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scikit-learn
Active
Libraries & SDKs Latest Version: 1.9.0 Latest Release: Jun 2, 2026
scikit-learn is the standard Python machine learning library for classical ML (classification, regression, clustering). Only the latest minor receives fixes; dependency/Python deprecation follows SPEC 0 (~3 years). Latest 1.9 and 1.7-1.8 require Python 3.10+.
Versions
9
Latest Version
1.9.0
Active Support
1
EOL
8
Lifecycle Timeline
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1.9
1.9
1.8
1.8
1.7
1.7
1.6
1.6
1.5
1.5
1.4
1.4
1.3
1.3
1.2
1.2
1.1
1.1
Active SupportSecurity SupportEOL
Versions
| Release | Release Date | Active Support | EOL | Latest Version | LTS | Status |
|---|---|---|---|---|---|---|
| 1.9 | Jun 2, 2026 | Yes | No | 1.9.0 | No | Active |
| 1.8 | Dec 10, 2025 | No | Yes | 1.8.0 | No | EOL |
| 1.7 | Jun 5, 2025 | No | Yes | 1.7.2 | No | EOL |
| 1.6 | Dec 9, 2024 | No | Yes | 1.6.1 | No | EOL |
| 1.5 | May 21, 2024 | No | Yes | 1.5.2 | No | EOL |
| 1.4 | Jan 18, 2024 | No | Yes | 1.4.2 | No | EOL |
| 1.3 | Jun 30, 2023 | No | Yes | 1.3.2 | No | EOL |
| 1.2 | Dec 8, 2022 | No | Yes | 1.2.2 | No | EOL |
| 1.1 | May 12, 2022 | No | Yes | 1.1.3 | No | EOL |
Frequently Asked Questions
Which versions of scikit-learn have reached end of life?
The following scikit-learn versions have reached end of life and no longer receive security updates: 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1. It is recommended to upgrade to a supported version.
Is it safe to continue using scikit-learn 1.8?
scikit-learn 1.8 has reached end of life and no longer receives security patches or bug fixes. Continuing to use it may expose your systems to known vulnerabilities. We strongly recommend upgrading to a supported version.
What is the latest version of scikit-learn?
The latest version of scikit-learn is 1.9.0, released in the 1.9 release cycle.
How many versions of scikit-learn are currently supported?
scikit-learn currently has 1 actively supported version(s): 1.9.
When does scikit-learn 1.9 reach end of life?
scikit-learn 1.9 does not have a specific end-of-life date announced yet.
What should I do when scikit-learn reaches end of life?
When a scikit-learn version reaches end of life, you should: 1) Plan your migration to a supported version as soon as possible. 2) Review the release notes for breaking changes. 3) Test your applications thoroughly in a staging environment. 4) Update your dependencies to ensure compatibility with the new version.