What is faust?

Faust is a Python library that helps you process continuous streams of data in real time. If your application receives a constant flood of events, like orders, clicks, or sensor readings, and you need to react to each one as it arrives, this tool lets you write that logic in plain Python. It was built at Robinhood to handle billions of events per day. The way it works is straightforward conceptually. You connect your app to a message broker (the only external infrastructure required is Kafka, which is a system that routes data between applications). Then you write Python functions that receive each incoming event and do whatever you need, print it, calculate a total, send an email, or call another service. Because these functions use Python's async features, they can juggle many operations without blocking. You can also define simple Python classes to describe what your data looks like, and the library handles serialization automatically. Beyond just processing events one at a time, the tool can also maintain state across your application, like a distributed database. You get "Tables" that behave like regular Python dictionaries but persist data between restarts and survive server crashes by keeping standby replicas on other machines. This makes it easy to track running counts, like how many clicks a URL got in the last hour, with rolling time windows that automatically expire old data. The main audience is developers building real-time data pipelines or event-driven services who already know Python and don't want to learn a separate domain-specific language. For example, a team processing financial orders could use it to update positions, trigger alerts, or feed analytics dashboards as trades stream in. It integrates with familiar Python libraries, so you can pull in NumPy, Flask, or SQLAlchemy within your stream processors. A notable tradeoff: it requires Python 3.6 or later and depends on Kafka, so it's not a lightweight choice for simple scripting. But for teams already in that ecosystem, it keeps everything in Python rather than forcing you into a new toolchain.