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setup.py
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from os import path
from setuptools import setup, find_packages
this_dir = path.abspath(path.dirname(__file__))
with open(path.join(this_dir, "README.md"), encoding="utf-8") as f:
long_description = f.read()
setup(
name="smarts",
description="Scalable Multi-Agent RL Training School",
long_description=long_description,
long_description_content_type="text/markdown",
version="0.4.3",
packages=find_packages(exclude="tests"),
include_package_data=True,
zip_safe=True,
python_requires=">=3.7",
install_requires=[
# setuptools:
# tensorboard needs >=41
# 50.0 is broken: https://github.com/pypa/setupatools/issues/2353
"setuptools>=41.0.0,!=50.0",
"click", # used in scl
"gym",
"panda3d",
"panda3d-gltf",
"numpy",
"shapely",
"networkx",
"trimesh", # Used for writing .glb files
"rtree", # Used by sumolib
"lz4",
"filelock",
"pandas",
"psutil",
"opencv-python",
"visdom",
"pybullet",
"sklearn", # KDTree from sklearn is used by waypoints
"tableprint",
"pynput", # Used by HumanKeyboardPolicy
"sh",
"rich",
"supervisor",
# HACK: There is a bug where if we only install the base ray dependency here
# and ray[rllib] under [train] it prevents rllib from getting installed.
# For simplicity we just install both here. In the future we may want to
# address this bug head on to keep our SMARTS base install more lean.
"ray[rllib]==0.8.3", # We use Ray for our multiprocessing needs
# The following are for Scenario Studio
"yattag",
# The following are for testing
"pytest",
"pytest-benchmark",
"pytest-xdist",
"pytest-cov",
# The following are for /envision
"tornado",
"websocket-client",
"cloudpickle<1.4.0",
# The following are for the /smarts/algorithms
"matplotlib",
"scikit-image",
# The following are for /smarts/zoo
"twisted",
"PyYAML",
],
extras_require={
"train": ["tensorflow==1.15", "torch==1.3.0", "torchvision==0.4.1"],
"dev": [
"black==19.10b0",
"sphinx",
"sphinx-rtd-theme",
"sphinxcontrib-apidoc",
],
},
entry_points={"console_scripts": ["scl=cli.cli:scl"]},
)