pyproject.toml

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

[tool.setuptools.packages.find]
where = ["./src"]
include = ["uav_envs*", "uav_rl*"]

[project]
name = "ray_uav"
version = "0.1.0"
authors = [
    { name = "0Pinky0", email = "lpinkyl@126.com" },
]
license = { text = "MIT License" }
keywords = ["Reinforcement Learning", "RL", "AI"]
classifiers = [
    "Development Status :: 4 - Beta",
    "License :: OSI Approved :: MIT License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    'Intended Audience :: Science/Research',
    'Topic :: Scientific/Engineering :: Artificial Intelligence',
]
description = "Self constructed environments based on Jax."
readme = "README.md"
requires-python = ">=3.8, <3.13"
dependencies = [
    "omegaconf",
    "opencv-python",
    "gputil",
    "tqdm",
    "ray[default, train, tune, rllib]==2.38.0",
#    "ray[default, train, tune, rllib] @ https://s3-us-west-2.amazonaws.com/ray-wheels/latest/ray-3.0.0.dev0-cp310-cp310-manylinux2014_x86_64.whl",
    "google-api-core==2.17.1",
    "google-auth==2.28.1",
    "google-auth-oauthlib==1.2.0",
    "google-pasta==0.2.0",
    "googleapis-common-protos==1.62.0",
    "gymnasium==0.28.1",
#    "gymnasium[atari]",
#    "gymnasium[accept-rom-license]",
    "pygame>=2.1.3",
    "tensorboard",
    "tensordict",
    "torch",
    "numpy<2.0",
    "matplotlib",
    "orjson",
]