Comparison
auto-sklearn vs pycaret
Verdict
Pick auto-sklearn if auto-sklearn is an automated machine learning toolkit designed to automate hyperparameter optimization and function seamlessly with scikit-learn workflows; pick pycaret if pyCaret is an open-source low-code AutoML platform with a dual license structure and support for various ML tasks like classification, clustering, and anomaly detection.
Markdown twin · auto-sklearn alternatives · pycaret alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | auto-sklearn | pycaret |
|---|---|---|
| Maintenance | Steady (35d since push) As of 2w · github_public_v1 | Active (12d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- auto-sklearn
- Automated Machine Learning with scikit-learn
- pycaret
- Open-source low-code AutoML platform for Python
Stars
- auto-sklearn
- 8.1k
- pycaret
- 9.8k
Forks
- auto-sklearn
- 1.3k
- pycaret
- 1.9k
Open issues
- auto-sklearn
- 209
- pycaret
- 32
Language
- auto-sklearn
- Python
- pycaret
- Python
Adopt for
- auto-sklearn
- auto-sklearn is an automated machine learning toolkit designed to automate hyperparameter optimization and function seamlessly with scikit-learn workflows.
- pycaret
- PyCaret is an open-source low-code AutoML platform with a dual license structure and support for various ML tasks like classification, clustering, and anomaly detection.
Persona
- auto-sklearn
- -
- pycaret
- -
Runtime
- auto-sklearn
- -
- pycaret
- -
License
- auto-sklearn
- BSD-3-Clause
- pycaret
- Other
Last pushed
- auto-sklearn
- Jun 29, 2026
- pycaret
- Jul 23, 2026
Categories
- auto-sklearn
- Model Training
- pycaret
- Model Training
Trust and health
Maintenance
- auto-sklearn
- Steady (60%)
- pycaret
- Active (82%)
Days since push
- auto-sklearn
- 35d
- pycaret
- 12d
Open issues (now)
- auto-sklearn
- 209
- pycaret
- 32
OSV dependency advisories
- auto-sklearn
- Published findings
- pycaret
- No lockfile (source not queried)
Full report
- auto-sklearn
- Trust report
- pycaret
- Trust report
Shared compatibility
- Python · auto-sklearn: Python runtime · pycaret: Python runtime
Choose auto-sklearn if…
- License: auto-sklearn is BSD-3-Clause, pycaret is Other.
- Tags unique to auto-sklearn: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, hyperparameter-search.
- auto-sklearn ships Docker support for self-hosted deployment.
- When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
When NOT to use auto-sklearn
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers.
- In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
Choose pycaret if…
- License: pycaret is Other, auto-sklearn is BSD-3-Clause.
- Tags unique to pycaret: anomaly-detection, classification, clustering, data-science.
- You need to implement end-to-end machine learning pipelines using Python without diving deep into code complexity
When NOT to use pycaret
- Looking for pure open-source contributions as the control plane is BUSL-1.1 licensed until 2027
- You prioritize a fully code-driven custom ML pipeline over a low-code and automated approach
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/auto-sklearn) · observed Aug 4, 2026
- GitHub forks (automl/auto-sklearn) · observed Aug 4, 2026
- Last push (automl/auto-sklearn) · observed Jun 29, 2026
- License file (BSD-3-Clause) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (pycaret/pycaret) · observed Aug 4, 2026
- GitHub forks (pycaret/pycaret) · observed Aug 4, 2026
- Last push (pycaret/pycaret) · observed Jul 23, 2026
- License file (Other) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: auto-sklearn 8.1k · pycaret 9.8k (synced Aug 4, 2026).
Common questions
- What is the difference between auto-sklearn and pycaret?
- auto-sklearn: Automated Machine Learning with scikit-learn. pycaret: Open-source low-code AutoML platform for Python. See the comparison table for live GitHub stats and shared categories.
- When should I choose auto-sklearn over pycaret?
- Choose auto-sklearn over pycaret when License: auto-sklearn is BSD-3-Clause, pycaret is Other; Tags unique to auto-sklearn: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, hyperparameter-search; auto-sklearn ships Docker support for self-hosted deployment; When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
- When should I choose pycaret over auto-sklearn?
- Choose pycaret over auto-sklearn when License: pycaret is Other, auto-sklearn is BSD-3-Clause; Tags unique to pycaret: anomaly-detection, classification, clustering, data-science; You need to implement end-to-end machine learning pipelines using Python without diving deep into code complexity.
- When should I avoid auto-sklearn?
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers. In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
- When should I avoid pycaret?
- Looking for pure open-source contributions as the control plane is BUSL-1.1 licensed until 2027 You prioritize a fully code-driven custom ML pipeline over a low-code and automated approach
- Is auto-sklearn or pycaret more popular on GitHub?
- pycaret has more GitHub stars (9,831 vs 8,127). Stars measure visibility, not whether either tool fits your constraints.
- Are auto-sklearn and pycaret open source?
- Yes - both are open-source projects on GitHub (auto-sklearn: BSD-3-Clause, pycaret: Other).
- Where can I find alternatives to auto-sklearn or pycaret?
- GraphCanon lists graph-backed alternatives at auto-sklearn alternatives and pycaret alternatives (auto-sklearn markdown twin, pycaret markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, auto-sklearn or pycaret?
- auto-sklearn: Steady. pycaret: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for auto-sklearn and pycaret?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: auto-sklearn trust report; pycaret trust report.