I'd be curious as to seeing what these circular dependencies you're seeing are (not saying I don't believe you, and I do recall in the early days of conda it doing some dumb stuff, but that particular issue seems odd)?
As for why conda: wheels do not have post-installation hooks (which given the issues with npm, I'm certainly a fan of), and while for most packages this isn't an issue, I've encountered enough packages where sadly they are required (for integration purposes), and the PyPI packages are subtlety broken on install without them. Additionally, conda (especially Anaconda Inc's commercial repositories) have significantly more optimised builds (not as good as the custom build well-run clusters provide, but better than PyPI-provided ones). I personally do not use conda (because I tend to want to test/modify/patch/upstream packages lower down the chain and test with higher up packages), but for novices (especially novices on Windows), conda for all its faults is the best option for those in the "data science" ecosystem.
As for why conda: wheels do not have post-installation hooks (which given the issues with npm, I'm certainly a fan of), and while for most packages this isn't an issue, I've encountered enough packages where sadly they are required (for integration purposes), and the PyPI packages are subtlety broken on install without them. Additionally, conda (especially Anaconda Inc's commercial repositories) have significantly more optimised builds (not as good as the custom build well-run clusters provide, but better than PyPI-provided ones). I personally do not use conda (because I tend to want to test/modify/patch/upstream packages lower down the chain and test with higher up packages), but for novices (especially novices on Windows), conda for all its faults is the best option for those in the "data science" ecosystem.