Many disciplines in science and engineering are focused on the perception and production of sounds. Applications range from signal processing algorithms to music information retrieval and speech analysis, and even audiological research. All of these disciplines require the playback and recording, and storage and retrieval of audio data. As a data structure, audio data is simple to work with: it consists of long arrays of air pressure measurements at a sample rate of several thousands per second. This kind of data is perfectly suited for Numpy arrays, and Numpy, Scipy, and Matplotlib contain a host of functionality for manipulating and analyzing audio data. Yet, actually playing and recording audio data in Python is still a major issue. While libraries exist for playback and recording, the quality of the implementations vary greatly between operating systems and audio APIs. In particular, academic signal processing often requires low-latency, real-time, multi-channel interaction with arbitrary sound cards, which can be difficult for existing libraries to support. Reading and writing audio files from Python is similarly difficult. Again, Python libraries do exist, but consistent, high-performance access to the vast variety of existing audio file formats is still a challenge. This talk presents an overview of the history and current landscape of audio libraries available for Python. Additionally, it highlights our ongoing work on the libraries SoundFile and Python-Audio, which bring high-performance reading and writing of audio files, and real-time playback and recording of audio data to Python.