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I would use Jupyter as my backend execution engine & you then can write your functions in several languages e.g. Julia, python or octave. https://github.com/ipython/ipython/wiki/IPython-kernels-for-other-languages


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Let's note that how the code is stored is inconsequential; how it is executed is essential. Most probably your functions have a limited repertoire. Implement them properly, without storing in the DB. (I leave alone the question if a numeric integration implemented in Ruby a good idea. Let's assume you use something like Numpy of the Ruby world.) Now you ...


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You could embed an interpreter (like Lua or GNU guile) into the program using the database. (I am not sure that coding your entire software in Ruby is best; coding it in C++ might be worthwhile) You would either store in the database expressions (that is string containing Guile or Lua source) in Lua or Guile, or you might store some bytecode or some ...


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I don't know how different the functions you want to store are, but if you can isolate few different "types of functions" you could do something like this : Create several generic methods in your model which can make every special calculus needed with the help of some arguments : def integrate_over_an_area(args={}) #Do your calculus with your args. end ...


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You are absolutely correct. The function tries out all possible combinations of elements from the array. In this case, it's O(n³) and would be of an even higher power, if you wrote a similiar function for the greatest 4, 5, .. elements. The best solution for any of these problems should be of the order O(n). I just want to mention that in your example for ...


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I think it depends on complexity of the interface. If the set of calls that you can make against the database is going to be significant, then something like a REST service in front of the database would make sense to limit the server side implementation and support efforts. It will slow things down by being inserted into all flows but it will enable ...



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