Maintaining Fortran in Python in Perpetuity

This talk covers recent advances to the f2py project, including preliminary derived type support, better documentation, and restructured design to enhance new contributor experiences. Additionally, we will discuss the structure and role of interoperability libraries and how modern Fortran intends to harmoniously and symbiotically evolve within the Python ecosystem in the context of Fortran-Lang, the np.distutils deprecation, newer compute devices and the ever changing landscape of high performance programming. More details at: https://rgoswami.me/posts/scipycon-2022-metaFortran forms the computational bedrock of the scientific community. Despite the prevalence of the pack libraries (LAPACK, PROPACK etc.) within scipy and the fact that f2py has been an integral part of the numpy ecosystem for decades now, it is seldom brought up. In particular, newer, younger programming languages and projects are consistently brought up as possible contenders to the crown of numerical computing within the Scientific Python ecosystem. Being such a foundational project has a unique set of maintainability challenges as well. Hyrum's law rings especially true for f2py, scientific projects, both public and private, depend heavily on every aspect of the exposed API. A boon for scientific programming from the very beginning, f2py has enabled high performance computing without in-depth understanding of either the python-C API or the Fortran language itself. Even as f2py reinvents itself for modern Fortran constructs however, backwards compatibility requirements remain (e.g. scipy lags by two versions). From a brief historical overview of the scientific python ecosystem and interoperability issues we will move through the sustainability efforts through the years. We will cover changes in f2py, both planned and implemented, including the migration towards the Python-C Limited API, the newer argparse front-end, moving away from np.distutils, restructuring and reducing reliance on features implemented by the NumPy-C API, and supporting newer Fortran standards (with derived types being the poster child of missing Modern Fortran features). The talk will also briefly cover the code-generation and fortranobject constructs. The focus is not meant to be the internals so much as a 50-foot view of each constituent part of f2py and its long term viability. Part of the discussion will revolve around synergies with existing projects, both within the scientific Python ecosystem (scipy), and Fortran-Lang (LFortran), and by planning to involve younger developers via GSoC. Lastly, we will discuss how the FOSS community stepped up to support f2py and how we intend to continue to carry modern Fortran as a corner stone of the scientific python ecosystem for many years to come in no small part by providing a common set of interoperability standards in the form of NEPs (NumPy Enhancement Proposals)