PyRank
vignesh2027

datamend

✦ Why datamend? ✦ Real-world data is never clean. Nulls sneak in. Distributions shift. Models fail silently on corrupted inputs. datamend is the single library that catches, fixes, validates, monitors, and traces every data quality issue — automatically — so your ML pipeline never breaks from bad data again.
PyPI GitHub
Downloads
Day
30
Week
244
Month
974
Stars
1
Forks
0
Issues
0
Version
1.1.1

Package Insights

What's this?
Score breakdown - each component scores 0-100, weighted by percentage
Maintenance
70
Popularity
4
Adoption
29
Community
0
How the maintenance status was determined
Last commit
7 days ago
Monthly downloads
974
• 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
974
Stars
1
Stars per 1k downloads
1.03
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
Needs at least 1,000 monthly downloads to classify popularity.
How download momentum is calculated
Week daily avg
35
Month daily avg
32
Momentum
—
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
Momentum not reported for packages with < 5,000 monthly downloads — percentages are noisy at low volume.
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
7 days ago
Total releases
3
Releases/year
136.9
• 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
1
Monthly downloads
974
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
5
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
-
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

macOS 6
Linux 2

Python Versions

3.11
100.0% 8

Top Countries

1. US US
30
2. JP JP
20
3. SG SG
16
4. FR FR
8
5. GB GB
8
6. KR KR
6
7. SE SE
4
8. NO NO
2
9. RU RU
2

Dependencies

7
28 optional dependencies

Used By

0
Not used by any tracked packages

GitHub Topics

Tags from the package's GitHub repository describing what it does.

Package Information

License
MIT
First Release
May 14, 2026
Last Release
1 week ago
Last Commit
1 week ago
Latest Version
1.1.1
Total Releases
3
Contributors
1
Open PRs
0
Archived
No
Python Versions
3 3.9 3.10 3.11 3.12 3.13
Wheels
py3
Keywords
data-quality data-cleaning drift-detection data-validation machine-learning mlops data-science pandas autorepair data-contracts feature-drift model-debugging
Tracking Since
May 14, 2026
Data Updated
May 17, 2026
Data Freshness
Fresh

Links