My name is Ask and I'm co-creator on this project, along with Vineet Goel.
This answer sums up why we wanted to use Python for this project: it's the most popular language for data science and people can learn it quickly.
Performance is not really a problem either, with Python 3 and asyncio we can process tens of thousands of events/s. I have seen 50k events/s, and there are still many optimizations that can be made.
That said, Faust is not just for data science. We use it to write backend services that serve WebSockets and HTTP from the same Faust worker instances that process the stream.
This answer sums up why we wanted to use Python for this project: it's the most popular language for data science and people can learn it quickly.
Performance is not really a problem either, with Python 3 and asyncio we can process tens of thousands of events/s. I have seen 50k events/s, and there are still many optimizations that can be made.
That said, Faust is not just for data science. We use it to write backend services that serve WebSockets and HTTP from the same Faust worker instances that process the stream.