Package Insights
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
55
Popularity
62
Adoption
80
Community
35
How the maintenance status was determined
Last commit
93 days ago
Monthly downloads
12,075
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
12,075
Stars
1,089
Stars per 1k downloads
90.19
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
817
Month daily avg
402
Momentum
+102.9%
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100Python version support tiers
requires_python
>=3.10
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-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
108 days ago
Total releases
17
Releases/year
3.5
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
13
Monthly downloads
12,075
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
65
Issue Burden
8.3
per 1k stars
Discussions
66.1
per 1k stars
Fork Ratio
13.7%
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
997
Windows
5
macOS
4
Python Versions
3.10
84.6%
862
3.8
12.9%
131
3.11
1.7%
17
3.9
0.7%
7
3.12
0.2%
2
Top Countries
1.
US
886
US
2.
SG
134
SG
3.
GB
2
GB
4.
IT
2
IT
5.
CA
1
CA
6.
JP
1
JP
Dependencies
9
- joblib
- literate-dataclasses
- matplotlib
- numpy <2.0
- requests
- scikit-learn
- scipy
- torch >=2.4.0
- tqdm
45 optional dependencies
- black[dev]
- captum[integrations]
- cffconvert[dev]
- codespell[dev]
- coverage[dev]
- cvxpy[integrations]
- docutils[docs]
- h5py[datasets]
- hdf5storage[datasets]
- interrogate[dev]
- ipykernel[docs]
- ipykernel[demos]
- isort[dev]
- jupyter[demos]
- licenseheaders[dev]
- matplotlib[docs]
- nbconvert[docs]
- nbconvert[demos]
- nbsphinx[docs]
- openpyxl[datasets]
- pandas[integrations]
- pandas[docs]
- pandas[datasets]
- plotly[integrations]
- pydata-sphinx-theme[docs]
- pylint[dev]
- pytest[dev]
- pytest-benchmark[dev]
- pytest-sphinx[dev]
- pytest-timeout[dev]
- pytest-xdist[dev]
- scikit-image[integrations]
- scikit-learn[docs]
- seaborn[docs]
- seaborn[integrations]
- sphinx[docs]
- sphinx-autodoc-typehints[docs]
- sphinx-copybutton[docs]
- sphinx-design[docs]
- sphinx-gallery[docs]
- sphinx-tabs[docs]
- sphinx-togglebutton[docs]
- tables[datasets]
- toml[dev]
- yapf[dev]
Used By
3
Package Information
License
Apache-2.0
First Release
June 11, 2021
Last Release
3 months ago
Last Commit
3 months ago
Latest Version
0.6.0
Total Releases
17
Contributors
13
Open PRs
7
Archived
No
Author
file: AUTHORS.md
Python Versions
3
Wheels
py2
py3
Tracking Since
January 14, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh