We present QBAF-Py, a library for explainable quantitative bipolar argumentation. The core of the library is written in C, whereas the API is exposed in Python. The idea behind QBAF-Py is to use a fast language for computation and a wide-spread language for the API, in order to facilitate re-use, e.g., in data science and machine learning contexts. QBAF-Py's focus is on solving acyclic quantitative bipolar argumentation frameworks and explaining inferences drawn from them.