PyRank

dscribe

A Python package for creating feature transformations in applications of machine learning to materials science.
PyPI
More links
Download Stats Documentation Source
Monthly downloads
224.8K
Weekly downloads
184.2K
GitHub stars
-

Downloads in the 30 and 7 days to October 10, 2026. Refreshed weekly.

Package Information

Latest Version
2.1.2
Requires Python
>=3.9
Licence
Apache License 2.0
Last Release
1 year ago
First Release
November 8, 2018
Total Releases
30
Python Versions
3 3.9 3.10 3.11 3.12 3.13
No reported malware or high/critical advisories · Details

The current version has no OSV.dev malware reports and no critical or high-severity vulnerabilities.

Package Insights

What's this?
Score based on PyPI data only - no linked source repository
N/A
Health Score
Not available
requires GitHub data
How the maintenance status was determined
Last release
383 days ago
Monthly downloads
224,750
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
224,750
Stars
Unknown
Stars per 1k downloads
—
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
No star data — can't compute stars-to-downloads ratio.
How download momentum is calculated
Week daily avg
26,307
Month daily avg
7,492
Momentum
+251.2%
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
More insights and metrics
Python version support tiers
requires_python
>=3.9
Cutting Edge
Minimum supported version is 3.14 or newer
Modern
Minimum supported version is 3.11 to 3.13
• Legacy
Supports 3.10 or older (or Python 2)
Unknown
No requires_python specified or unparseable
License categories
License
Apache License 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
383 days ago
Total releases
30
Releases/year
3.8
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
Unknown
Monthly downloads
224,750
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
Contributor count is missing — this usually indicates the package has no linked GitHub repository.
Engagement
0
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
-
contrib / forks
Stale Release
No
 
PR Velocity
-
 
Not all downloads include detailed metadata. Breakdowns reflect the subset that does.

Downloads by OS

Linux 69.7K
macOS 50
Windows 35

Python Versions

3.13
99.2% 69.1K
3.11
0.3% 234
3.12
0.3% 224
3.10
0.1% 70
3.14
0.1% 50

Top Countries

1. US US
70.0K
2. BE BE
222
3. RU RU
62
4. SG SG
20
5. CN CN
14
6. GB GB
10
7. IN IN
7
8. NL NL
6
9. CH CH
5
10. JP JP
5

Weekly Downloads

GitHub Stars

Dependencies

6
8 optional dependencies

Used By

27
View all 27 dependents

Repository details

Forks
-
Issues
-
Last Commit
-
Contributors
-
Open PRs
-
Archived
-

Data and sources

Tracking Since
September 26, 2026
Data Updated
October 11, 2026
Data Freshness
Fresh
Keywords
descriptor machine learning atomistic structure materials science
Sources and methodology