Factual package intelligence from PyPI

digital-twinning 1.0.1 package intelligence

A comprehensive package for digital twin model updating and predictive modeling using machine learning and uncertainty quantification techniques

pip install digital-twinning

Current version
1.0.1
Python requirement
Not declared
License
GNU General Public License v3 (GPLv3)
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
154.3 KiB
Release history
28 releases with files
Median release cadence
0 days

digital-twinning dependencies

PyPI declares 19 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. asyncio
  2. catboost
  3. emcee
  4. gPCE-model
  5. IPython
  6. lightgbm
  7. matplotlib
  8. numpy
  9. pandas
  10. plotly
  11. SALib
  12. scipy
  13. seaborn
  14. shap
  15. scikit-learn
  16. torch
  17. uncertain-variables
  18. xgboost

The compact report shows 18 of 19 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

digital-twinning publishes 1 wheel and 1 source archive for version 1.0.1. Wheel platform tags: any.

No version-specific Python classifiers are declared.

Security snapshot for digital-twinning 1.0.1

An OSV query completed on and found 0 known vulnerabilities affecting this version. 0 advisories are classified as critical. 0 advisories appear in the CISA Known Exploited Vulnerabilities catalog.

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 28 releases with files. The first dated release is ; 28 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .