Thomas Ballinger

Alternate Python implementations with goals like running in the browser, compiling to a smaller binary, and running faster than CPython have flourished in Python's long history. They're mostly like Python, but not quite – sometimes very not quite! There are enough parts of Python and enough different users cases to keeping track of these differences hard; the libraries and corners of the language a data scientist, a web developer, and data engineer might know might not overlap much! How do we find patterns in and draw conclusions from this diversity? Let's try some tools of naturalists: phylogeny, speciation, even look for some horizontal gene transfer.