Factual package intelligence from PyPI

happymath 0.2.1 package intelligence

Happymath is a high-level mathematical modeling Python library. Its core philosophy lies in reducing users' learning costs through high-level encapsulation, enabling efficient mathematical modeling. I

pip install happymath

Current version
0.2.1
Python requirement
>=3.11
License
MIT
Distribution type
Pure Python wheel
Release files
2 (1 wheels, 1 source)
Download size
693.4 KiB
Release history
8 releases with files
Median release cadence
55 days

happymath dependencies

PyPI declares 38 unique dependency rules for this release. Environment markers are shown when supplied by the project.

  1. numpy
  2. scipy ==1.10.0
  3. sympy
  4. pandas <2.2.0
  5. scikit-learn
  6. catboost
  7. xgboost
  8. pycaret ==3.3.2
  9. pyomo
  10. pymoo
  11. matplotlib <3.8.0
  12. seaborn

The compact report shows 12 of 38 declarations. The interactive dependency graph loads the complete metadata.

Compatibility and release files

happymath publishes 1 wheel and 1 source archive for version 0.2.1. Wheel platform tags: any.

Declared Python classifiers: 3.11.

Security snapshot for happymath 0.2.1

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.

Release activity and sources

PyPI lists 8 releases with files. The first dated release is ; 7 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .