  The Python package fluidfft provides a common Python API for performing Fast
Fourier Transforms (FFT) in sequential, in parallel and on GPU with different
FFT libraries (FFTW, P3DFFT, PFFT, cuFFT). fluidfft is a comprehensive FFT
framework which allows Python users to easily and efficiently perform FFT and
the associated tasks, such as as computing linear operators and energy spectra.
We describe the architecture of the package composed of C++ and Cython FFT
classes, Python "operator" classes and Pythran functions. The package supplies
utilities to easily test itself and benchmark the different FFT solutions for a
particular case and on a particular machine. We present a performance scaling
analysis on three different computing clusters and a microbenchmark showing
that fluidfft is an interesting solution to write efficient Python applications
using FFT.
