Factual package intelligence from PyPI

mat_discover 2.2.9 package intelligence

Data-driven materials discovery based on composition or structure.

pip install mat-discover

Current version
2.2.9
Python requirement
Not declared
License
MIT License
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
17.4 MiB
Release history
33 releases with files
Median release cadence
2 days

mat_discover dependencies

PyPI declares 36 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. tqdm
  2. pqdm
  3. seaborn
  4. scipy
  5. hdbscan
  6. joblib ==1.1.0
  7. cython
  8. numba >=0.53.1
  9. plotly >=5.6.0
  10. kaleido
  11. pandas
  12. matplotlib >=3.4.3
  13. scikit_learn
  14. umap-learn
  15. dill
  16. crabnet >=2.0.5,<3.0.0
  17. torch <2
  18. chem_wasserstein >=1.0.8,<2.0.0
  19. composition_based_feature_vector
  20. matbench_genmetrics >= 0.6.1
  21. megnet
  22. m3gnet
  23. gridrdf ==0.3.0
  24. matbench

The compact report shows 25 of 36 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

mat_discover publishes 1 wheel and 1 source archive for version 2.2.9. Wheel platform tags: any.

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

Metadata completeness

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

Release activity and sources

PyPI lists 33 releases with files. The first dated release is ; 4 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .

6 historical releases are fully yanked in PyPI metadata.