Naming change: gym_minigrid->minigrid (#238)

.github/ISSUE_TEMPLATE/bug.md

@@ -15,7 +15,7 @@ Please try to provide a minimal example to reproduce the bug. Error messages and
 
 **System Info**
 Describe the characteristic of your environment:
- * Describe how `gym-minigrid` was installed (pip, docker, source, ...)
+ * Describe how `minigrid` was installed (pip, docker, source, ...)
  * What OS/version of Linux you're using. Note that while we will accept PRs to improve Window's support, we do not officially support it.
  * Python version
 
@@ -24,4 +24,4 @@ Add any other context about the problem here.
 
 ### Checklist
 
-- [ ] I have checked that there is no similar [issue](https://github.com/Farama-Foundation/gym-minigrid/issues) in the repo (**required**)
+- [ ] I have checked that there is no similar [issue](https://github.com/Farama-Foundation/MiniGrid/issues) in the repo (**required**)

.github/ISSUE_TEMPLATE/proposal.md

@@ -30,4 +30,4 @@ Add any other context or screenshots about the feature request here.
 
 ### Checklist
 
-- [ ] I have checked that there is no similar [issue](https://github.com/Farama-Foundation/gym-minigrid/issues) in the repo (**required**)
+- [ ] I have checked that there is no similar [issue](https://github.com/Farama-Foundation/MiniGrid/issues) in the repo (**required**)

.github/workflows/build.yml

@@ -12,6 +12,6 @@ jobs:
       - run: |
            docker build -f py.Dockerfile \
              --build-arg PYTHON_VERSION=${{ matrix.python-version }} \
-             --tag gym-minigrid-docker .      
+             --tag minigrid-docker .      
       - name: Run tests
-        run: docker run gym-minigrid-docker pytest
+        run: docker run minigrid-docker pytest

README.md

@@ -19,13 +19,13 @@ Requirements:
 Please use this bibtex if you want to cite this repository in your publications:
 
 ```
-@misc{gym_minigrid,
+@misc{minigrid,
   author = {Chevalier-Boisvert, Maxime and Willems, Lucas and Pal, Suman},
-  title = {Minimalistic Gridworld Environment for OpenAI Gym},
+  title = {Minimalistic Gridworld Environment for Gymnasium},
   year = {2018},
   publisher = {GitHub},
   journal = {GitHub repository},
-  howpublished = {\url{https://github.com/maximecb/gym-minigrid}},
+  howpublished = {\url{https://github.com/Farama-Foundation/MiniGrid}},
 }
 ```
 
@@ -75,18 +75,18 @@ This environment has been built as part of work done at [Mila](https://mila.queb
 
 ## Installation
 
-There is now a [pip package](https://pypi.org/project/gym-minigrid/) available, which is updated periodically:
+There is now a [pip package](https://pypi.org/project/minigrid/) available, which is updated periodically:
 
 ```
-pip3 install gym-minigrid
+pip install minigrid
 ```
 
 Alternatively, to get the latest version of MiniGrid, you can clone this repository and install the dependencies with `pip3`:
 
 ```
-git clone https://github.com/maximecb/gym-minigrid.git
-cd gym-minigrid
-pip3 install -e .
+git clone https://github.com/Farama-Foundation/MiniGrid
+cd MiniGrid
+pip install -e .
 ```
 
 ## Basic Usage
@@ -94,13 +94,13 @@ pip3 install -e .
 There is a UI application which allows you to manually control the agent with the arrow keys:
 
 ```
-./gym-minigrid/manual_control.py
+./minigrid/manual_control.py
 ```
 
 The environment being run can be selected with the `--env` option, eg:
 
 ```
-./gym-minigrid/manual_control.py --env MiniGrid-Empty-8x8-v0
+./minigrid/manual_control.py --env MiniGrid-Empty-8x8-v0
 ```
 
 ## Reinforcement Learning
@@ -125,7 +125,7 @@ field which can be used as an optional compass. Using dictionaries makes it
 easy for you to add additional information to observations
 if you need to, without having to encode everything into a single tensor.
 
-There are a variety of wrappers to change the observation format available in [gym_minigrid/wrappers.py](/gym_minigrid/wrappers.py). 
+There are a variety of wrappers to change the observation format available in [minigrid/wrappers.py](/minigrid/wrappers.py). 
 If your RL code expects one single tensor for observations, take a look at `FlatObsWrapper`. 
 There is also an `ImgObsWrapper` that gets rid of the 'mission' field in observations, leaving only the image field tensor.
 
@@ -136,7 +136,7 @@ use the `RGBImgPartialObsWrapper`. You can use it as follows:
 
 ```python
 import gym
-from gym_minigrid.wrappers import RGBImgPartialObsWrapper, ImgObsWrapper
+from minigrid.wrappers import RGBImgPartialObsWrapper, ImgObsWrapper
 
 env = gym.make('MiniGrid-Empty-8x8-v0')
 env = RGBImgPartialObsWrapper(env) # Get pixel observations
@@ -167,7 +167,7 @@ Actions in the basic environment:
 
 Default tile/observation encoding:
 - Each tile is encoded as a 3 dimensional tuple: `(OBJECT_IDX, COLOR_IDX, STATE)` 
-- `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+- `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in [minigrid/minigrid.py](minigrid/minigrid.py)
 - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
 By default, sparse rewards are given for reaching a green goal tile. A
@@ -176,11 +176,11 @@ environment-specific time step limit for completing the task.
 You can define your own reward function by creating a class derived
 from `MiniGridEnv`. Extending the environment with new object types or new actions
 should be very easy. If you wish to do this, you should take a look at the
-[gym_minigrid/minigrid.py](gym_minigrid/minigrid.py) source file.
+[minigrid/minigrid.py](minigrid/minigrid.py) source file.
 
 ## Included Environments
 
-The environments listed below are implemented in the [gym_minigrid/envs](/gym_minigrid/envs) directory.
+The environments listed below are implemented in the [minigrid/envs](/minigrid/envs) directory.
 Each environment provides one or more configurations registered with OpenAI gym. Each environment
 is also programmatically tunable in terms of size/complexity, which is useful for curriculum learning
 or to fine-tune difficulty.

gym_minigrid/envs/__init__.py

@@ -1,25 +0,0 @@
-from gym_minigrid.envs.blockedunlockpickup import BlockedUnlockPickupEnv
-from gym_minigrid.envs.crossing import CrossingEnv
-from gym_minigrid.envs.distshift import DistShiftEnv
-from gym_minigrid.envs.doorkey import DoorKeyEnv
-from gym_minigrid.envs.dynamicobstacles import DynamicObstaclesEnv
-from gym_minigrid.envs.empty import EmptyEnv
-from gym_minigrid.envs.fetch import FetchEnv
-from gym_minigrid.envs.fourrooms import FourRoomsEnv
-from gym_minigrid.envs.gotodoor import GoToDoorEnv
-from gym_minigrid.envs.gotoobject import GoToObjectEnv
-from gym_minigrid.envs.keycorridor import KeyCorridorEnv
-from gym_minigrid.envs.lavagap import LavaGapEnv
-from gym_minigrid.envs.lockedroom import LockedRoom, LockedRoomEnv
-from gym_minigrid.envs.memory import MemoryEnv
-from gym_minigrid.envs.multiroom import MultiRoom, MultiRoomEnv
-from gym_minigrid.envs.obstructedmaze import (
-    ObstructedMaze_1Dlhb,
-    ObstructedMaze_Full,
-    ObstructedMazeEnv,
-)
-from gym_minigrid.envs.playground import PlaygroundEnv
-from gym_minigrid.envs.putnear import PutNearEnv
-from gym_minigrid.envs.redbluedoors import RedBlueDoorEnv
-from gym_minigrid.envs.unlock import UnlockEnv
-from gym_minigrid.envs.unlockpickup import UnlockPickupEnv

gym_minigrid/__init__.py

@@ -1,6 +1,6 @@
 from gym.envs.registration import register
 
-from gym_minigrid import minigrid, roomgrid, wrappers
+from minigrid import minigrid, roomgrid, wrappers
 
 
 def register_minigrid_envs():
@@ -9,32 +9,32 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-BlockedUnlockPickup-v0",
-        entry_point="gym_minigrid.envs:BlockedUnlockPickupEnv",
+        entry_point="minigrid.envs:BlockedUnlockPickupEnv",
     )
 
     # LavaCrossing
     # ----------------------------------------
     register(
         id="MiniGrid-LavaCrossingS9N1-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 1},
     )
 
     register(
         id="MiniGrid-LavaCrossingS9N2-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 2},
     )
 
     register(
         id="MiniGrid-LavaCrossingS9N3-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 3},
     )
 
     register(
         id="MiniGrid-LavaCrossingS11N5-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 11, "num_crossings": 5},
     )
 
@@ -43,25 +43,25 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-SimpleCrossingS9N1-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 1, "obstacle_type": minigrid.Wall},
     )
 
     register(
         id="MiniGrid-SimpleCrossingS9N2-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 2, "obstacle_type": minigrid.Wall},
     )
 
     register(
         id="MiniGrid-SimpleCrossingS9N3-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 9, "num_crossings": 3, "obstacle_type": minigrid.Wall},
     )
 
     register(
         id="MiniGrid-SimpleCrossingS11N5-v0",
-        entry_point="gym_minigrid.envs:CrossingEnv",
+        entry_point="minigrid.envs:CrossingEnv",
         kwargs={"size": 11, "num_crossings": 5, "obstacle_type": minigrid.Wall},
     )
 
@@ -70,13 +70,13 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-DistShift1-v0",
-        entry_point="gym_minigrid.envs:DistShiftEnv",
+        entry_point="minigrid.envs:DistShiftEnv",
         kwargs={"strip2_row": 2},
     )
 
     register(
         id="MiniGrid-DistShift2-v0",
-        entry_point="gym_minigrid.envs:DistShiftEnv",
+        entry_point="minigrid.envs:DistShiftEnv",
         kwargs={"strip2_row": 5},
     )
 
@@ -85,25 +85,25 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-DoorKey-5x5-v0",
-        entry_point="gym_minigrid.envs:DoorKeyEnv",
+        entry_point="minigrid.envs:DoorKeyEnv",
         kwargs={"size": 5},
     )
 
     register(
         id="MiniGrid-DoorKey-6x6-v0",
-        entry_point="gym_minigrid.envs:DoorKeyEnv",
+        entry_point="minigrid.envs:DoorKeyEnv",
         kwargs={"size": 5},
     )
 
     register(
         id="MiniGrid-DoorKey-8x8-v0",
-        entry_point="gym_minigrid.envs:DoorKeyEnv",
+        entry_point="minigrid.envs:DoorKeyEnv",
         kwargs={"size": 8},
     )
 
     register(
         id="MiniGrid-DoorKey-16x16-v0",
-        entry_point="gym_minigrid.envs:DoorKeyEnv",
+        entry_point="minigrid.envs:DoorKeyEnv",
         kwargs={"size": 16},
     )
 
@@ -112,36 +112,36 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-Dynamic-Obstacles-5x5-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
         kwargs={"size": 5, "n_obstacles": 2},
     )
 
     register(
         id="MiniGrid-Dynamic-Obstacles-Random-5x5-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
         kwargs={"size": 5, "agent_start_pos": None, "n_obstacles": 2},
     )
 
     register(
         id="MiniGrid-Dynamic-Obstacles-6x6-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
         kwargs={"size": 6, "n_obstacles": 3},
     )
 
     register(
         id="MiniGrid-Dynamic-Obstacles-Random-6x6-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
         kwargs={"size": 6, "agent_start_pos": None, "n_obstacles": 3},
     )
 
     register(
         id="MiniGrid-Dynamic-Obstacles-8x8-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
     )
 
     register(
         id="MiniGrid-Dynamic-Obstacles-16x16-v0",
-        entry_point="gym_minigrid.envs:DynamicObstaclesEnv",
+        entry_point="minigrid.envs:DynamicObstaclesEnv",
         kwargs={"size": 16, "n_obstacles": 8},
     )
 
@@ -150,36 +150,36 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-Empty-5x5-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
         kwargs={"size": 5},
     )
 
     register(
         id="MiniGrid-Empty-Random-5x5-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
         kwargs={"size": 5, "agent_start_pos": None},
     )
 
     register(
         id="MiniGrid-Empty-6x6-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
         kwargs={"size": 6},
     )
 
     register(
         id="MiniGrid-Empty-Random-6x6-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
         kwargs={"size": 6, "agent_start_pos": None},
     )
 
     register(
         id="MiniGrid-Empty-8x8-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
     )
 
     register(
         id="MiniGrid-Empty-16x16-v0",
-        entry_point="gym_minigrid.envs:EmptyEnv",
+        entry_point="minigrid.envs:EmptyEnv",
         kwargs={"size": 16},
     )
 
@@ -188,24 +188,24 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-Fetch-5x5-N2-v0",
-        entry_point="gym_minigrid.envs:FetchEnv",
+        entry_point="minigrid.envs:FetchEnv",
         kwargs={"size": 5, "numObjs": 2},
     )
 
     register(
         id="MiniGrid-Fetch-6x6-N2-v0",
-        entry_point="gym_minigrid.envs:FetchEnv",
+        entry_point="minigrid.envs:FetchEnv",
         kwargs={"size": 6, "numObjs": 2},
     )
 
-    register(id="MiniGrid-Fetch-8x8-N3-v0", entry_point="gym_minigrid.envs:FetchEnv")
+    register(id="MiniGrid-Fetch-8x8-N3-v0", entry_point="minigrid.envs:FetchEnv")
 
     # FourRooms
     # ----------------------------------------
 
     register(
         id="MiniGrid-FourRooms-v0",
-        entry_point="gym_minigrid.envs:FourRoomsEnv",
+        entry_point="minigrid.envs:FourRoomsEnv",
     )
 
     # GoToDoor
@@ -213,18 +213,18 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-GoToDoor-5x5-v0",
-        entry_point="gym_minigrid.envs:GoToDoorEnv",
+        entry_point="minigrid.envs:GoToDoorEnv",
     )
 
     register(
         id="MiniGrid-GoToDoor-6x6-v0",
-        entry_point="gym_minigrid.envs:GoToDoorEnv",
+        entry_point="minigrid.envs:GoToDoorEnv",
         kwargs={"size": 6},
     )
 
     register(
         id="MiniGrid-GoToDoor-8x8-v0",
-        entry_point="gym_minigrid.envs:GoToDoorEnv",
+        entry_point="minigrid.envs:GoToDoorEnv",
         kwargs={"size": 8},
     )
 
@@ -233,12 +233,12 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-GoToObject-6x6-N2-v0",
-        entry_point="gym_minigrid.envs:GoToObjectEnv",
+        entry_point="minigrid.envs:GoToObjectEnv",
     )
 
     register(
         id="MiniGrid-GoToObject-8x8-N2-v0",
-        entry_point="gym_minigrid.envs:GoToObjectEnv",
+        entry_point="minigrid.envs:GoToObjectEnv",
         kwargs={"size": 8, "numObjs": 2},
     )
 
@@ -247,37 +247,37 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-KeyCorridorS3R1-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 3, "num_rows": 1},
     )
 
     register(
         id="MiniGrid-KeyCorridorS3R2-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 3, "num_rows": 2},
     )
 
     register(
         id="MiniGrid-KeyCorridorS3R3-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 3, "num_rows": 3},
     )
 
     register(
         id="MiniGrid-KeyCorridorS4R3-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 4, "num_rows": 3},
     )
 
     register(
         id="MiniGrid-KeyCorridorS5R3-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 5, "num_rows": 3},
     )
 
     register(
         id="MiniGrid-KeyCorridorS6R3-v0",
-        entry_point="gym_minigrid.envs:KeyCorridorEnv",
+        entry_point="minigrid.envs:KeyCorridorEnv",
         kwargs={"room_size": 6, "num_rows": 3},
     )
 
@@ -286,19 +286,19 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-LavaGapS5-v0",
-        entry_point="gym_minigrid.envs:LavaGapEnv",
+        entry_point="minigrid.envs:LavaGapEnv",
         kwargs={"size": 5},
     )
 
     register(
         id="MiniGrid-LavaGapS6-v0",
-        entry_point="gym_minigrid.envs:LavaGapEnv",
+        entry_point="minigrid.envs:LavaGapEnv",
         kwargs={"size": 6},
     )
 
     register(
         id="MiniGrid-LavaGapS7-v0",
-        entry_point="gym_minigrid.envs:LavaGapEnv",
+        entry_point="minigrid.envs:LavaGapEnv",
         kwargs={"size": 7},
     )
 
@@ -307,7 +307,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-LockedRoom-v0",
-        entry_point="gym_minigrid.envs:LockedRoomEnv",
+        entry_point="minigrid.envs:LockedRoomEnv",
     )
 
     # Memory
@@ -315,37 +315,37 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-MemoryS17Random-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 17, "random_length": True},
     )
 
     register(
         id="MiniGrid-MemoryS13Random-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 13, "random_length": True},
     )
 
     register(
         id="MiniGrid-MemoryS13-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 13},
     )
 
     register(
         id="MiniGrid-MemoryS11-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 11},
     )
 
     register(
         id="MiniGrid-MemoryS9-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 9},
     )
 
     register(
         id="MiniGrid-MemoryS7-v0",
-        entry_point="gym_minigrid.envs:MemoryEnv",
+        entry_point="minigrid.envs:MemoryEnv",
         kwargs={"size": 7},
     )
 
@@ -354,19 +354,19 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-MultiRoom-N2-S4-v0",
-        entry_point="gym_minigrid.envs:MultiRoomEnv",
+        entry_point="minigrid.envs:MultiRoomEnv",
         kwargs={"minNumRooms": 2, "maxNumRooms": 2, "maxRoomSize": 4},
     )
 
     register(
         id="MiniGrid-MultiRoom-N4-S5-v0",
-        entry_point="gym_minigrid.envs:MultiRoomEnv",
+        entry_point="minigrid.envs:MultiRoomEnv",
         kwargs={"minNumRooms": 6, "maxNumRooms": 6, "maxRoomSize": 5},
     )
 
     register(
         id="MiniGrid-MultiRoom-N6-v0",
-        entry_point="gym_minigrid.envs:MultiRoomEnv",
+        entry_point="minigrid.envs:MultiRoomEnv",
         kwargs={"minNumRooms": 6, "maxNumRooms": 6},
     )
 
@@ -375,24 +375,24 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-1Dl-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_1Dlhb",
+        entry_point="minigrid.envs:ObstructedMaze_1Dlhb",
         kwargs={"key_in_box": False, "blocked": False},
     )
 
     register(
         id="MiniGrid-ObstructedMaze-1Dlh-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_1Dlhb",
+        entry_point="minigrid.envs:ObstructedMaze_1Dlhb",
         kwargs={"key_in_box": True, "blocked": False},
     )
 
     register(
         id="MiniGrid-ObstructedMaze-1Dlhb-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_1Dlhb",
+        entry_point="minigrid.envs:ObstructedMaze_1Dlhb",
     )
 
     register(
         id="MiniGrid-ObstructedMaze-2Dl-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
         kwargs={
             "agent_room": (2, 1),
             "key_in_box": False,
@@ -404,7 +404,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-2Dlh-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
         kwargs={
             "agent_room": (2, 1),
             "key_in_box": True,
@@ -416,7 +416,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-2Dlhb-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
         kwargs={
             "agent_room": (2, 1),
             "key_in_box": True,
@@ -428,7 +428,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-1Q-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
         kwargs={
             "agent_room": (1, 1),
             "key_in_box": True,
@@ -440,7 +440,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-2Q-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
         kwargs={
             "agent_room": (2, 1),
             "key_in_box": True,
@@ -452,7 +452,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-ObstructedMaze-Full-v0",
-        entry_point="gym_minigrid.envs:ObstructedMaze_Full",
+        entry_point="minigrid.envs:ObstructedMaze_Full",
     )
 
     # Playground
@@ -460,7 +460,7 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-Playground-v0",
-        entry_point="gym_minigrid.envs:PlaygroundEnv",
+        entry_point="minigrid.envs:PlaygroundEnv",
     )
 
     # PutNear
@@ -468,12 +468,12 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-PutNear-6x6-N2-v0",
-        entry_point="gym_minigrid.envs:PutNearEnv",
+        entry_point="minigrid.envs:PutNearEnv",
     )
 
     register(
         id="MiniGrid-PutNear-8x8-N3-v0",
-        entry_point="gym_minigrid.envs:PutNearEnv",
+        entry_point="minigrid.envs:PutNearEnv",
         kwargs={"size": 8, "numObjs": 3},
     )
 
@@ -482,24 +482,24 @@ def register_minigrid_envs():
 
     register(
         id="MiniGrid-RedBlueDoors-6x6-v0",
-        entry_point="gym_minigrid.envs:RedBlueDoorEnv",
+        entry_point="minigrid.envs:RedBlueDoorEnv",
         kwargs={"size": 6},
     )
 
     register(
         id="MiniGrid-RedBlueDoors-8x8-v0",
-        entry_point="gym_minigrid.envs:RedBlueDoorEnv",
+        entry_point="minigrid.envs:RedBlueDoorEnv",
     )
 
     # Unlock
     # ----------------------------------------
 
-    register(id="MiniGrid-Unlock-v0", entry_point="gym_minigrid.envs:UnlockEnv")
+    register(id="MiniGrid-Unlock-v0", entry_point="minigrid.envs:UnlockEnv")
 
     # UnlockPickup
     # ----------------------------------------
 
     register(
         id="MiniGrid-UnlockPickup-v0",
-        entry_point="gym_minigrid.envs:UnlockPickupEnv",
+        entry_point="minigrid.envs:UnlockPickupEnv",
     )

gym_minigrid/benchmark.py

@@ -4,7 +4,7 @@ import time
 
 import gym
 
-from gym_minigrid.wrappers import ImgObsWrapper, RGBImgPartialObsWrapper
+from minigrid.wrappers import ImgObsWrapper, RGBImgPartialObsWrapper
 
 
 def benchmark(env_id, num_resets, num_frames):

minigrid/envs/__init__.py

@@ -0,0 +1,25 @@
+from minigrid.envs.blockedunlockpickup import BlockedUnlockPickupEnv
+from minigrid.envs.crossing import CrossingEnv
+from minigrid.envs.distshift import DistShiftEnv
+from minigrid.envs.doorkey import DoorKeyEnv
+from minigrid.envs.dynamicobstacles import DynamicObstaclesEnv
+from minigrid.envs.empty import EmptyEnv
+from minigrid.envs.fetch import FetchEnv
+from minigrid.envs.fourrooms import FourRoomsEnv
+from minigrid.envs.gotodoor import GoToDoorEnv
+from minigrid.envs.gotoobject import GoToObjectEnv
+from minigrid.envs.keycorridor import KeyCorridorEnv
+from minigrid.envs.lavagap import LavaGapEnv
+from minigrid.envs.lockedroom import LockedRoom, LockedRoomEnv
+from minigrid.envs.memory import MemoryEnv
+from minigrid.envs.multiroom import MultiRoom, MultiRoomEnv
+from minigrid.envs.obstructedmaze import (
+    ObstructedMaze_1Dlhb,
+    ObstructedMaze_Full,
+    ObstructedMazeEnv,
+)
+from minigrid.envs.playground import PlaygroundEnv
+from minigrid.envs.putnear import PutNearEnv
+from minigrid.envs.redbluedoors import RedBlueDoorEnv
+from minigrid.envs.unlock import UnlockEnv
+from minigrid.envs.unlockpickup import UnlockPickupEnv

gym_minigrid/envs/blockedunlockpickup.py

@@ -1,5 +1,5 @@
-from gym_minigrid.minigrid import COLOR_NAMES, Ball, MissionSpace
-from gym_minigrid.roomgrid import RoomGrid
+from minigrid.minigrid import COLOR_NAMES, Ball, MissionSpace
+from minigrid.roomgrid import RoomGrid
 
 
 class BlockedUnlockPickupEnv(RoomGrid):
@@ -39,7 +39,7 @@ class BlockedUnlockPickupEnv(RoomGrid):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/crossing.py

@@ -2,7 +2,7 @@ import itertools as itt
 
 import numpy as np
 
-from gym_minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
 
 
 class CrossingEnv(MiniGridEnv):
@@ -44,7 +44,7 @@ class CrossingEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/distshift.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
 
 
 class DistShiftEnv(MiniGridEnv):
@@ -35,7 +35,7 @@ class DistShiftEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/doorkey.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import Door, Goal, Grid, Key, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Door, Goal, Grid, Key, MiniGridEnv, MissionSpace
 
 
 class DoorKeyEnv(MiniGridEnv):
@@ -32,7 +32,7 @@ class DoorKeyEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/dynamicobstacles.py

@@ -2,7 +2,7 @@ from operator import add
 
 from gym.spaces import Discrete
 
-from gym_minigrid.minigrid import Ball, Goal, Grid, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Ball, Goal, Grid, MiniGridEnv, MissionSpace
 
 
 class DynamicObstaclesEnv(MiniGridEnv):
@@ -37,7 +37,7 @@ class DynamicObstaclesEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/empty.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import Goal, Grid, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Goal, Grid, MiniGridEnv, MissionSpace
 
 
 class EmptyEnv(MiniGridEnv):
@@ -36,7 +36,7 @@ class EmptyEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/fetch.py

@@ -1,11 +1,4 @@
-from gym_minigrid.minigrid import (
-    COLOR_NAMES,
-    Ball,
-    Grid,
-    Key,
-    MiniGridEnv,
-    MissionSpace,
-)
+from minigrid.minigrid import COLOR_NAMES, Ball, Grid, Key, MiniGridEnv, MissionSpace
 
 
 class FetchEnv(MiniGridEnv):
@@ -47,7 +40,7 @@ class FetchEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/fourrooms.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import Goal, Grid, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Goal, Grid, MiniGridEnv, MissionSpace
 
 
 class FourRoomsEnv(MiniGridEnv):
@@ -32,7 +32,7 @@ class FourRoomsEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/gotodoor.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import COLOR_NAMES, Door, Grid, MiniGridEnv, MissionSpace
+from minigrid.minigrid import COLOR_NAMES, Door, Grid, MiniGridEnv, MissionSpace
 
 
 class GoToDoorEnv(MiniGridEnv):
@@ -36,7 +36,7 @@ class GoToDoorEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/gotoobject.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import (
+from minigrid.minigrid import (
     COLOR_NAMES,
     Ball,
     Box,

gym_minigrid/envs/keycorridor.py

@@ -1,5 +1,5 @@
-from gym_minigrid.minigrid import COLOR_NAMES, MissionSpace
-from gym_minigrid.roomgrid import RoomGrid
+from minigrid.minigrid import COLOR_NAMES, MissionSpace
+from minigrid.roomgrid import RoomGrid
 
 
 class KeyCorridorEnv(RoomGrid):
@@ -41,7 +41,7 @@ class KeyCorridorEnv(RoomGrid):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/lavagap.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from gym_minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Goal, Grid, Lava, MiniGridEnv, MissionSpace
 
 
 class LavaGapEnv(MiniGridEnv):
@@ -36,7 +36,7 @@ class LavaGapEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/lockedroom.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import (
+from minigrid.minigrid import (
     COLOR_NAMES,
     Door,
     Goal,
@@ -59,7 +59,7 @@ class LockedRoomEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/memory.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from gym_minigrid.minigrid import Ball, Grid, Key, MiniGridEnv, MissionSpace, Wall
+from minigrid.minigrid import Ball, Grid, Key, MiniGridEnv, MissionSpace, Wall
 
 
 class MemoryEnv(MiniGridEnv):
@@ -35,7 +35,7 @@ class MemoryEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/multiroom.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import (
+from minigrid.minigrid import (
     COLOR_NAMES,
     Door,
     Goal,
@@ -49,7 +49,7 @@ class MultiRoomEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/obstructedmaze.py

@@ -1,5 +1,5 @@
-from gym_minigrid.minigrid import COLOR_NAMES, DIR_TO_VEC, Ball, Box, Key, MissionSpace
-from gym_minigrid.roomgrid import RoomGrid
+from minigrid.minigrid import COLOR_NAMES, DIR_TO_VEC, Ball, Box, Key, MissionSpace
+from minigrid.roomgrid import RoomGrid
 
 
 class ObstructedMazeEnv(RoomGrid):
@@ -32,7 +32,7 @@ class ObstructedMazeEnv(RoomGrid):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/playground.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import (
+from minigrid.minigrid import (
     COLOR_NAMES,
     Ball,
     Box,

gym_minigrid/envs/putnear.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import (
+from minigrid.minigrid import (
     COLOR_NAMES,
     Ball,
     Box,
@@ -45,7 +45,7 @@ class PutNearEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/redbluedoors.py

@@ -1,4 +1,4 @@
-from gym_minigrid.minigrid import Door, Grid, MiniGridEnv, MissionSpace
+from minigrid.minigrid import Door, Grid, MiniGridEnv, MissionSpace
 
 
 class RedBlueDoorEnv(MiniGridEnv):
@@ -32,7 +32,7 @@ class RedBlueDoorEnv(MiniGridEnv):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/unlock.py

@@ -1,5 +1,5 @@
-from gym_minigrid.minigrid import MissionSpace
-from gym_minigrid.roomgrid import RoomGrid
+from minigrid.minigrid import MissionSpace
+from minigrid.roomgrid import RoomGrid
 
 
 class UnlockEnv(RoomGrid):
@@ -31,7 +31,7 @@ class UnlockEnv(RoomGrid):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/envs/unlockpickup.py

@@ -1,5 +1,5 @@
-from gym_minigrid.minigrid import COLOR_NAMES, MissionSpace
-from gym_minigrid.roomgrid import RoomGrid
+from minigrid.minigrid import COLOR_NAMES, MissionSpace
+from minigrid.roomgrid import RoomGrid
 
 
 class UnlockPickupEnv(RoomGrid):
@@ -34,7 +34,7 @@ class UnlockPickupEnv(RoomGrid):
     - Each tile is encoded as a 3 dimensional tuple:
         `(OBJECT_IDX, COLOR_IDX, STATE)`
     - `OBJECT_TO_IDX` and `COLOR_TO_IDX` mapping can be found in
-        [gym_minigrid/minigrid.py](gym_minigrid/minigrid.py)
+        [minigrid/minigrid.py](minigrid/minigrid.py)
     - `STATE` refers to the door state with 0=open, 1=closed and 2=locked
 
     ### Rewards

gym_minigrid/manual_control.py

@@ -2,8 +2,8 @@
 
 import gym
 
-from gym_minigrid.window import Window
-from gym_minigrid.wrappers import ImgObsWrapper, RGBImgPartialObsWrapper
+from minigrid.window import Window
+from minigrid.wrappers import ImgObsWrapper, RGBImgPartialObsWrapper
 
 
 def redraw(window, img):
@@ -108,7 +108,7 @@ if __name__ == "__main__":
         env = RGBImgPartialObsWrapper(env)
         env = ImgObsWrapper(env)
 
-    window = Window("gym_minigrid - " + args.env)
+    window = Window("minigrid - " + args.env)
     window.reg_key_handler(lambda event: key_handler(env, window, event))
 
     seed = None if args.seed == -1 else args.seed

gym_minigrid/minigrid.py

@@ -10,7 +10,7 @@ from gym import spaces
 from gym.utils import seeding
 
 # Size in pixels of a tile in the full-scale human view
-from gym_minigrid.rendering import (
+from minigrid.rendering import (
     downsample,
     fill_coords,
     highlight_img,
@@ -20,7 +20,7 @@ from gym_minigrid.rendering import (
     point_in_triangle,
     rotate_fn,
 )
-from gym_minigrid.window import Window
+from minigrid.window import Window
 
 TILE_PIXELS = 32
 
@@ -1525,7 +1525,7 @@ class MiniGridEnv(gym.Env):
 
         if self.render_mode == "human":
             if self.window is None:
-                self.window = Window("gym_minigrid")
+                self.window = Window("minigrid")
                 self.window.show(block=False)
             self.window.set_caption(self.mission)
             self.window.show_img(img)

gym_minigrid/roomgrid.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from gym_minigrid.minigrid import COLOR_NAMES, Ball, Box, Door, Grid, Key, MiniGridEnv
+from minigrid.minigrid import COLOR_NAMES, Ball, Box, Door, Grid, Key, MiniGridEnv
 
 
 def reject_next_to(env, pos):

gym_minigrid/wrappers.py

@@ -7,7 +7,7 @@ import numpy as np
 from gym import spaces
 from gym.core import ObservationWrapper, Wrapper
 
-from gym_minigrid.minigrid import COLOR_TO_IDX, OBJECT_TO_IDX, STATE_TO_IDX, Goal
+from minigrid.minigrid import COLOR_TO_IDX, OBJECT_TO_IDX, STATE_TO_IDX, Goal
 
 
 class ReseedWrapper(Wrapper):

py.Dockerfile

@@ -6,7 +6,7 @@ SHELL ["/bin/bash", "-o", "pipefail", "-c"]
 
 RUN apt-get -y update
 
-COPY . /usr/local/gym_minigrid/
-WORKDIR /usr/local/gym_minigrid/
+COPY . /usr/local/minigrid/
+WORKDIR /usr/local/minigrid/
 
 RUN pip install .[testing] --no-cache-dir

pyproject.toml

@@ -1,7 +1,7 @@
 [tool.pyright]
 
 include = [
-    "gym_minigrid/**",
+    "minigrid/**",
 ]
 
 exclude = [

setup.py

@@ -15,7 +15,7 @@ with open("README.md") as fh:
 extras = {"testing": ["pytest==7.0.1"]}
 
 setup(
-    name="gym_minigrid",
+    name="MiniGrid",
     author="Farama Foundation",
     author_email="jkterry@farama.org",
     classifiers=[
@@ -28,13 +28,11 @@ setup(
     ],
     version="1.2.1",
     keywords="memory, environment, agent, rl, gym",
-    url="https://github.com/Farama-Foundation/gym-minigrid",
+    url="https://github.com/Farama-Foundation/MiniGrid",
     description="Minimalistic gridworld reinforcement learning environments",
     extras_require=extras,
-    packages=["gym_minigrid", "gym_minigrid.envs"],
-    entry_points={
-        "gym.envs": ["__root__ = gym_minigrid.__init__:register_minigrid_envs"]
-    },
+    packages=["minigrid", "minigrid.envs"],
+    entry_points={"gym.envs": ["__root__ = minigrid.__init__:register_minigrid_envs"]},
     license="Apache",
     long_description=long_description,
     long_description_content_type="text/markdown",

tests/test_envs.py

@@ -6,7 +6,7 @@ import pytest
 from gym.envs.registration import EnvSpec
 from gym.utils.env_checker import check_env
 
-from gym_minigrid.minigrid import Grid, MissionSpace
+from minigrid.minigrid import Grid, MissionSpace
 from tests.utils import all_testing_env_specs, assert_equals
 
 CHECK_ENV_IGNORE_WARNINGS = [

tests/test_scripts.py

@@ -1,9 +1,9 @@
 import gym
 import numpy as np
 
-from gym_minigrid.benchmark import benchmark
-from gym_minigrid.manual_control import key_handler, reset
-from gym_minigrid.window import Window
+from minigrid.benchmark import benchmark
+from minigrid.manual_control import key_handler, reset
+from minigrid.window import Window
 
 
 def test_benchmark():

tests/test_wrappers.py

@@ -4,9 +4,9 @@ import gym
 import numpy as np
 import pytest
 
-from gym_minigrid.envs import EmptyEnv
-from gym_minigrid.minigrid import MiniGridEnv
-from gym_minigrid.wrappers import (
+from minigrid.envs import EmptyEnv
+from minigrid.minigrid import MiniGridEnv
+from minigrid.wrappers import (
     ActionBonus,
     DictObservationSpaceWrapper,
     FlatObsWrapper,

tests/utils.py

@@ -5,7 +5,7 @@ import numpy as np
 all_testing_env_specs = [
     env_spec
     for env_spec in gym.envs.registry.values()
-    if env_spec.entry_point.startswith("gym_minigrid.envs")
+    if env_spec.entry_point.startswith("minigrid.envs")
 ]