MaintainerPulse

temporal prediction of dependency maintenance risk

httpcore encode/httpcore ▲ high risk

77%
no release in the next 12 months
67%
new issues will go unanswered (30 days)
100%
maintainer activity collapse within 12 months
13%
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%2019-112021-092023-082025-06high risk

Repository activity, last 36 months

pushes issues PyPI release
025502023-092024-082025-082026-09

What drives this score

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

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
httpx The next generation HTTP client. 0.76 12 36%
grpcio HTTP/2-based RPC framework 0.68 3 0%
httplib2 A comprehensive HTTP client library. 0.68 0 11%
urllib3 HTTP library with thread-safe connection pooling, file post, and more. 0.60 7 4%
niquests Niquests is a simple, yet elegant, HTTP library. It is a drop-in replacement for Requests, 0.56 0 1%

Signals at the latest snapshot

days since last release 495 releases, last 12mo 0
people pushing, last 12mo 0 bus factor (top pusher share) -
issues opened, last 12mo 1 30-day response rate 0%
stars accumulated 662 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).