> you get acceptable performance with an insane package repository that means you can ship so much faster. You absolutely do not. There are a ton of holes in t

> you get acceptable performance with an insane package repository that means you can ship so much faster. You absolutely do not. There are a ton of holes in the Python package ecosystem that have been plugged by Julia. For example, stiff ODE solvers that mix with structured matrices, like block banded matrices, are very common in PDE fields, but Python really just has (very slow) stiff ODE solvers and unstructured sparse matrices are the only thing you can mix with that, along with a lack of a solid sparse AD. You can keep going down the list of all of these applications that are wide open, and where Julia libraries already are either (a) existing where Python libraries don't exist or (b) are orders of magnitude faster. So let's be a bit more concrete there: there are areas where Python packages can get you by, and there are not, and there are a lot of things in the not category (which is why we as devs exist!).