PyPI Stats
mljar

mljar-supervised

Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
PyPI GitHub
Downloads
Day
360
Week
1.8K
Month
9.7K
Stars
3.3K
Forks
432
Issues
145
Version
1.2.2

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
80
Popularity
75
Adoption
39
Community
50
How the maintenance status was determined
Last commit
41 days ago
Monthly downloads
9,679
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
9,679
Stars
3,255
Stars per 1k downloads
336.30
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
258
Month daily avg
323
Momentum
-20.0%
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
Python version support tiers
requires_python
>=3.9
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
MIT
• 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
41 days ago
Total releases
104
Releases/year
14.7
• 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
25
Monthly downloads
9,679
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
66
 
Issue Burden
44.5
per 1k stars
Discussions
8.3
per 1k stars
Fork Ratio
5.8%
contrib / forks
Stale Release
No
 
PR Velocity
Quiet
 

Weekly Downloads

GitHub Stars

Not all downloads include detailed metadata. Breakdowns reflect the subset that does.

Downloads by OS

Linux 182
Windows 10

Python Versions

3.11
38.0% 71
3.12
29.4% 55
3.10
28.9% 54
3.14
3.2% 6
3.7
0.5% 1

Top Countries

1. US US
102
2. NL NL
71
3. CH CH
6
4. GB GB
6
5. DK DK
5
6. SG SG
4
7. CN CN
2
8. KR KR
2
9. RU RU
2
10. CA CA
1

Dependencies

18

Used By

0
Not used by any tracked packages

Package Information

License
MIT
First Release
April 9, 2019
Last Release
1 month ago
Last Commit
1 month ago
Latest Version
1.2.2
Total Releases
104
Contributors
25
Open PRs
4
Archived
No
Author
MLJAR, Sp. z o.o.
Python Versions
3.9 3.10 3.11 3.12
Wheels
py3
Keywords
automated machine learning automl machine learning data science data mining mljar random forest decision tree xgboost lightgbm catboost neural network extra trees linear model features selection features engineering
Topics
automl machine-learning mljar data-science scikit-learn hyperparameter-optimization feature-engineering xgboost random-forest neural-network lightgbm catboost ensemble hyper-parameters decision-tree automated-machine-learning automl-api automl-python
Tracking Since
January 6, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links