translate setup to pyproject

pyproject.toml

@@ -0,0 +1,38 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "pina-mathlab"
+version = "0.2.0"
+description = "Physic Informed Neural networks for Advance modeling."
+readme = "README.md"
+authors = [
+    { name = "PINA Contributors" },
+]
+license = { text = "MIT" }
+keywords = [
+    "machine-learning", "deep-learning", "modeling", "pytorch", "ode", 
+    "neural-networks", "differential-equations", "pde", "hacktoberfest", 
+    "pinn", "physics-informed", "physics-informed-neural-networks", "neural-operators", "equation-learning", "lightining"
+]
+dependencies = [
+    "numpy", "matplotlib", "lightning", "torch_geometric", "pytorch_lightning"
+]
+requires-python = ">=3.8"
+
+[project.optional-dependencies]
+docs = [
+    "sphinx>5.0", "sphinx_rtd_theme", "sphinx_copybutton", "sphinx_design", "pydata_sphinx_theme"
+]
+test = [
+    "pytest", "pytest-cov", "scipy"
+]
+
+[project.urls]
+Homepage = "https://github.com/mathLab/PINA"
+Repository = "https://github.com/mathLab/PINA"
+
+[tool.setuptools]
+packages = ["pina"]
+

setup.py

@@ -1,74 +0,0 @@
-from setuptools import setup, find_packages
-
-meta = {}
-with open("pina/meta.py") as fp:
-    exec(fp.read(), meta)
-
-# Package meta-data.
-IMPORTNAME = meta['__title__']
-PIPNAME = meta['__packagename__']
-DESCRIPTION = 'Physic Informed Neural networks for Advance modeling.'
-URL = 'https://github.com/mathLab/PINA'
-MAIL = meta['__mail__']
-AUTHOR = meta['__author__']
-VERSION = meta['__version__']
-KEYWORDS = 'machine-learning deep-learning modeling pytorch ode neural-networks differential-equations pde hacktoberfest pinn physics-informed physics-informed-neural-networks neural-operators equation-learning lightining'
-
-REQUIRED = [
-    'numpy', 'matplotlib', 'torch', 'lightning', 'torch_geometric',
-    'torch-cluster', 'pytorch_lightning',
-]
-
-EXTRAS = {
-    'docs': [
-        'sphinx>5.0',
-        'sphinx_rtd_theme',
-        'sphinx_copybutton',
-        'sphinx_design',
-        'pydata_sphinx_theme'
-        ],
-    'test': [
-        'pytest',
-        'pytest-cov',
-        'scipy'
-    ],
-}
-
-LDESCRIPTION = (
-    "PINA is a Python package providing an easy interface to deal with "
-    "physics-informed neural networks (PINN) for the approximation of "
-    "(differential, nonlinear, ...) functions. Based on Pytorch, PINA "
-    "offers a simple and intuitive way to formalize a specific problem "
-    "and solve it using PINN. The approximated solution of a differential "
-    "equation can be implemented using PINA in a few lines of code thanks "
-    "to the intuitive and user-friendly interface."
-)
-
-setup(
-    name=PIPNAME,
-    version=VERSION,
-    description=DESCRIPTION,
-    long_description=LDESCRIPTION,
-    author=AUTHOR,
-    author_email=MAIL,
-    classifiers=[
-        'Development Status :: 3 - Alpha',
-        'License :: OSI Approved :: MIT License',
-        'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: 3.8',
-        'Programming Language :: Python :: 3.9',
-        'Programming Language :: Python :: 3.10',
-        'Programming Language :: Python :: 3.11',
-        'Programming Language :: Python :: 3.12',
-        'Intended Audience :: Science/Research',
-        'Topic :: Scientific/Engineering :: Mathematics'
-    ],
-    keywords=KEYWORDS,
-    url=URL,
-    license='MIT',
-    packages=find_packages(),
-    install_requires=REQUIRED,
-    extras_require=EXTRAS,
-    include_package_data=True,
-    zip_safe=False,
-)