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As the overlap between traditional computational mechanics and machinelearning grows, there is an increasing demand for straight-forward approachesto interface Python-based procedures with C++-based OpenFOAM. This articleintroduces one such general methodology, allowing the execution of Python codedirectly within an OpenFOAM solver without the need for Python codetranslation. The proposed approach is based on the lightweight librarypybind11, where OpenFOAM data is transferred to an embedded Python interpreterfor manipulation, and results are returned as needed. Following a review ofrelated approaches, the article describes the approach, with a particular focuson data transfer between Python and OpenFOAM, executing Python scripts andfunctions, and practical details about the implementation in OpenFOAM. Threecomplementary test cases are presented to highlight the functionality anddemonstrate the effect of different data transfer approaches: a Python-basedvelocity profile boundary condition; a Python-based solver for prototyping; anda machine learning mechanical constitutive law class for solids4foam whichperforms field calculations.

A general approach for running Python codes in OpenFOAM using an embedded pybind11 Python interpreter