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The Python package fluidsim is introduced in this article as an extensibleframework for Computational Fluid Mechanics (CFD) solvers. It is developed as apart of FluidDyn project (Augier et al., 2018), an effort to promoteopen-source and open-science collaboration within fluid mechanics community andintended for both educational as well as research purposes. Solvers in fluidsimare scalable, High-Performance Computing (HPC) codes which are powered underthe hood by the rich, scientific Python ecosystem and the ApplicationProgramming Interfaces (API) provided by fluiddyn and fluidfft packages(Mohanan et al., 2018). The present article describes the design aspects offluidsim, viz. use of Python as the main language; focus on the ease of use,reuse and maintenance of the code without compromising performance. Theimplementation details including optimization methods, modular organization offeatures and object-oriented approach of using classes to implement solvers arealso briefly explained. Currently, fluidsim includes solvers for a variety ofphysical problems using different numerical methods (includingfinite-difference methods). However, this metapaper shall dwell only on theimplementation and performance of its pseudo-spectral solvers, in particularthe two- and three-dimensional Navier-Stokes solvers. We investigate theperformance and scalability of fluidsim in a state of the art HPC cluster.Three similar pseudo-spectral CFD codes based on Python (Dedalus, SpectralDNS)and Fortran (NS3D) are presented and qualitatively and quantitatively comparedto fluidsim. The source code is hosted at Bitbucket as a Mercurial repositorybitbucket.org/fluiddyn/fluidsim and the documentation generated using Sphinxcan be read online at fluidsim.readthedocs.io.

FluidSim: modular, object-oriented Python package for high-performance CFD simulations