pyproject.toml

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[project]
name = "mgktools"
description = "Marginalized Graph Kernel Library for Molecular Property Prediction"
version = "3.1.0"
authors = [
    {name = "Yan Xiang", email="yan.xiang@duke.edu"}
]
readme = "README.md"
license = {text = "MIT"}
classifiers = [
	"Programming Language :: Python :: 3",
	"Programming Language :: Python :: 3.12",
    "License :: OSI Approved :: MIT License",
    "Operating System :: OS Independent"
]
keywords = [
    "chemistry",
    "machine learning",
    "molecular property prediction",
    "marginalized graph kernel",
    "drug discovery"
]
requires-python = ">=3.9"
dependencies = [
    "rdkit==2023.9.6", # new version print annoying warnings
    "descriptastorus==2.6.1", # new version fail in pickle and multi-process acceleration
    "numpy==1.26.4",
    "mendeleev==0.19.0",
    "typed-argument-parser",
    "scikit-learn",
    "rxntools",
    "optuna",
    "hyperopt",
    "ipython",
    "pytest"
]

[project.urls]
source = "https://github.com/xiangyan93/mgktools"
PyPi = "https://pypi.org/project/mgktools/"

[project.scripts]
mgk_cache_data = "mgktools.exe.run:mgk_cache_data"
mgk_kernel_calc = "mgktools.exe.run:mgk_kernel_calc"
mgk_cross_validation = "mgktools.exe.run:mgk_cross_validation"
mgk_gradientopt = "mgktools.exe.run:mgk_gradientopt"
mgk_optuna = "mgktools.exe.run:mgk_optuna"
mgk_optuna_multi_datasets = "mgktools.exe.run:mgk_optuna_multi_datasets"
mgk_embedding = "mgktools.exe.run:mgk_embedding"

[tool.setuptools.package-data]
"*" = ["hyperparameters/configs/*.json", "graph/*.dat"]

[tool.setuptools.packages.find]
where = ["."]  # list of folders that contain the packages (["."] by default)
namespaces = false  # to disable scanning PEP 420 namespaces (true by default)