ggym

GeneticsGym: benchmark, compare and decompose missense variant effect predictors on human genetic datasets.

This is a placeholder release. The package will be published together with the accompanying manuscript; this version contains no code.

Metadata

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for ggym 0.0.1
File	Size	Uploaded
ggym-0.0.1.tar.gz	1.3 kB	Sep 30, 2026	Details

Table of built distributions (wheels) for ggym 0.0.1
File	Interpreter	ABI	Platform	Reset
ggym-0.0.1-py3-none-any.whl 1.3 kB Sep 30, 2026	Python 3	none	any	Details

Total release size: 2.5 kB

Download URL	ggym-0.0.1.tar.gz
Size	1.3 kB
Tags	Source
SHA-256 checksum How to use checksums	`a04df0d4640c485bc7e08fcf2c3341465ff24e9483d57f9b78bcb60e16ad6b7f`
BLAKE2b-256 checksum How to use checksums	`6d04fab69d1860e7b5b4ac72e08204f5a3c08bf685634b3c90199156f04e660c`
Upload date	Sep 30, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.4`

Download URL	ggym-0.0.1-py3-none-any.whl
Size	1.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`fc2774751e79a746c39597c7344caebc7825eb4d4a400d76acf1689c05b59591`
BLAKE2b-256 checksum How to use checksums	`5cb8d841cac801692af4c8ff2ce133ec2c08101cd81433f9fa79e93bc0bb98b4`
Upload date	Sep 30, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.14.4`

This release

0.0.1 This release