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Symbolic Computation: The authors used symbolic algebra (SymPy) to derive the discrete equations. This reduces human error in coding complex fluid dynamics equations.
Just-In-Time (JIT) Compilation: By using tools like JAX or Numba, Python code can be compiled at runtime to run at speeds comparable to Fortran.
Accessibility: It lowers the barrier to entry for students and researchers who know Python but not Fortran.