import itertools
from pathlib import Path
from typing import List

from setuptools import setup, find_packages

# Environment-specific dependencies for dmc and metaworld
extras = {
    'dmc': ['dm_control>=1.0.1'],
    'metaworld': ['metaworld @ git+https://github.com/rlworkgroup/metaworld.git@3ced29c8cee6445386eba32e92870d664ad5e6e3#egg=metaworld',
                  'mujoco-py<2.2,>=2.1',
                  ],
    'box2d': ['gymnasium[box2d]>=0.26.0'],
    'testing': ['pytest'],
}

# All dependencies
all_groups = set(extras.keys())
extras["all"] = list(set(itertools.chain.from_iterable(
    map(lambda group: extras[group], all_groups))))


def find_package_data(extensions_to_include: List[str]) -> List[str]:
    envs_dir = Path("fancy_gym/envs/mujoco")
    package_data_paths = []
    for extension in extensions_to_include:
        package_data_paths.extend([str(path)[10:]
                                  for path in envs_dir.rglob(extension)])

    return package_data_paths


setup(
    author='Fabian Otto, Onur Celik',
    name='fancy_gym',
    version='0.3',
    classifiers=[
        'Development Status :: 3 - Alpha',
        'Intended Audience :: Science/Research',
        'License :: OSI Approved :: MIT License',
        'Natural Language :: English',
        'Operating System :: OS Independent',
        'Topic :: Scientific/Engineering :: Artificial Intelligence',
        'Programming Language :: Python :: 3',
        'Programming Language :: Python :: 3.7',
        'Programming Language :: Python :: 3.8',
        'Programming Language :: Python :: 3.9',
        'Programming Language :: Python :: 3.10',
    ],
    extras_require=extras,
    install_requires=[
        'gymnasium>=0.26.0'
        'mp_pytorch<=0.1.3'
    ],
    packages=[package for package in find_packages(
    ) if package.startswith("fancy_gym")],
    package_data={
        "fancy_gym": find_package_data(extensions_to_include=["*.stl", "*.xml"])
    },
    python_requires=">=3.7",
    url='https://github.com/ALRhub/fancy_gym/',
    license='MIT license',
    author_email='',
    description='Fancy Gym: Unifying interface for various RL benchmarks with support for Black Box approaches.'
)