Factual package intelligence from PyPI

autotuning_methodology 1.1.0 package intelligence

Software package easing implementation of the guidelines of the 2024 paper 'A Methodology for Comparing Auto-Tuning Optimization Algorithms' (https://doi.org/10.1016/j.future.2024.05.021). The DOI of

pip install autotuning-methodology

Current version
1.1.0
Python requirement
<4,>=3.10
License
MIT License
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
4.3 MiB
Release history
8 releases with files
Median release cadence
5 days

autotuning_methodology dependencies

PyPI declares 21 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy >=2.0.0
  2. scipy >=1.10.1
  3. scikit-learn >=1.0.2
  4. matplotlib >=3.7.1
  5. yappi >=1.4.0
  6. progressbar2 >=4.2.0
  7. jsonschema >=4.17.3
  8. nonconformist >=2.1.0
  9. kernel_tuner >=1.3.0

The compact report shows 12 of 21 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

autotuning_methodology publishes 1 wheel and 1 source archive for version 1.1.0. Wheel platform tags: any.

Declared Python classifiers: 3.10, 3.11, 3.12, 3.13.

Release activity and sources

PyPI lists 8 releases with files. The first dated release is ; 1 release falls within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .