formatting and linting

examples/panda_pick_and_place.py

@@ -246,9 +246,7 @@ def move_fingers(
 gazebo.run(paused=True)
 
 # Insert the Panda manipulator
-panda = gym_gz_environments.models.panda.Panda(
-    world=world, position=[-0.1, 0, 1.0]
-)
+panda = gym_gz_environments.models.panda.Panda(world=world, position=[-0.1, 0, 1.0])
 
 # Disable joint velocity limits
 _ = [j.to_gazebo().set_velocity_limit(1_000) for j in panda.joints()]

examples/python/launch_cartpole.py

@@ -20,8 +20,8 @@
 
 
 def make_env_from_id(env_id: str, **kwargs) -> gym.Env:
-    import gymnasium as gym
     import gym_gz_environments
+    import gymnasium as gym
 
     return gym.make(env_id, **kwargs)
 

python/gym_gz/__init__.py

@@ -19,8 +19,8 @@
 
 def initialize_verbosity() -> None:
 
-    import gymnasium as gym
     import gym_gz.utils.logger
+    import gymnasium as gym
 
     import scenario
 

python/gym_gz/base/task.py

@@ -7,7 +7,6 @@
 
 import gymnasium as gym
 import numpy as np
-from gymnasium.utils import seeding
 from gym_gz.utils.typing import (
     Action,
     ActionSpace,
@@ -16,6 +15,7 @@
     Reward,
     SeedList,
 )
+from gymnasium.utils import seeding
 
 from scenario import core
 
@@ -208,7 +208,7 @@ def is_terminated(self) -> bool:
         Returns:
             True if the environment terminated, False otherwise.
         """
-    
+
     @abc.abstractmethod
     def is_truncated(self) -> bool:
         """

python/gym_gz/randomizers/abc.py

@@ -118,9 +118,7 @@ def randomize_model(
 
 class ModelDescriptionRandomizer(abc.ABC):
     @abc.abstractmethod
-    def randomize_model_description(
-        self, task: gym_gz.base.task.Task, **kwargs
-    ) -> str:
+    def randomize_model_description(self, task: gym_gz.base.task.Task, **kwargs) -> str:
         """
         Randomize the model description.
 

python/gym_gz/randomizers/gazebo_env_randomizer.py

@@ -72,7 +72,9 @@ def __init__(
     # gym.Env methods
     # ===============
 
-    def reset(self, seed: int = None, options : Dict = {}, **kwargs) -> typing.ResetReturn:
+    def reset(
+        self, seed: int = None, options: Dict = {}, **kwargs
+    ) -> typing.ResetReturn:
 
         # Reset the physics
         if self._physics_randomizer.physics_expired() and seed is None:
@@ -94,7 +96,9 @@ def reset(self, seed: int = None, options : Dict = {}, **kwargs) -> typing.Reset
         self._physics_randomizer.increase_rollout_counter()
 
         # Reset the task through the TaskRandomizer
-        self.randomize_task(task=self.env.unwrapped.task, gazebo=self.env.unwrapped.gazebo, **kwargs)
+        self.randomize_task(
+            task=self.env.unwrapped.task, gazebo=self.env.unwrapped.gazebo, **kwargs
+        )
 
         ok_paused_run = self.env.unwrapped.gazebo.run(paused=True)
 

python/gym_gz/runtimes/gazebo_runtime.py

@@ -2,16 +2,25 @@
 # This software may be modified and distributed under the terms of the
 # GNU Lesser General Public License v2.1 or any later version.
 
-from typing import Optional, Dict
+from typing import Dict, Optional
 
+import gym_gz_models
 import gymnasium as gym
 import numpy as np
-
-import gym_gz_models
 from gym_gz import base
 from gym_gz.base import runtime
 from gym_gz.utils import logger
-from gym_gz.utils.typing import Action, Info, Observation, Reward, SeedList, State, Terminated, Truncated, ResetReturn
+from gym_gz.utils.typing import (
+    Action,
+    Info,
+    Observation,
+    ResetReturn,
+    Reward,
+    SeedList,
+    State,
+    Terminated,
+    Truncated,
+)
 
 from scenario import gazebo as scenario
 
@@ -143,9 +152,17 @@ def step(self, action: Action) -> State:
         # Get info
         info = self.task.get_info()
 
-        return State((Observation(observation), Reward(reward), Terminated(terminated), Truncated(truncated), Info(info)))
+        return State(
+            (
+                Observation(observation),
+                Reward(reward),
+                Terminated(terminated),
+                Truncated(truncated),
+                Info(info),
+            )
+        )
 
-    def reset(self, seed: int = None, options : Dict = {}, **kwargs) -> ResetReturn:
+    def reset(self, seed: int = None, options: Dict = {}, **kwargs) -> ResetReturn:
 
         self.seed(seed)
 
@@ -170,8 +187,8 @@ def reset(self, seed: int = None, options : Dict = {}, **kwargs) -> ResetReturn:
         # Render the environment
         if self.render_mode == "human":
             self.render()
-        
-        return ResetReturn((Observation(observation), Info(info))) 
+
+        return ResetReturn((Observation(observation), Info(info)))
 
     def render(self, **kwargs) -> None:
         mode = self.render_mode
@@ -282,9 +299,7 @@ def world(self) -> scenario.World:
         if self._world_sdf == "":
 
             # Insert the ground plane
-            ok_ground = world.insert_model(
-                gym_gz_models.get_model_file("ground_plane")
-            )
+            ok_ground = world.insert_model(gym_gz_models.get_model_file("ground_plane"))
 
             if not ok_ground:
                 raise RuntimeError("Failed to insert the ground plane")

python/gym_gz/runtimes/realtime_runtime.py

@@ -2,10 +2,22 @@
 # This software may be modified and distributed under the terms of the
 # GNU Lesser General Public License v2.1 or any later version.
 
-from gym_gz.base import runtime, task
-from gym_gz.utils.typing import Action, Done, Info, Observation, State, Terminated, Truncated, ResetReturn, Dict
 from typing import Optional
 
+from gym_gz.base import runtime, task
+from gym_gz.utils.typing import (
+    Action,
+    Dict,
+    Done,
+    Info,
+    Observation,
+    ResetReturn,
+    State,
+    Terminated,
+    Truncated,
+)
+
+
 class RealTimeRuntime(runtime.Runtime):
     """
     Implementation of :py:class:`~gym_gz.base.runtime.Runtime` for real-time
@@ -15,7 +27,14 @@ class RealTimeRuntime(runtime.Runtime):
         This class is not yet complete.
     """
 
-    def __init__(self, task_cls: type, robot_cls: type, agent_rate: float, render_mode: Optional[str] = None, **kwargs):
+    def __init__(
+        self,
+        task_cls: type,
+        robot_cls: type,
+        agent_rate: float,
+        render_mode: Optional[str] = None,
+        **kwargs
+    ):
 
         # Build the environment
         task_object = task_cls(**kwargs)
@@ -27,7 +46,7 @@ def __init__(self, task_cls: type, robot_cls: type, agent_rate: float, render_mo
 
         # Render mode
         self.render_mode = render_mode
-        
+
         super().__init__(task=task_object, agent_rate=agent_rate)
 
         raise NotImplementedError
@@ -72,17 +91,25 @@ def step(self, action: Action) -> State:
         # Check termination
         terminated = self.task.is_terminated()
 
-        #Check truncation
+        # Check truncation
         truncated = self.task.is_truncated()
 
-        return State((observation, reward, Terminated(terminated), Truncated(truncated), Info({})))
+        return State(
+            (
+                observation,
+                reward,
+                Terminated(terminated),
+                Truncated(truncated),
+                Info({}),
+            )
+        )
 
-    def reset(self, seed: int = None, options : Dict = {}, **kwargs) -> ResetReturn:
+    def reset(self, seed: int = None, options: Dict = {}, **kwargs) -> ResetReturn:
 
         # Get the observation
         observation = self.task.get_observation()
 
-        return ResetReturn((observation, Info({}))) 
+        return ResetReturn((observation, Info({})))
 
     def render(self, **kwargs) -> None:
         mode = self.render_mode

python/gym_gz_environments/tasks/cartpole_continuous_balancing.py

@@ -13,8 +13,8 @@
     ActionSpace,
     Observation,
     ObservationSpace,
-    Reward,
     ResetReturn,
+    Reward,
 )
 
 from scenario import core as scenario
@@ -125,7 +125,7 @@ def is_terminated(self) -> bool:
         terminated = not self.reset_space.contains(observation)
 
         return terminated
-    
+
     def is_truncated(self) -> bool:
         return False
 

python/gym_gz_environments/tasks/cartpole_continuous_swingup.py

@@ -128,7 +128,7 @@ def is_terminated(self) -> bool:
         terminated = not self.reset_space.contains(observation)
 
         return terminated
-    
+
     def is_truncated(self) -> bool:
         return False
 

python/gym_gz_environments/tasks/cartpole_discrete_balancing.py

@@ -124,7 +124,7 @@ def is_terminated(self) -> bool:
         terminated = not self.reset_space.contains(observation)
 
         return terminated
-    
+
     def is_truncated(self) -> bool:
         return False
 

python/gym_gz_environments/tasks/pendulum_swingup.py

@@ -99,14 +99,14 @@ def is_terminated(self) -> bool:
         terminated = not self.observation_space.contains(observation)
 
         return terminated
-    
+
     def is_truncated(self) -> bool:
         return False
 
     def reset_task(self) -> None:
 
         if self.model_name not in self.world.model_names():
-            raise RuntimeError("The cartpole model was not inserted in the world")
+            raise RuntimeError("The pendulum model was not inserted in the world")
 
         # Get the model
         model = self.world.get_model(self.model_name)

scenario/bindings/__init__.py

@@ -212,9 +212,7 @@ def import_gazebo() -> None:
 def create_home_dot_folder() -> None:
 
     # Make sure that the dot folder in the user's home exists
-    Path("~/.gz/gazebo").expanduser().mkdir(
-        mode=0o755, parents=True, exist_ok=True
-    )
+    Path("~/.gz/gazebo").expanduser().mkdir(mode=0o755, parents=True, exist_ok=True)
 
 
 # ===================

tests/.python/test_pendulum_wrt_ground_truth.py

@@ -2,16 +2,17 @@
 # This software may be modified and distributed under the terms of the
 # GNU Lesser General Public License v2.1 or any later version.
 
+from typing import Dict, Optional
+
 import gymnasium as gym
 import numpy as np
 import pytest
-from gymnasium.envs import registry
-from gymnasium.envs.registration import register
 from gym_gz.robots.sim import gazebo, pybullet
 from gym_gz.tasks.pendulum_swingup import PendulumSwingUp
 from gym_gz.utils import logger
-from gym_gz.utils.typing import Observation, Reward, State 
-from typing import Dict, Optional
+from gym_gz.utils.typing import Observation, Reward, State
+from gymnasium.envs import registry
+from gymnasium.envs.registration import register
 
 # Set verbosity
 logger.set_level(gym.logger.DEBUG)
@@ -70,7 +71,7 @@ def step(self, action: np.ndarray) -> State:
 
         return State((Observation(observation), Reward(0.0), False, {}))
 
-    def reset(self, seed: int = None, options: Dict ={}, **kwargs):
+    def reset(self, seed: int = None, options: Dict = {}, **kwargs):
         # Use set_state_from_obs
         pass
 
@@ -134,7 +135,6 @@ def template_pendulum_wrt_ground_truth(env_name: str, max_error_in_deg: float):
     # env.render('human')
     # time.sleep(5)
 
-
     for epoch in range(10):
         # Reset the environment
         logger.info("Resetting the environment")

tests/.python/test_runtimes.py

@@ -5,12 +5,12 @@
 import gymnasium as gym
 import numpy as np
 import pytest
-from gymnasium.envs import registry
-from gymnasium.envs.registration import register
 from gym_gz.robots.sim import gazebo, pybullet
 from gym_gz.tasks.cartpole_discrete import CartPoleDiscrete
 from gym_gz.tasks.pendulum_swingup import PendulumSwingUp
 from gym_gz.utils import logger
+from gymnasium.envs import registry
+from gymnasium.envs.registration import register
 
 # Set verbosity
 logger.set_level(gym.logger.DEBUG)
@@ -49,9 +49,7 @@
         },
     )
 
-if "CartPoleDiscrete-Gz-PyTest-v0" not in [
-    spec.id for spec in list(registry.all())
-]:
+if "CartPoleDiscrete-Gz-PyTest-v0" not in [spec.id for spec in list(registry.all())]:
     register(
         id="CartPoleDiscrete-Gz-PyTest-v0",
         entry_point="gym_gz.runtimes.gazebo_runtime:GazeboRuntime",

tests/test_gym_gz/test_reproducibility.py

@@ -16,8 +16,8 @@
 
 def make_env(**kwargs) -> gym.Env:
 
-    import gymnasium as gym
     import gym_gz_environments
+    import gymnasium as gym
 
     return gym.make("CartPoleDiscreteBalancing-Gazebo-v0", **kwargs)
 

tests/test_scenario/test_link_velocities.py

@@ -264,7 +264,6 @@ def test_linear_acceleration(
         if (np.absolute(np.array(world_linear_acceleration())) > 100.0).any():
             continue
 
-
         # Test the world acceleration (MIXED)
         assert world_linear_acceleration() == pytest.approx(world_acceleration, abs=0.5)
 

tests/test_scenario/test_model.py

@@ -33,9 +33,7 @@ def get_model(
 
     model_urdf = gym_gz_models.get_model_file(gym_gz_models_name)
 
-    assert world.insert_model(
-        model_urdf, core.Pose_identity(), gym_gz_models_name
-    )
+    assert world.insert_model(model_urdf, core.Pose_identity(), gym_gz_models_name)
 
     # Get the model and cast it to a Gazebo model
     model = world.get_model(gym_gz_models_name).to_gazebo()