| TLDR: Will the Julia grow to a significant fraction of python's popularity and capability for general, web and data science programming? I was looking at python for a good general purpose scripting language, .net libraries, etc with statistical and data science capabilities. It seems that despite the success and burgeoning capabilities, The pydata ecosystem has inherent limitations (that I would bump up against in my use cases). So I turn to Julia a purportedly general purpose language that excels at numerics, with easy python interopt to ameliorate the current embryonic state of libraries. Sounds great, but the analyst in me is looking for one language that is versatile while still fullfililng my data analysis requirements... I don't want to invest in an ecosystem that will stagnate in terms of general programming, web programming, data science and job demand. I feel bullish on Julia, but not completely sure. I would be quite grateful for everyone's thoughts on this? Thanks |
My take is that I'd really like Julia to take off (I would really like to be less penalized for writing loops), but libraries, and especially libraries that allow people to use it as an analysis language (rather than for writing their own bespoke stuff) is essential.