This feels like Schrodinger's Cake to me (you know, having it and eating it too). > ... the first of which is called "biased reference counts" ... With this scheme, the reference count in each object is split in two, with one "local" count for the owner (creator) of the object and a shared count for all other threads. Since the owner has exclusive access to its count, increments and decrements can be done with fast,…
This is not correct. There is a lot of data analysis code in the research and scientific community written in python. A lot of PyCon attendees and speakers come from these communities. Oftentimes, it’s not easy to write code to perform a task entirely in numpy, and then you incur massive slowdowns (often 20-100x). This is a common and contemporary problem in the python ecosystem.
GVR initially didn’t think that python needed to be faster either, but recently changed his mind. You can find a presentation on his motivations here: https://github.com/faster-cpython/ideas/blob/main/FasterCPyt...
Sam Gross comes out of that community so he’s familiar with the motivations for making raw python faster.