REPL to quickly testing out a bit of syntax. However, I find it really useful to keep a simple minimal installation always running on my laptop. Sometimes these are short lived installations in conda environments on my laptop, sometimes they are running on a remote server, and sometimes I use a managed service like JupyterHub or Binder. In my day to day work I generally access a variety of Jupyter installations. 5 minute read #jupyter, #jupyterlab, #macos, #startup ![]()
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