← The openness index

classic-ml · Openness profile

scikit-learn

scikit-learn developers · snapshot 2026-11-07

Machine learning in Python

Tier 5 Fully open / reproducible

What the publisher claims: open source

The one-liner: The default Python ML library, permissively licensed and fully inspectable.

The six questions

A AccessScore 3 of 3

Full source and wheels are downloadable.

P PermissionScore 3 of 3

BSD 3-Clause.

D DeploymentScore 3 of 3

Runs on any supported platform with no proprietary runtime.

T TransparencyScore 3 of 3

Estimator definitions, objectives and evaluation procedures are public, and the data is the user's own.

R ReproducibilityScore 3 of 3

A skilled group can rebuild equivalent implementations from the published algorithm and code.

G Governance & ParticipationScore 3 of 3

Community-governed open source with public governance documents, core-team elections, and decades of merged outside contributions.

License

BSD 3-Clause OSI-approved — license source ↗

What is actually released

Why it matters

A decade of accumulated practice sits in a repository anyone can read and modify, the opposite of an API-only frontier model.

Sources

Derived from the openness dataset behind But Is It Open? — snapshot 2026-11-07 ↗. Scores are qualitative readings of the cited evidence, not verdicts; tier measures openness, not intelligence.

← The openness indexJoin the newsletter ↗