Factual package intelligence from PyPI

raven-framework 3.2 package intelligence

RAVEN (Risk Analysis Virtual Environment) is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN C++ dependenciences including a library for computing the Approximate Morse-Smale Complex (AMSC) and Crow probability tools

pip install raven-framework

Current version
3.2
Python requirement
Not declared
License
Not declared
Distribution type
Includes compiled wheel
Release files
5 (4 wheels, 1 source)
Download size
12.4 MiB
Release history
6 releases with files
Median release cadence
188 days

raven-framework dependencies

PyPI declares 30 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. h5py
  2. numpy ==1.26.*
  3. scipy ==1.12.*
  4. scikit-learn ==1.1.*
  5. numba ==0.61.*
  6. pandas
  7. xarray
  8. netcdf4 ==1.6.*
  9. matplotlib ==3.6.*
  10. statsmodels ==0.13.*
  11. cloudpickle
  12. tensorflow ==2.14.*
  13. pylint
  14. coverage
  15. lxml
  16. psutil
  17. pyDOE3
  18. importlib_metadata
  19. dask
  20. typing-extensions ==4.14.*
  21. ray ==2.49.*
  22. imageio ==2.22.*
  23. statsforecast
  24. pywavelets ==1.4.*
  25. python-sensors

The compact report shows 25 of 30 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

raven-framework publishes 4 wheels and 1 source archive for version 3.2. Wheel platform tags: macosx_11_0_arm64, win_amd64.

No version-specific Python classifiers are declared.

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 6 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 .