Factual package intelligence from PyPI
EazyML provides a suite of APIs for identifying the Urbanicity of zip codes based on population density
pip install eazyml-segmentation
PyPI declares 35 unique dependency rules for this release. Environment markers are shown when supplied by the project.
==1.3.* when python_version <= "3.7"==1.0.* when python_version <= "3.7"==1.21.* when python_version <= "3.7"==5.9.* when python_version <= "3.7"==2.32.* when python_version <= "3.7">=2.0.3 when python_version == "3.8"==1.3.* when python_version == "3.8"==1.24.* when python_version == "3.8"==5.9.* when python_version == "3.8"==2.32.* when python_version == "3.8">=2.2.3 when python_version == "3.9"==1.3.* when python_version == "3.9"==1.24.* when python_version == "3.9">=2.2.3 when python_version == "3.10"==1.3.* when python_version == "3.10"==1.24.* when python_version == "3.10"The compact report shows 25 of 35 declarations. The interactive dependency graph loads the complete metadata.
eazyml-segmentation publishes 1 wheel and 1 source archive for version 0.1.2. Wheel platform tags: any.
Declared Python classifiers: 3.10, 3.11, 3.12, 3.8, 3.9.
PyPI lists 2 releases with files. The first dated release is ; 2 releases fall within the 365 days preceding the latest dated release. The current release files were uploaded on . The preceding dated release was .