Quansight Labs is an experiment for us in a way. One of our main aims is to channel more resources into community-driven PyData projects, to keep them healthy and accelerate their development. And do so in a way that projects themselves stay in charge.
This post explains one method we're starting to use for this. I'm writing it to be transparent with projects, the wider community and potential funders about what we're starting to do. As well as to explicitly solicit feedback on this method.
Community work ordersIf you talk to someone about supporting an open source project, in particular a well-known one that they rely on (e.g. NumPy, Jupyter, Pandas), they're often willing to listen and help. What you quickly learn though is that they want to know in some detail what will be done with the funds provided. This is true not only for companies, but also for individuals. In addition, companies will likely want a written agreement and some form of reporting about the progress of the work. To meet this
from Planet SciPy
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