I think part of the issue here is that in an extremely well-established language like Python, there are large organizations with deep pockets that pour resources into a few high-profile packages in key problem areas. It’s not there is less duplication (how many re-implementations of numpy are we up to by now?), it’s simply that it is easier to identify a well-resourced solution.
And yes, “Julia is not as well established as Python, does not have as much corporate and institutional support, and does not have as many developers” is a perfectly valid criticism! … but this observation does not lead to much productive discussion.
Are there ways we could improve things like search tools? Yes! Are there areas where it would be useful for people to write more documentation? Definitely!
But “be more like Python” == “get more resources” is not really actionable. (Nor is the monolithic Matlab model of “bundle ‘official’ versions of everything” a productive approach for decentralized free/open-source development.)