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julia has really good interop with both of python and R as well as cpp, matlab, mathematica and others. Also it's not just about the numbers.
by adamnemecek 7y ago
julia has really good interop with both of python and R as well as cpp, matlab, mathematica and others.
Also it's not just about the numbers.
- randomvectors 7y agoSo you're telling us not to waste our time with R or Python... but to constantly interop with R and Python?
- adamnemecek 7y agoI mean if there are packages that you need then be my guest. But like if you are starting a new project, julia is a more productive language.
- s_Hogg 7y ago> julia is a more productive language Source for this, please?
- adamnemecek 7y agohttps://news.ycombinator.com/item?id=20240155 https://news.ycombinator.com/item?id=20240155
- ddragon 7y agoIt would really still depend on the support libraries around the task you want to write, if you really need more performance for the parts that those support libraries don't cover (and beyond what you get with PyPy or Numba) and which language you have more experience with. If you're really going down to the FFI, it's hard to think it wouldn't be more productive, but that's not what a true beginner like the target of this book would do. Though it's quite nice to quickly extend some tool for your purpose without compromising anything or to understand how something works thanks to being written in high level code. Syntax-wise, Julia's Common Lisp-like feature set gives the language a lot of power, but normal use will probably be just on par with Python in terms of productivity.
- ivirshup 7y agoI love Julia, but feel the interop story could use some work. If I want to have my python package depend on some Julia code, how easy is that? Last time I checked (a few months ago), it was pretty difficult.
- ChrisRackauckas 7y agoYou can get it done with a little bit of user interaction: https://github.com/JuliaDiffEq/diffeqpy https://github.com/JuliaDiffEq/diffeqpy