"Replacement for X" is a vague phrase - will Julia take over every usecase of Python? Unlikely. Will projects with established Python codebases, that work well for them, suddenly switch to Julia? Nah.

Will new projects that need a flexible performant language, that would have otherwise been shoehorned into Python as the closest available option, choose Julia instead? Quite likely, and that happens a lot.

Python has its place, and is good at a lot of things. But there have always been a lot of projects that have straddled the line between numeric computing and general purpose computing, needing both, where Python was chosen for lack of choice, just because it was the best among the bad options. That's the pain point Julia addresses, and the people who have experience being stuck in that situation understand what its place is and why it has the success it has. (And being a well designed language that's a pleasure to use helps too.)

I don't really understand this comment. It was never intended to be a replacement for python in general use; do you mean as a numpy/scipy replacement?

In that case, I guess we'll see. Python will never be a particularly good language for implementing such things, but has become pretty ok for using them once someone has implemented (in another language, and made the python bindings).

Network effect is the real barrier, python itself is very easy to toss for this use .