PyPI Stats
capitalone

fma-django

The Federated Model Aggregation (FMA) Service is a collection of installable python components that make up the generic workflow/infrastructure needed for federated learning.
PyPI GitHub

Shared Repository

This package shares its GitHub repository (capitalone/federated-model-aggregation) with 2 other packages. Stars, forks, and other GitHub metrics reflect the entire repository.
Downloads
Day
5
Week
16
Month
70
Stars
34
Forks
11
Issues
1
Version
0.0.1

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
4
Popularity
32
Adoption
18
Community
50
How the maintenance status was determined
Last commit
212 days ago
Monthly downloads
70
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
Repository is archived on GitHub — no further commits expected.
How the popularity category was determined
Monthly downloads
70
Stars
34
Stars per 1k downloads
485.71
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
2
Month daily avg
2
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
>=3.8
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 License, Version 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
1155 days ago
Total releases
2
Releases/year
0.6
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
16
Monthly downloads
70
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
46
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
145.5%
contrib / forks
Stale Release
943d
 
PR Velocity
Quiet
 

Weekly Downloads

GitHub Stars

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

Downloads by OS

No OS data available

Python Versions

No Python version data available

Top Countries

1. CA CA
1

Dependencies

8
4 optional dependencies

Used By

0
Not used by any tracked packages

Package Information

License
Apache License, Version 2.0
First Release
February 22, 2023
Last Release
3 years ago
Last Commit
7 months ago
Latest Version
0.0.1
Total Releases
2
Contributors
16
Open PRs
0
Archived
Yes
Author
Kenny Bean, Tyler Farnan, Taylor Turner, Michael Davis, Jeremy Goodsitt
Python Versions
3
Keywords
Federated Learning
Topics
distributed-systems federated-learning machine-learning python edge-compute
Tracking Since
January 14, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links