Replace setup.py with pyproject.toml (#875)

.github/workflows/linux-test.yml

@@ -29,6 +29,7 @@ jobs:
         run: |
           sudo apt-get install python3-opengl xvfb
           pip install -e .[all]
+          pip install -e .[tests]
           AutoROM -v
       - name: Source distribution test
         run: |

.github/workflows/macos-test.yml

@@ -22,6 +22,7 @@ jobs:
       - name: Install dependencies
         run: |
           pip install -e .[all]
+          pip install -e .[tests]
           AutoROM -v
       - name: Full Python tests
         run: |

pettingzoo/test/api_test.py

@@ -245,7 +245,7 @@ def play_test(env, observation_0, num_cycles):
         if terminated or truncated:
             action = None
         elif isinstance(prev_observe, dict) and "action_mask" in prev_observe:
-            action = random.choice(np.flatnonzero(prev_observe["action_mask"]))
+            action = random.choice(np.flatnonzero(prev_observe["action_mask"]).tolist())
         else:
             action = env.action_space(agent).sample()
 
@@ -319,7 +319,7 @@ def play_test(env, observation_0, num_cycles):
         if terminated or truncated:
             action = None
         elif isinstance(obs, dict) and "action_mask" in obs:
-            action = random.choice(np.flatnonzero(obs["action_mask"]))
+            action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
         else:
             action = env.action_space(agent).sample()
         assert isinstance(terminated, bool), "terminated from last is not True or False"
@@ -350,7 +350,7 @@ def test_action_flexibility(env):
         if terminated or truncated:
             action = None
         elif isinstance(obs, dict) and "action_mask" in obs:
-            action = random.choice(np.flatnonzero(obs["action_mask"]))
+            action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
         else:
             action = 0
         env.step(action)

pettingzoo/test/bombardment_test.py

@@ -22,7 +22,7 @@ def bombardment_test(env, cycles=10000):
             if termination or truncation:
                 action = None
             elif isinstance(obs, dict) and "action_mask" in obs:
-                action = random.choice(np.flatnonzero(obs["action_mask"]))
+                action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
             else:
                 action = env.action_space(agent).sample()
             next_observe = env.step(action)

pettingzoo/test/performance_benchmark.py

@@ -21,7 +21,7 @@ def performance_benchmark(env):
             if termination or truncation:
                 action = None
             elif isinstance(obs, dict) and "action_mask" in obs:
-                action = random.choice(np.flatnonzero(obs["action_mask"]))
+                action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
             else:
                 action = env.action_space(agent).sample()
             env.step(action)

pettingzoo/test/render_test.py

@@ -14,7 +14,7 @@ def collect_render_results(env):
                 if terminated or truncated:
                     action = None
                 elif isinstance(obs, dict) and "action_mask" in obs:
-                    action = random.choice(np.flatnonzero(obs["action_mask"]))
+                    action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
                 else:
                     action = env.action_space(agent).sample()
                 env.step(action)

pettingzoo/test/seed_test.py

@@ -28,7 +28,7 @@ def calc_hash(new_env, rand_issue, max_env_iters):
             if terminated or truncated:
                 action = None
             elif isinstance(obs, dict) and "action_mask" in obs:
-                action = sampler.choice(np.flatnonzero(obs["action_mask"]))
+                action = sampler.choice(np.flatnonzero(obs["action_mask"]).tolist())
             else:
                 action = new_env.action_space(agent).sample()
             new_env.step(action)

pettingzoo/utils/average_total_reward.py

@@ -27,7 +27,7 @@ def average_total_reward(env, max_episodes=100, max_steps=10000000000):
             if termination or truncation:
                 action = None
             elif isinstance(obs, dict) and "action_mask" in obs:
-                action = random.choice(np.flatnonzero(obs["action_mask"]))
+                action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
             else:
                 action = env.action_space(agent).sample()
             env.step(action)

pettingzoo/utils/random_demo.py

@@ -19,7 +19,7 @@ def random_demo(env, render=True, episodes=1):
             if termination or truncation:
                 action = None
             elif isinstance(obs, dict) and "action_mask" in obs:
-                action = random.choice(np.flatnonzero(obs["action_mask"]))
+                action = random.choice(np.flatnonzero(obs["action_mask"]).tolist())
             else:
                 action = env.action_space(agent).sample()
             env.step(action)

pyproject.toml

@@ -1,5 +1,92 @@
-[tool.pyright]
+# Package ######################################################################
+
+[build-system]
+requires = ["setuptools >= 61.0.0"]
+build-backend = "setuptools.build_meta"
 
+[project]
+name = "pettingzoo"
+description = "Gymnasium for multi-agent reinforcement learning."
+readme = "README.md"
+requires-python = ">= 3.7"
+authors = [{ name = "Farama Foundation", email = "[email protected]" }]
+license = { text = "MIT License" }
+keywords = ["Reinforcement Learning", "game", "RL", "AI", "gymnasium"]
+classifiers = [
+    "Development Status :: 4 - Beta",  # change to `5 - Production/Stable` when ready
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    'Intended Audience :: Science/Research',
+    'Topic :: Scientific/Engineering :: Artificial Intelligence',
+]
+
+dependencies = [
+    "numpy>=1.21.0",
+    "gymnasium>=0.26.0",
+]
+dynamic = ["version"]
+
+[project.optional-dependencies]
+# Update dependencies in `all` if any are added or removed
+atari = ["multi_agent_ale_py==0.1.11", "pygame==2.1.3.dev8"]
+classic = [
+    "chess==1.7.0",
+    "rlcard==1.0.5",
+    "pygame==2.1.3.dev8",
+    "hanabi_learning_environment==0.0.4",
+]
+butterfly = ["pygame==2.1.3.dev8", "pymunk==6.2.0"]
+mpe = ["pygame==2.1.3.dev8"]
+sisl = ["pygame==2.1.3.dev8", "box2d-py==2.3.5", "scipy>=1.4.1"]
+other = ["pillow>=8.0.1"]
+tests = [
+    "pynput",
+    "pytest",
+    "AutoROM",
+    "pytest",
+    "pytest-cov",
+    "pre-commit",
+]
+all = [
+    "multi_agent_ale_py==0.1.11",
+    "pygame==2.1.3.dev8",
+    "chess==1.7.0",
+    "rlcard==1.0.5",
+    "hanabi_learning_environment==0.0.4",
+    "pymunk==6.2.0",
+    "box2d-py==2.3.5",
+    "scipy>=1.4.1",
+    "pillow>=8.0.1",
+]
+
+[project.urls]
+Homepage = "https://farama.org"
+Repository = "https://github.com/Farama-Foundation/PettingZoo"
+Documentation = "https://pettingzoo.farama.org"
+"Bug Report" = "https://github.com/Farama-Foundation/PettingZoo/issues"
+
+[tool.setuptools]
+include-package-data = true
+
+[tool.setuptools.packages.find]
+include = ["pettingzoo", "pettingzoo.*"]
+
+# Linters and Test tools #######################################################
+
+[tool.black]
+safe = true
+
+[tool.isort]
+atomic = true
+profile = "black"
+src_paths = ["pettingzoo", "test"]
+
+[tool.pyright]
 # add any files/directories with type declaration to include
 include = [
     "pettingzoo/",

setup.py

@@ -1,98 +1,21 @@
-"""Sets up the PettingZoo module."""
+"""Setups the project."""
 
-from setuptools import find_packages, setup
+import pathlib
 
+from setuptools import setup
 
-def get_description():
-    """Gets the description from the readme."""
-    with open("README.md") as fh:
-        long_description = ""
-        header_count = 0
-        for line in fh:
-            if line.startswith("##"):
-                header_count += 1
-            if header_count < 2:
-                long_description += line
-            else:
-                break
-    return header_count, long_description
+CWD = pathlib.Path(__file__).absolute().parent
 
 
 def get_version():
     """Gets the pettingzoo version."""
-    path = "pettingzoo/__init__.py"
-    with open(path) as file:
-        lines = file.readlines()
+    path = CWD / "pettingzoo" / "__init__.py"
+    content = path.read_text()
 
-    for line in lines:
+    for line in content.splitlines():
         if line.startswith("__version__"):
             return line.strip().split()[-1].strip().strip('"')
     raise RuntimeError("bad version data in __init__.py")
 
 
-extras = {
-    "atari": ["multi_agent_ale_py==0.1.11", "pygame==2.1.3.dev8"],
-    "classic": [
-        "chess==1.7.0",
-        "rlcard==1.0.5",
-        "pygame==2.1.3.dev8",
-        "hanabi_learning_environment==0.0.4",
-    ],
-    "butterfly": ["pygame==2.1.3.dev8", "pymunk==6.2.0"],
-    "mpe": ["pygame==2.1.3.dev8"],
-    "sisl": ["pygame==2.1.3.dev8", "box2d-py==2.3.5", "scipy>=1.4.1"],
-    "other": ["pillow>=8.0.1"],
-    "tests": [
-        "pynput",
-        "pytest",
-        "codespell",
-        "flake8",
-        "isort",
-        "AutoROM",
-        "bandit",
-        "pytest",
-        "pytest-cov",
-        "pre-commit",
-    ],
-}
-
-extras["all"] = (
-    extras["atari"]
-    + extras["classic"]
-    + extras["butterfly"]
-    + extras["mpe"]
-    + extras["sisl"]
-    + extras["other"]
-    + extras["tests"]
-)
-
-version = get_version()
-header_count, long_description = get_description()
-
-setup(
-    name="PettingZoo",
-    version=version,
-    author="Farama Foundation",
-    author_email="[email protected]",
-    description="Gymnasium for multi-agent reinforcement learning",
-    url="https://pettingzoo.farama.org/",
-    license_files=("LICENSE.txt",),
-    long_description=long_description,
-    long_description_content_type="text/markdown",
-    keywords=["Reinforcement Learning", "game", "RL", "AI", "gymnasium"],
-    python_requires=">=3.7, <3.12",
-    packages=["pettingzoo"]
-    + ["pettingzoo." + pkg for pkg in find_packages("pettingzoo")],
-    include_package_data=True,
-    install_requires=["numpy>=1.18.0", "gymnasium>=0.26.0"],
-    classifiers=[
-        "Development Status :: 5 - Production/Stable",
-        "Programming Language :: Python :: 3",
-        "Programming Language :: Python :: 3.7",
-        "Programming Language :: Python :: 3.8",
-        "Programming Language :: Python :: 3.9",
-        "Programming Language :: Python :: 3.10",
-        "Programming Language :: Python :: 3.11",
-    ],
-    extras_require=extras,
-)
+setup(name="pettingzoo", version=get_version())

test/doc_examples_test.py

@@ -1,4 +1,5 @@
 from docs.code_examples import aec_rps, parallel_rps
+
 from pettingzoo.test import api_test, parallel_api_test
 
 

tutorials/CleanRL/requirements.txt

@@ -1,3 +1,3 @@
 SuperSuit==3.6.0
 torch==1.13.1
-pettingzoo==1.22.0
+pettingzoo==1.22.3

tutorials/EnvironmentCreation/requirements.txt

@@ -1 +1 @@
-pettingzoo==1.22.1
+pettingzoo==1.22.3

tutorials/Ray/render_rllib_pistonball.py

@@ -15,9 +15,9 @@
 from ray.rllib.env.wrappers.pettingzoo_env import PettingZooEnv
 from ray.rllib.models import ModelCatalog
 from ray.tune.registry import register_env
+from tutorials.Ray.rllib_pistonball import CNNModelV2
 
 from pettingzoo.butterfly import pistonball_v6
-from tutorials.Ray.rllib_pistonball import CNNModelV2
 
 raise NotImplementedError(
     "There are currently bugs in this tutorial, we will fix them soon."

tutorials/Ray/requirements.txt

@@ -5,4 +5,4 @@ Pillow==9.3.0
 torch==1.13.1
 SuperSuit==3.6.0
 ray[rllib]==2
-pettingzoo==1.22.0
+pettingzoo==1.22.3

tutorials/Tianshou/requirements.txt

@@ -1,3 +1,3 @@
-pettingzoo[classic]==1.22.1
+pettingzoo[classic]==1.22.3
 packaging==21.3
-git+https://github.com/WillDudley/tianshou.git
+git+https://github.com/WillDudley/tianshou.git