| > Julia is very fragmented No, it isn't. I'm using Pandas, DF.jl, and even polars at work. DF.jl is by far the best/easiest/quickest to use, as its syntax is consistent. Polars is a bit more annoying as its syntax is further along the learning curve that I have gotten yet. Pandas ... what to say about a library that will happily return a pd.Series in one moment, and a pd.DataFrame in another, for the same function call. This means you need extra code like if type(ret_thing) = pd.Series:
# then do something to coax it back to a df. lest your actual code break. This is of course the same language that has API differences that make no sense in, say, re.match vs re.findall vs re.search. I've been burned by all of those. So, look, we get you hate Julia. That's fine. Go live your python life to its best. But really, stop with the misinformation/FUD. This speaks volumes about you, and tends to make the case precisely the opposite of what you think. And yes, I use Python, Julia, C++, and many other languages in the $day_job. |
Yes the ecosystem is very fragmented. It's done so by design. One of the major contributors to the language wrote a paper about it.