Even though you can do `@which naked_function` it's a fair position to have that you prefer to import modules and be explicit about where they come from. I tend to prefer explicitness like that in package code, but for data analytical scripts (like the examples here) it would be superfluous in my opinion.
It is nice that Julia leaves this style decision to the user. I personally find the constant prepending of modules to be one of the clumsiest aspects of Python for data analysis.
Program structure by text formatting is a misfeature, though. What you do need though to make sure code remains readable is strong convention. I think actually that's the most unique feature of Julia (as also alluded to in the post) - how much of julia's ecosystem that works because of social convention (and conversation).
Another compelling argument is that {} , while very easy to type on an English keyboard, is highly awkward on keyboards of almost any other language in the world. E.g. I'm Danish and on my Mac { involves flexing the right thumb down to hit right-alt while typing 7 with my middle finger and holding down shift with my left pinky. `end`, though, being actual letters, is completely easy and fast to type (on languages that uses the latin alphabet).