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This is now happening. The DifferentialEquations Library in Julia seems to be best in class.

More importantly: I can imagine writing algorithmic improvements to it for my use case, which is where I hit a wall with python + scipy/numpy/numba.

I can't go and use my python skill to teach a scipy routine about some feature I need.



This is where Julia really shines. Hopefully as more researcher's realize they can quickly make customized/specialized implementations for their projects it'll help reinforce momentum. It's awesome being able to quickly dig into a library, grok the algorithm and tweak it. Actually could make for some fun hackathons!




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