An increasing number of devices and applications are producing vast amounts of data in real time. This can include measurements, sensor readings, and performance data. Making this data useful often requires that we analyse and use the data in real time but this requires techniques to aggregate, filter, and smooth the data. Drawing on simple and well-tested techniques from mathematics and engineering allows us to solve these problems quickly and efficiently. This talk will describe how Python can be used to develop powerful capabilities for working with real-time data streams and provide simple examples you can start using yourself.