MaintainerPulse

temporal prediction of dependency maintenance risk

audiofile audeering/audiofile ● elevated

49%
no release in the next 12 months
50%
new issues will go unanswered (30 days)
100%
maintainer activity collapse within 12 months
32%
chance of a release within 12 months (survival model)

Model risk over time

calibrated P(no release next 12mo) at each historical monthly snapshot
0%50%100%2019-102021-092023-072025-06high risk

Repository activity, last 36 months

pushes issues PyPI release
025502023-102024-072025-102026-05

What drives this score

TreeSHAP contributions; raises risk / lowers risk
releases, all time-days since last release-events, all time+releases, last 12mo+

Survival curve

P(still no release) m months ahead, discrete-time hazard model
0%50%100%036912

What if? — poke the model

drag a signal and the deployed models rescore this package live (implied signals move together — two years without a release also zeroes "releases, last 12mo"). The needle tracks the activity-collapse model, a logistic regression: monotone by construction, so it responds smoothly to counterfactuals where the tree models step.

maintainer activity collapse, 12mo

In plain words

Maintained alternatives

similar packages with low predicted risk; ranked by summary similarity blended with shared-dependents overlap, validated against known migrations
packagewhat it issimilarity shared dependentsits 12mo risk
fastavro Fast read/write of AVRO files 0.58 0 29%
mediafile A simple, cross-format library for reading and writing media file metadata. 0.54 0 21%
torchaudio An audio package for PyTorch 0.48 0 13%
yt-dlp A feature-rich command-line audio/video downloader 0.48 0 1%
anycrc The fastest general Python CRC Library 0.47 0 21%

Signals at the latest snapshot

days since last release 104 releases, last 12mo 2
people pushing, last 12mo 1 bus factor (top pusher share) 100%
issues opened, last 12mo 1 30-day response rate 0%
stars accumulated 38 open vulns without fix 0

Probabilities are isotonic-calibrated on a held-out validation year and evaluated on future snapshots the models never saw (PR-AUC 0.894, precision@50 = 1.00 on the headline target).