PyPI Stats
mj-will

nessai

nessai: Nested Sampling with Artificial Intelligence
PyPI GitHub
Downloads
Day
204
Week
1.9K
Month
10.8K
Stars
49
Forks
4
Issues
2
Version
0.15.2

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
80
Popularity
30
Adoption
40
Community
10
How the maintenance status was determined
Last commit
75 days ago
Monthly downloads
10,789
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
10,789
Stars
49
Stars per 1k downloads
4.54
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
276
Month daily avg
360
Momentum
-23.4%
((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
75 days ago
Total releases
36
Releases/year
6.9
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
3
Monthly downloads
10,789
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
30
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
75.0%
contrib / forks
Stale Release
No
 
PR Velocity
Active
 

Weekly Downloads

GitHub Stars

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

Downloads by OS

Linux 12
macOS 2

Python Versions

3.12
50.0% 7
3.14
42.9% 6
3.9
7.1% 1

Top Countries

1. US US
16
2. SG SG
3
3. TW TW
2
4. CA CA
1

Dependencies

9
20 optional dependencies

Used By

8

Package Information

License
MIT
First Release
February 18, 2021
Last Release
2 months ago
Last Commit
2 months ago
Latest Version
0.15.2
Total Releases
36
Contributors
3
Open PRs
3
Archived
No
Python Versions
3
Wheels
py3
Keywords
nested sampling normalizing flows machine learning
Topics
pytorch normalizing-flows nested-sampling python bayesian-inference bilby machine-learning
Tracking Since
January 6, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links