The field of scientific computing requires not only the topological and geometrical outlines of the simulation domain, but also requires the quick and easy specification of quantities within these domains to set both parameters and boundary conditions. Python has enjoyed a growing community of developers and users due to the easy availability of several different programming paradigms within a single language. Furthermore, its syntax and semantics are, by design, simple and exhibit many of the required features. However, Python lacks the essential feature of consistent and efficient traversal of simulation domains, as well as quantity storage mechanisms.
It is for this reason that the Typhoon Python module has been developed. This module makes the high performance traversal and quantity storage mechanisms of the Generic Scientific Simulation Environment (GSSE), which was also developed at this institute, available to Python.
Due to the overhead of the interpreter, Python modules need to be based on highly optimized libraries written in a variety of compiled languages, which are made available to Python via a wrapping layer, in order achieve acceptable performance. The multi-paradigmatic nature of both C++ and Python makes combinations of these two languages very appealing. Not only does C++ offer several paradigms concurrently, it also offers a high degree of run-time efficiency. However, the great multitude of features and possibilities offered by C++ along with its strong typing mechanisms are often perceived as obstacles to the rapid implementations of prototypes, especially by beginners to programming. On the other hand, Python has become known as a language which is easy to learn.
By making the topological traversal and quantity storage mechanisms available to Python, the ease of use and rapid prototyping are greatly facilitated.