Visibility winner
scikit-learn/scikit-learn
67K stars
Use this as the long-horizon mindshare read, not as the final answer.
Freshness winner
scikit-learn/scikit-learn
Momentum not captured in this snapshot
Last commit Aug 13, 2026
Adoption winner
scikit-learn/scikit-learn
6.7M/week
pypi package signal
Data completeness
Comparison confidence
1/2 package links
0/2 repos have weekly momentum in the current snapshot.
Compare up to four repositories with comma-separated owner/repo names. GitStar keeps missing package or momentum data explicit instead of flattening it into a false zero.
scikit-learn/scikit-learn currently leads on long-horizon mindshare with the strongest star base in this comparison. scikit-learn/scikit-learn has the strongest linked package footprint in this group.
GitStar keeps cross-repository gaps visible. Missing package mappings or partial momentum data lower confidence, but they do not stop the page from showing a directional read.
scikit-learn/scikit-learn currently leads on long-horizon mindshare with the strongest star base in this comparison.
Stars are strongest at showing durable visibility, not direct production fit.
scikit-learn/scikit-learn has the strongest current movement signal in this set.
Recent movement is missing from the current cache, so freshness falls back to commit recency.
scikit-learn/scikit-learn has the strongest linked package footprint in this group.
pypi usage is a better production proxy than stars when it exists.
This comparison lives in the same data lane, so package usage and repo detail should carry more weight than raw stars alone.
Shared category overlap makes the comparison more decision-useful than a random popularity matchup.
HST-Bench evaluation dataset contains 753 agentic tasks along with the time taken by human annotators to solve each task. This dataset was collected as part of our ICML 2026 paper on Scaling Small Agents Through Strategy Auctions https//arxiv.org/pdf/2602.02751
scikit-learn: machine learning in Python