Update to support Gymnasium v1.0

.github/workflows/build.yml

@@ -16,7 +16,7 @@ jobs:
 
     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
@@ -25,20 +25,6 @@ jobs:
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        sudo pip install pygame
-        pip install -e .[deploy]
-    - name: Lint with flake8
-      run: |
-        pip install flake8
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+      run: pip install .[testing]
     - name: Test with pytest
-      run: |
-        pip install pytest
-        pip install pytest-cov
-        pytest --cov=./ --cov-report=xml
-
+      run: pytest --cov=./ --cov-report=xml

.pre-commit-config.yaml

@@ -17,7 +17,6 @@ repos:
     hooks:
       - id: isort
         args: ["--profile", "black"]
-        exclude: "__init__.py"
   - repo: https://github.com/python/black
     rev: 23.3.0
     hooks:

highway_env/__init__.py

@@ -1,7 +1,9 @@
 import os
 import sys
 
-__version__ = "1.9.1"
+from gymnasium.envs.registration import register
+
+__version__ = "2.0.0"
 
 try:
     from farama_notifications import notifications
@@ -15,96 +17,101 @@
 # Hide pygame support prompt
 os.environ["PYGAME_HIDE_SUPPORT_PROMPT"] = "1"
 
-from gymnasium.envs.registration import register
-from highway_env.envs.common.abstract import MultiAgentWrapper
-
 
-def register_highway_envs():
+def _register_highway_envs():
     """Import the envs module so that envs register themselves."""
 
+    from highway_env.envs.common.abstract import MultiAgentWrapper
+
     # exit_env.py
     register(
         id="exit-v0",
-        entry_point="highway_env.envs:ExitEnv",
+        entry_point="highway_env.envs.exit_env:ExitEnv",
     )
 
     # highway_env.py
     register(
         id="highway-v0",
-        entry_point="highway_env.envs:HighwayEnv",
+        entry_point="highway_env.envs.highway_env:HighwayEnv",
     )
 
     register(
         id="highway-fast-v0",
-        entry_point="highway_env.envs:HighwayEnvFast",
+        entry_point="highway_env.envs.highway_env:HighwayEnvFast",
     )
 
     # intersection_env.py
     register(
         id="intersection-v0",
-        entry_point="highway_env.envs:IntersectionEnv",
+        entry_point="highway_env.envs.intersection_env:IntersectionEnv",
     )
 
     register(
         id="intersection-v1",
-        entry_point="highway_env.envs:ContinuousIntersectionEnv",
+        entry_point="highway_env.envs.intersection_env:ContinuousIntersectionEnv",
     )
 
     register(
         id="intersection-multi-agent-v0",
-        entry_point="highway_env.envs:MultiAgentIntersectionEnv",
+        entry_point="highway_env.envs.intersection_env:MultiAgentIntersectionEnv",
     )
 
     register(
         id="intersection-multi-agent-v1",
-        entry_point="highway_env.envs:MultiAgentIntersectionEnv",
+        entry_point="highway_env.envs.intersection_env:MultiAgentIntersectionEnv",
         additional_wrappers=(MultiAgentWrapper.wrapper_spec(),),
     )
 
     # lane_keeping_env.py
     register(
         id="lane-keeping-v0",
-        entry_point="highway_env.envs:LaneKeepingEnv",
+        entry_point="highway_env.envs.lane_keeping_env:LaneKeepingEnv",
         max_episode_steps=200,
     )
 
     # merge_env.py
     register(
         id="merge-v0",
-        entry_point="highway_env.envs:MergeEnv",
+        entry_point="highway_env.envs.merge_env:MergeEnv",
     )
 
     # parking_env.py
     register(
         id="parking-v0",
-        entry_point="highway_env.envs:ParkingEnv",
+        entry_point="highway_env.envs.parking_env:ParkingEnv",
     )
 
     register(
         id="parking-ActionRepeat-v0",
-        entry_point="highway_env.envs:ParkingEnvActionRepeat",
+        entry_point="highway_env.envs.parking_env:ParkingEnvActionRepeat",
     )
 
     register(
-        id="parking-parked-v0", entry_point="highway_env.envs:ParkingEnvParkedVehicles"
+        id="parking-parked-v0",
+        entry_point="highway_env.envs.parking_env:ParkingEnvParkedVehicles",
     )
 
     # racetrack_env.py
     register(
         id="racetrack-v0",
-        entry_point="highway_env.envs:RacetrackEnv",
+        entry_point="highway_env.envs.racetrack_env:RacetrackEnv",
     )
 
     # roundabout_env.py
     register(
         id="roundabout-v0",
-        entry_point="highway_env.envs:RoundaboutEnv",
+        entry_point="highway_env.envs.roundabout_env:RoundaboutEnv",
     )
 
     # two_way_env.py
     register(
-        id="two-way-v0", entry_point="highway_env.envs:TwoWayEnv", max_episode_steps=15
+        id="two-way-v0",
+        entry_point="highway_env.envs.two_way_env:TwoWayEnv",
+        max_episode_steps=15,
     )
 
     # u_turn_env.py
-    register(id="u-turn-v0", entry_point="highway_env.envs:UTurnEnv")
+    register(id="u-turn-v0", entry_point="highway_env.envs.u_turn_env:UTurnEnv")
+
+
+_register_highway_envs()

highway_env/envs/__init__.py

@@ -1,10 +1,35 @@
-from highway_env.envs.highway_env import *
-from highway_env.envs.merge_env import *
-from highway_env.envs.parking_env import *
-from highway_env.envs.roundabout_env import *
-from highway_env.envs.two_way_env import *
-from highway_env.envs.intersection_env import *
-from highway_env.envs.lane_keeping_env import *
-from highway_env.envs.u_turn_env import *
-from highway_env.envs.exit_env import *
-from highway_env.envs.racetrack_env import *
+from highway_env.envs.exit_env import ExitEnv
+from highway_env.envs.highway_env import HighwayEnv, HighwayEnvFast
+from highway_env.envs.intersection_env import (
+    ContinuousIntersectionEnv,
+    IntersectionEnv,
+    MultiAgentIntersectionEnv,
+)
+from highway_env.envs.lane_keeping_env import LaneKeepingEnv
+from highway_env.envs.merge_env import MergeEnv
+from highway_env.envs.parking_env import (
+    ParkingEnv,
+    ParkingEnvActionRepeat,
+    ParkingEnvParkedVehicles,
+)
+from highway_env.envs.racetrack_env import RacetrackEnv
+from highway_env.envs.roundabout_env import RoundaboutEnv
+from highway_env.envs.two_way_env import TwoWayEnv
+from highway_env.envs.u_turn_env import UTurnEnv
+
+__all__ = [
+    "ExitEnv",
+    "HighwayEnv",
+    "HighwayEnvFast",
+    "IntersectionEnv",
+    "ContinuousIntersectionEnv",
+    "MultiAgentIntersectionEnv",
+    "LaneKeepingEnv",
+    "MergeEnv",
+    "ParkingEnv",
+    "ParkingEnvActionRepeat",
+    "RacetrackEnv",
+    "RoundaboutEnv",
+    "TwoWayEnv",
+    "UTurnEnv",
+]

highway_env/envs/common/abstract.py

@@ -5,6 +5,7 @@
 import gymnasium as gym
 import numpy as np
 from gymnasium import Wrapper
+from gymnasium.utils import RecordConstructorArgs
 from gymnasium.wrappers import RecordVideo
 
 from highway_env import utils
@@ -426,10 +427,13 @@ def __deepcopy__(self, memo):
         return result
 
 
-class MultiAgentWrapper(Wrapper):
+class MultiAgentWrapper(Wrapper, RecordConstructorArgs):
+    def __init__(self, env):
+        Wrapper.__init__(self, env)
+        RecordConstructorArgs.__init__(self)
+
     def step(self, action):
-        obs, reward, terminated, truncated, info = super().step(action)
+        obs, _, _, truncated, info = super().step(action)
         reward = info["agents_rewards"]
         terminated = info["agents_terminated"]
-        truncated = info["agents_truncated"]
         return obs, reward, terminated, truncated, info

highway_env/envs/common/action.py

@@ -94,7 +94,7 @@ def __init__(
         lateral: bool = True,
         dynamical: bool = False,
         clip: bool = True,
-        **kwargs
+        **kwargs,
     ) -> None:
         """
         Create a continuous action space.
@@ -172,7 +172,7 @@ def __init__(
         dynamical: bool = False,
         clip: bool = True,
         actions_per_axis: int = 3,
-        **kwargs
+        **kwargs,
     ) -> None:
         super().__init__(
             env,
@@ -216,7 +216,7 @@ def __init__(
         longitudinal: bool = True,
         lateral: bool = True,
         target_speeds: Optional[Vector] = None,
-        **kwargs
+        **kwargs,
     ) -> None:
         """
         Create a discrete action space of meta-actions.

highway_env/envs/common/observation.py

@@ -70,7 +70,7 @@ def __init__(
         weights: List[float],
         scaling: Optional[float] = None,
         centering_position: Optional[List[float]] = None,
-        **kwargs
+        **kwargs,
     ) -> None:
         super().__init__(env)
         self.observation_shape = observation_shape
@@ -168,7 +168,7 @@ def __init__(
         see_behind: bool = False,
         observe_intentions: bool = False,
         include_obstacles: bool = True,
-        **kwargs: dict
+        **kwargs: dict,
     ) -> None:
         """
         :param env: The environment to observe
@@ -293,7 +293,7 @@ def __init__(
         align_to_vehicle_axes: bool = False,
         clip: bool = True,
         as_image: bool = False,
-        **kwargs: dict
+        **kwargs: dict,
     ) -> None:
         """
         :param env: The environment to observe
@@ -674,7 +674,7 @@ def observe(self) -> np.ndarray:
         if self.order == "shuffled":
             self.env.np_random.shuffle(obs[1:])
         # Flatten
-        return obs
+        return obs.astype(self.space().dtype)
 
 
 class LidarObservation(ObservationType):
@@ -687,7 +687,7 @@ def __init__(
         cells: int = 16,
         maximum_range: float = 60,
         normalize: bool = True,
-        **kwargs
+        **kwargs,
     ):
         super().__init__(env, **kwargs)
         self.cells = cells

highway_env/envs/exit_env.py

@@ -1,12 +1,14 @@
-from typing import Dict, Text, Tuple
+from __future__ import annotations
 
 import numpy as np
 
 from highway_env import utils
-from highway_env.envs import CircularLane, HighwayEnv, Vehicle
 from highway_env.envs.common.action import Action
+from highway_env.envs.highway_env import HighwayEnv
+from highway_env.road.lane import CircularLane
 from highway_env.road.road import Road, RoadNetwork
 from highway_env.vehicle.controller import ControlledVehicle
+from highway_env.vehicle.kinematics import Vehicle
 
 
 class ExitEnv(HighwayEnv):
@@ -44,10 +46,10 @@ def _reset(self) -> None:
         self._create_road()
         self._create_vehicles()
 
-    def step(self, action) -> Tuple[np.ndarray, float, bool, dict]:
-        obs, reward, terminal, info = super().step(action)
+    def step(self, action) -> tuple[np.ndarray, float, bool, bool, dict]:
+        obs, reward, terminated, truncated, info = super().step(action)
         info.update({"is_success": self._is_success()})
-        return obs, reward, terminal, info
+        return obs, reward, terminated, truncated, info
 
     def _create_road(
         self, road_length=1000, exit_position=400, exit_length=100
@@ -154,7 +156,7 @@ def _reward(self, action: Action) -> float:
             reward = np.clip(reward, 0, 1)
         return reward
 
-    def _rewards(self, action: Action) -> Dict[Text, float]:
+    def _rewards(self, action: Action) -> dict[str, float]:
         lane_index = (
             self.vehicle.target_lane_index
             if isinstance(self.vehicle, ControlledVehicle)

highway_env/envs/intersection_env.py

@@ -123,7 +123,7 @@ def _info(self, obs: np.ndarray, action: int) -> dict:
         info["agents_rewards"] = tuple(
             self._agent_reward(action, vehicle) for vehicle in self.controlled_vehicles
         )
-        info["agents_dones"] = tuple(
+        info["agents_terminated"] = tuple(
             self._agent_is_terminal(vehicle) for vehicle in self.controlled_vehicles
         )
         return info

highway_env/road/road.py

@@ -313,7 +313,7 @@ def straight_road_network(
                 *nodes_str,
                 StraightLane(
                     origin, end, line_types=line_types, speed_limit=speed_limit
-                )
+                ),
             )
         return net