[dannyz]

I think Python has a large advantage in this space since it is not as specialized. For many projects that I work on the actual core number crunching code is small (or part of a library I don't have to worry about). The rest of the code could be scraping data, or a web application. These are things that there are numerous packages available for in Python but seem to fall outside the focus of Julia.

[asgraham]

I would highly recommend reading this recent post in the Julia forums [1]. It's from a "relatively new" Julia user explaining why Julia is actually a very good general purpose language, e.g. for string manipulation of scraped data. You do have a good point about packages, though: The problem is that the user base is smaller than Python's so some packages have yet to be created. And since the userbase is currently largely numerical programmers, non-numerical packages are more likely to be missing.

[1] https://discourse.julialang.org/t/not-only-for-technical-com...

[lenticular]

Julia would be ideal for those task as well, but alas the libraries aren't there. Julia can easily call Python functions with PyCall, although I still wouldn't want to extensively use a complicated Python library in this way.

[peteradio]

Seems like it would be better to call Julia from python.

[Sean1708]

They're way ahead of you: https://github.com/JuliaPy/pyjulia

[elcritch]

Python doesn't have the typing support or even availability of many types. Calling Julia from Python in some cases would require something like cython or require even using the C api ahem.