  There are many packages in Python which allow one to perform real-time
processing on audio data. Unfortunately, due to the synchronous nature of the
language, there lacks a framework which allows for distributed parallel
processing of the data without requiring a large programming overhead and in
which the data acquisition is not blocked by subsequent processing operations.
This work improves on packages used for audio data collection with a
light-weight backend and a simple interface that allows for distributed
processing through a socket-based structure. This is intended for real-time
audio machine learning and data processing in Python with a quick deployment of
multiple parallel operations on the same data, allowing users to spend less
time debugging and more time developing.
