add py3.12

.github/workflows/build.yml

@@ -9,7 +9,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
     steps:
       - uses: actions/checkout@v2
       - run: |

README.md

@@ -1,4 +1,8 @@
-[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://pre-commit.com/) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+[![Python](https://img.shields.io/pypi/pyversions/gymnasium-robotics.svg)](https://badge.fury.io/py/gymnasium-robotics)
+[![PyPI](https://badge.fury.io/py/gymnasium-robotics.svg)](https://badge.fury.io/py/gymnasium-robotics)
+[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://pre-commit.com/)
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
 
 <p align="center">
   <img src="https://raw.githubusercontent.com/Farama-Foundation/Gymnasium-Robotics/main/gymrobotics-revised-text.png" width="500px"/>
@@ -16,7 +20,7 @@ These environments also require the MuJoCo engine from Deepmind to be installed.
 
 Note that the latest environment versions use the latest mujoco python bindings maintained by the MuJoCo team. If you wish to use the old versions of the environments that depend on [mujoco-py](https://github.com/openai/mujoco-py), please install this library with `pip install gymnasium-robotics[mujoco-py]`
 
-We support and test for Python 3.8, 3.9, 3.10 and 3.11 on Linux and macOS. We will accept PRs related to Windows, but do not officially support it.
+We support and test for Linux and macOS. We will accept PRs related to Windows, but do not officially support it.
 
 ## Environments
 

pyproject.toml

@@ -13,13 +13,14 @@ authors = [{ name = "Farama Foundation", email = "[email protected]" }]
 license = { text = "MIT License" }
 keywords = ["Reinforcement Learning", "Gymnasium", "RL", "AI", "Robotics"]
 classifiers = [
-    "Development Status :: 4 - Beta",  # change to `5 - Production/Stable` when ready
+    "Development Status :: 5 - Production/Stable",
     "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 :: Artificial Intelligence',
 ]

tests/envs/hand/test_manipulate.py

@@ -4,9 +4,12 @@
 import pytest
 
 ENVIRONMENT_IDS = (
-    "HandManipulateEgg-v0",
-    "HandManipulatePen-v0",
-    "HandManipulateBlock-v0",
+    #  "HandManipulateEgg-v0",
+    #  "HandManipulatePen-v0",
+    #  "HandManipulateBlock-v0",
+    "HandManipulateEgg-v1",
+    "HandManipulatePen-v1",
+    "HandManipulateBlock-v1",
 )
 
 

tests/envs/hand/test_reach.py

@@ -4,7 +4,7 @@
 
 
 def test_serialize_deserialize():
-    env1 = gym.make("HandReach-v0", distance_threshold=1e-6)
+    env1 = gym.make("HandReach-v2", distance_threshold=1e-6)
     env1.reset()
     env2 = pickle.loads(pickle.dumps(env1))