Data stream learning is an artificial intelligence method of extracting knowledge from continuous, rapid and evolving “streams” of data. Our talk presents our new Python library, called CapyMOA, to close the gap between pioneering research and accessible tooling by providing a Python API that tightly integrates MOA (Java data stream mining), PyTorch (hardware accelerated deep learning), and sci-kit-learn (machine learning). Despite these advanced topics, the talk is intended for a broad audience. It will introduce the discipline of data streams for a wide audience, look at some practical examples, and discuss the technical novelty in constructing the Python CapyMOA project.