MaintainerPulse

temporal prediction of dependency maintenance risk

The dependency network, colored by risk

Every node is a PyPI package in our universe with at least one dependency link; size is how many other packages depend on it, color is the calibrated probability of shipping no release in the next 12 months. Drag to pan, scroll to zoom, hover for details, click to open a package.

<40% 40–70% 70–90% ≥90% not scored

Systemic risk: high-risk packages others depend on

Risk ≥ 70% and at least 3 dependents inside the universe. These are the quiet single points of failure.

packagerepodependents risk
aiofiles Tinche/aiofiles 34 77% ● high
toml uiri/toml 34 92% ▲ critical
pycryptodome Legrandin/pycryptodome 29 77% ● high
defusedxml tiran/defusedxml 28 84% ● high
requests-toolbelt requests/toolbelt 23 77% ● high
backoff litl/backoff 18 86% ● high
mypy-extensions python/mypy_extensions 17 77% ● high
requests-mock jamielennox/requests-mock 17 82% ● high
parameterized wolever/parameterized 17 86% ● high
appdirs ActiveState/appdirs 16 77% ● high
pytest-runner pytest-dev/pytest-runner 16 72% ● high
httpcore encode/httpcore 14 72% ● high
future PythonCharmers/python-future 13 86% ● high
nest-asyncio erdewit/nest_asyncio 12 92% ▲ critical
xlsxwriter jmcnamara/XlsxWriter 11 77% ● high
pysocks Anorov/PySocks 11 92% ▲ critical
bump2version c4urself/bump2version 10 92% ▲ critical
webencodings SimonSapin/python-webencodings 10 98% ▲ critical
deprecation briancurtin/deprecation 10 98% ▲ critical
cached-property pydanny/cached-property 9 84% ● high