  Direct Numerical Simulations (DNS) of the Navier Stokes equations is a
valuable research tool in fluid dynamics, but there are very few publicly
available codes and, due to heavy number crunching, codes are usually written
in low-level languages. In this work a \textasciitilde{}100 line standard
scientific Python DNS code is described that nearly matches the performance of
pure C for thousands of processors and billions of unknowns. With optimization
of a few routines in Cython, it is found to match the performance of a more or
less identical solver implemented from scratch in C++. Keys to the efficiency
of the solver are the mesh decomposition and three dimensional FFT routines,
implemented directly in Python using MPI, wrapped through MPI for Python, and a
serial FFT module (both numpy.fft or pyFFTW may be used). Two popular
decomposition strategies, slab and pencil, have been implemented and tested.
