No known security advisories.
The current version has no OSV.dev malware reports and no critical or high-severity vulnerabilities.
autogluon has 226K monthly downloads and 11K GitHub stars. Version 1.5.0 supports Python <3.14,>=3.10, first published in 2019.
It is actively maintained under a permissive license, last released in Dec 2025.
It is built on top of autogluon-core, autogluon-features and autogluon-multimodal. It is used by 17 tracked packages, including arsa-ml, adi-ml-toolkit and saddle-ml.
GitHub topics include automl, machine-learning and data-science.
Package Insights
Package Risks
- No releases in 194 days despite active commits
Score breakdown - each component scores 0-100, weighted by percentage
Maintenance
100
Popularity
86
Adoption
63
Community
80
Provenance
0
How the maintenance status was determined
Last commit
4 days ago
Monthly downloads
226,035
•
Active
Activity within 30 days
Stable
Activity within 31-180 days
Minimal
Activity within 181-365 days, or no activity data
At Risk
No activity for > 365 days, but > 10,000 monthly downloads
Archived
Repository flagged as archived on GitHub
How the popularity category was determined
Monthly downloads
226,035
Stars
10,517
Stars per 1k downloads
46.53
Industry Standard
> 10,000,000 monthly downloads
Hidden Gem
< 0.5 stars per 1k downloads and > 100,000 monthly downloads
•
Community Favorite
> 5 stars per 1k downloads
Rising Star
Balanced ratio of stars to downloads
Unknown
Fewer than 1,000 monthly downloads, or no star data
How download momentum is calculated
Week daily avg
6,974
Month daily avg
7,534
Momentum
-7.4%
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100Python version support tiers
requires_python
<3.14,>=3.10
Cutting Edge
Minimum supported version is 3.12 or newer
•
Modern
Minimum supported version is 3.9, 3.10, or 3.11
Legacy
Supports 3.8 or older (or Python 2)
Unknown
No requires_python specified or unparseable
License categories
License
Apache-2.0
•
Permissive
MIT, Apache, BSD, ISC, Unlicense, CC0, etc.
Copyleft
GPL, LGPL, AGPL, MPL, EPL, etc.
Proprietary
Commercial, all rights reserved, custom EULAs
Unknown
No license specified, or none of the above match
How the release cadence was determined
Last release
199 days ago
Total releases
2,228
Releases/year
338.3
•
Rapid
Last release within 365 days and > 12 releases/year
Regular
Last release within 365 days
Slow
Last release 366-730 days ago
Stalled
Last release > 730 days ago, or no releases
Unknown
No usable release date available
How contributor risk was determined
Contributors
159
Monthly downloads
226,035
High Load
≤ 2 contributors and ≥ 50,000 monthly downloads
Moderate Load
< 10 contributors and ≥ 500,000 monthly downloads
Low Load
< 25 contributors and ≥ 5,000,000 monthly downloads, or sole maintainer with ≥ 10,000 monthly downloads
•
Balanced
Enough contributors for the package's popularity
Unknown
No contributor data available
Engagement
86
Issue Burden
35.6
per 1k stars
Discussions
50.0
per 1k stars
Fork Ratio
13.6%
contrib / forks
Stale Release
194d
PR Velocity
Quiet
Weekly Downloads
GitHub Stars
Not all downloads include detailed metadata. Breakdowns reflect the subset that does.
Downloads by OS
Windows
2.3K
Linux
1.5K
macOS
47
Python Versions
3.12
74.3%
2.8K
3.11
15.2%
567
3.13
5.5%
206
3.10
3.2%
119
3.9
1.8%
68
Top Countries
1.
CN
4.5K
CN
2.
IN
4.5K
IN
3.
JP
2.3K
JP
4.
US
1.5K
US
5.
NL
258
NL
6.
DE
92
DE
7.
GB
62
GB
8.
SG
56
SG
9.
HK
33
HK
10.
RU
31
RU
Dependencies
5
- autogluon-core ==1.5.0
- autogluon-features ==1.5.0
- autogluon-multimodal ==1.5.0
- autogluon-tabular ==1.5.0
- autogluon-timeseries ==1.5.0
1 optional dependencies
- autogluon-tabular[tabarena]
GitHub Topics
Tags from the package's GitHub repository describing what it does.
Package Information
License
Apache-2.0
First Release
December 7, 2019
Last Release
6 months ago
Last Commit
5 days ago
Latest Version
1.5.0
Total Releases
2,228
Contributors
159
Open PRs
22
Archived
No
Author
AutoGluon Community
Python Versions
3
3.10
3.11
3.12
3.13
Wheels
py3
Tracking Since
January 6, 2026
Data Updated
July 5, 2026
Data Freshness
Fresh