PyPI Stats
fjwillemsen

autotuning-methodology

This software package accompanies the paper "A Methodology for Comparing Auto-Tuning Optimization Algorithms" (https://doi.org/10.1016/j.future.2024.05.021), making the guidelines in the methodology easy to apply.
PyPI GitHub
Downloads
Day
21
Week
112
Month
412
Stars
7
Forks
3
Issues
1
Version
1.1.0

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
30
Popularity
18
Adoption
26
Community
40
How the maintenance status was determined
Last commit
245 days ago
Monthly downloads
412
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
412
Stars
7
Stars per 1k downloads
16.99
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
16
Month daily avg
14
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
<4,>=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
MIT License
• 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
245 days ago
Total releases
8
Releases/year
2.7
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
2
Monthly downloads
412
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
14
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
66.7%
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

No OS data available

Python Versions

No Python version data available

Top Countries

1. CA CA
1
2. DE DE
1

Dependencies

9
12 optional dependencies

Used By

0
Not used by any tracked packages

Package Information

License
MIT License
First Release
June 2, 2023
Last Release
8 months ago
Last Commit
8 months ago
Latest Version
1.1.0
Total Releases
8
Contributors
2
Open PRs
1
Archived
No
Python Versions
3.10 3.11 3.12 3.13
Wheels
py3
Keywords
autotuning auto-tuning methodology scientific
Topics
auto-tuning methodology optimization-algorithms performance-comparison performance-metrics performance-optimization
Tracking Since
January 14, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links