Python is well suited for creating wrappers all over native libraries mainly because it works very well with C/C++. You’re not gonna want any C/C++ (or Fortran) for this tutorial, but if you need to learn more relating to this awesome aspect, then look into the next assets:

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There are various ideal and nicely-known Python tools for linear programming and blended-integer linear programming.

It’s really worth mentioning that just about all widely utilized linear programming and mixed-integer linear programming libraries are native to and published in Fortran or C or C++.

This is due to linear programming needs computationally intensive work with (generally big) matrices. These kinds of libraries are identified as solvers. The Python instruments are only wrappers throughout the solvers.

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