The code-generation facilities in SymPy are already in active use in the research community. There are, however, still many exciting opportunities for further improvements. As a CAS, SymPy has access to far more information than a compiler processing typical source code in languages such C/C++/Fortran. SymPy uses arbitrary precision arithmetics which means that the size and precision of numbers represented are only limited by the amount of memory the computer has access too. However, operations with arbitrary precision are inherently slow, which is why high performance code relies on floating-point arithmetic (which has dedicated hardware in modern CPUs). Therefore, any code generation for a programming language which maps mathematical expressions to finite precision floating point instructions, would benefit greatly if that code-generation was made in such a way to minimize loss of significance, risk of under-/overflow etc.