Python 2 is old now, y'all!
(installed by default on Macs and Linux, but maybe you need a newer version than that!)
(great for grabbing libraries on your own machine)
(great for your own account on someone else's machine)
(in base python3 library but still too limited to be useful)
(the old standard for package isolation)
(combination of python binary isolation and package isolation)
what we usually recommend for studies, see Python in the wiki)
(python version isolation with less overhead than conda)
(link between pyenv and virtualenv, also deals with conda envs)
(a new opinionated all-in-one standard)
(another popular attempt to join all these concerns in one place)
(integrates with virtualenv and conda environments)
(disclaimer: I have not used this AT ALL but it seems pretty easy and works inside notebooks)
Create an environment
conda create --name example
conda env list
conda activate example
conda install jupyter
(how is this different from
Keep your key safe!
Those ports are usually firewalled by default, but anyone on the same machine could pretend to be you if you publish or screenshare your key.
Shared notebooks? Advantages and disadvantages...
Actual multi-tenant: Jupyter Hub
Run all with the Run button
Ctrl-Shift-F: Searchable command list
What can you do in your notebook?
Define and use functions:
Load data and plot it:
Higher resolution and size of plot defaults:
Experiment with a library that's new to you:
Some ideas, of increasing difficulty
condavs. a study-wide
bash Miniconda3-latest-Linux-x86_64.sh... hit ENTER, space to view the license, type "yes"
conda update -n base -c defaults conda
On a Mac or Linux machine:
ssh -L 8889:localhost:8889 USERNAME@SERVER.keck.waisman.wisc.edu
(replace USERNAME and SERVER)
On a Windows machine with putty:
TODO: google "SSH tunnel putty"
jupyter notebook and open the link