  Governments are increasingly funding open source software (OSS) development
to support software security, digital sovereignty, and national competitiveness
in science and innovation, amongst others. However, little is known about how
OSS developers evaluate the relative benefits and drawbacks of governmental
funding for OSS. This study explores this question through a case study on
scikit-learn, a Python library for machine learning, funded by public research
grants, commercial sponsorship, micro-donations, and a 32 euro million grant
announced in France's artificial intelligence strategy. Through 25 interviews
with scikit-learn's maintainers and funders, this study makes two key
contributions. First, it contributes empirical findings about the benefits and
drawbacks of public and private funding in an impactful OSS project, and the
governance protocols employed by the maintainers to balance the diverse
interests of their community and funders. Second, it offers practical lessons
on funding for OSS developers, governments, and companies based on the
experience of scikit-learn. The paper concludes with key recommendations for
practitioners and future research directions.
