arXiv:2611.06947v1 Announce Type: new Abstract: Developers who upgrade a Python audio library need to know what changed in the code they import and whether the release notes say so. Release notes and breaking changes have been mined for general software, but the module structure of audio libraries and its documentation have not been studied together. We mine 56 audio repositories used in machine learning workflows: the import graph of 49 packages at 1,395 releases, joined to 20,864 release-note and changelog entries, labeled by three open-weight language models and checked against two human coders. We find that (1) the set of a package's top-level modules is unchanged in 86.1% of consecutive release pairs, while the set of module files is unchanged in 61.4%. (2) A major increment changes the top level 5.2 times as often as another increment, and major and 0.x minor increments together account for 48.7% of the observed changes. (3) When a release removes modules, its notes name 8.9% of the removal units under a lexical match, an estimated 4.3% after a hand check of the matches. (4) Longer notes are more likely to contain an entry labeled as structural, and within each length band this proportion is also higher for releases with module removals. We intend to release the aligned dataset and the pipeline