Factual package intelligence from PyPI

mol-coma 2.1.0 package intelligence

Choi, J., Seo, S. & Park, S. COMA: efficient structure-constrained molecular generation using contractive and margin losses. J Cheminform 15, 8 (2023). https://doi.org/10.1186/s13321-023-00679-y

pip install mol-coma

Current version
2.1.0
Python requirement
Not declared
License
Not declared
Distribution type
Pure Python wheel
Release files
1 (1 wheels, 0 source)
Download size
3.7 MiB
Release history
8 releases with files
Median release cadence
0 days

mol-coma dependencies

PyPI declares 12 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy >=1.19.5
  2. scikit-learn >=0.20.0
  3. rdkit >=2022.3.3
  4. torch >=1.10.1
  5. jupyter >=1.0.0
  6. scipy >=1.5.3
  7. networkx >=2.3
  8. pandas >=1.1.5
  9. tqdm >=4.64.0
  10. requests >=2.28.0
  11. matplotlib >=3.3.4
  12. seaborn >=0.11.2

Compatibility and release files

mol-coma publishes 1 wheel and 0 source archives for version 2.1.0. Wheel platform tags: any.

Declared Python classifiers: 3.10, 3.11, 3.7, 3.8, 3.9.

Metadata completeness

PyPI does not currently declare: Python requirement, license. PyDeps marks these fields as unknown instead of guessing values.

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 .

4 historical releases are fully yanked in PyPI metadata.