Factual package intelligence from PyPI
A Python tool to forecast GA data using several popular timeseries models
pip install forecastga
PyPI declares 39 unique dependency rules for this release. Environment markers are shown when supplied by the project.
>=1.3.0,<2.0.0>=1.4.2,<2.0.0>=0.4.4,<0.5.0>=0.7.1,<0.8.0>=0.6.4,<0.7.0>=1.24.1,<2.0.0>=1.12.8,<2.0.0>=0.0.4,<0.0.5>=1.24.0,<2.0.0>=0.10.4,<0.11.0>=0.18.1,<0.19.0>=0.3.2,<0.4.0>=21.8.0,<22.0.0>=3.1.1,<4.0.0==3.2.2>=4.1.3,<5.0.0>=1.8.0,<2.0.0>=2.0.0,<3.0.0>=2.19.1,<3.0.0>=2.8.1,<3.0.0>=5.3.1,<6.0.0>=2.25.1,<3.0.0>=4.6,<5.0>=0.24.0,<0.25.0==1.5.0The compact report shows 25 of 39 declarations. The interactive dependency graph loads the complete metadata.
forecastga publishes 1 wheel and 1 source archive for version 0.1.16. Wheel platform tags: any.
Declared Python classifiers: 3.7, 3.8, 3.9.
PyPI lists 14 releases with files. The first dated release is ; 14 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .