This is not just interesting for comparison but its interesting for people that know R/Python how to go from one to the other.
Python: There should be one, and only one, preferable way to do things. Though this may not be obvious at first.
R: Every author has a different style of doing things, reflecting in the code.
As for the comparison in general: You can call R from within Python. So Python is at least as powerful as R. The rest (BeautifulSoup, Compression, Game development etc.) is icing on the cake.
He says "In R, there are packages to make sampling simpler, but aren’t much more concise than using the built-in sample function" but using caret is more concise.
Added: Later in the section on random forests he says "With R, there are many smaller packages containing individual algorithms, often with inconsistent ways to access them." Which is why you want to use the caret package as it makes accessing many machine learning packages consistent and easy.