Improve pre-commit workflow (#2602)

* feat: add `isort` to `pre-commit`

* ci: skip `__init__.py` file for `isort`

* ci: make `isort` mandatory in lint pipeline

* docs: add a section on Git hooks

* ci: check isort diff

* fix: isort from master branch

* docs: add pre-commit badge

* ci: update black + bandit versions

* feat: add PR template

* refactor: PR template

* ci: remove bandit

* docs: add Black badge

* ci: try to remove all `|| true` statements

* ci: remove lint_python job

- Remove `lint_python` CI job
- Move `pyupgrade` job to `pre-commit` workflow

* fix: avoid messing with typing

* docs: add a note on running `pre-cpmmit` manually

* ci: apply `pre-commit` to the whole codebase

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,45 @@
+# Description
+
+Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
+
+Fixes # (issue)
+
+## Type of change
+
+Please delete options that are not relevant.
+
+- [ ] Bug fix (non-breaking change which fixes an issue)
+- [ ] New feature (non-breaking change which adds functionality)
+- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
+- [ ] This change requires a documentation update
+
+### Screenshots
+Please attach before and after screenshots of the change if applicable.
+
+<!--
+Example:
+
+| Before | After |
+| ------ | ----- |
+| _gif/png before_ | _gif/png after_ |
+
+
+To upload images to a PR -- simply drag and drop an image while in edit mode and it should upload the image directly. You can then paste that source into the above before/after sections.
+-->
+
+# Checklist:
+
+- [ ] I have run the [`pre-commit` checks](https://pre-commit.com/) with `pre-commit run --all-files` (see `CONTRIBUTING.md` instructions to set it up)
+- [ ] I have commented my code, particularly in hard-to-understand areas
+- [ ] I have made corresponding changes to the documentation
+- [ ] My changes generate no new warnings
+- [ ] I have added tests that prove my fix is effective or that my feature works
+- [ ] New and existing unit tests pass locally with my changes
+
+<!--
+As you go through the checklist above, you can mark something as done by putting an x character in it
+
+For example,
+- [x] I have done this task
+- [ ] I have not done this task
+-->

.github/workflows/lint_python.yml

@@ -1,25 +1,14 @@
+---
 name: lint_python
 on: [pull_request, push]
 jobs:
-  lint_python:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
-      - run: pip install isort pytest pyupgrade safety
-      - run: isort --check-only --profile black . || true
-      - run: pip install -e .[nomujoco]
-      - run: pytest . || true
-      - run: pytest --doctest-modules . || true
-      - run: shopt -s globstar && pyupgrade --py36-plus **/*.py || true
-
   pyright:
     name: Check types with pyright
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-platform: [ "Linux" ]
-        python-version: [ "3.7"]
+        python-platform: ["Linux"]
+        python-version: ["3.7"]
       fail-fast: false
     env:
       PYRIGHT_VERSION: 1.1.204

.pre-commit-config.yaml

@@ -1,15 +1,7 @@
+---
 repos:
-  - repo: https://github.com/PyCQA/bandit/
-    rev: 1.7.0
-    hooks:
-      - id: bandit
-        args:
-          - --recursive
-          - --skip
-          - B101,B108,B301,B403,B404,B603
-          - .
   - repo: https://github.com/python/black
-    rev: 21.7b0
+    rev: 22.1.0
     hooks:
       - id: black
   - repo: https://github.com/codespell-project/codespell
@@ -28,3 +20,14 @@ repos:
           - --max-line-length=456
           - --show-source
           - --statistics
+  - repo: https://github.com/PyCQA/isort
+    rev: 5.10.1
+    hooks:
+      - id: isort
+        args: ["--profile", "black"]
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v2.31.0
+    hooks:
+      - id: pyupgrade
+        # TODO: remove `--keep-runtime-typing` option
+        args: ["--py37-plus", "--keep-runtime-typing"]

CONTRIBUTING.md

@@ -22,7 +22,7 @@ This section contains technical instructions & hints for the contributors.
 
 ## Type checking
 The project uses `pyright` to check types. 
-To type check locally, install pyright per official [instructions](https://github.com/microsoft/pyright#command-line). 
+To type check locally, install `pyright` per official [instructions](https://github.com/microsoft/pyright#command-line). 
 It's configuration lives under a section of `pyproject.toml`. It includes list of files currently supporting type checks. Use `pyright` CLI command to launch type checks.
 
 ### Adding typing to more modules and packages
@@ -32,3 +32,9 @@ add the path to the file(s) in the include section
 (pyproject.toml -> [tool.pyright] -> include). 
 Then you can run `pyright` to see list of type problems in the newly added file, and fix them.
 
+## Git hooks
+The CI will run several checks on the new code pushed to the Gym repository. These checks can also be run locally without waiting for the CI by following the steps below:
+1. [install `pre-commit`](https://pre-commit.com/#install),
+2. install the Git hooks by running `pre-commit install`.
+
+Once those two steps are done, the Git hooks will be run automatically at every new commit. The Git hooks can also be run manually with `pre-commit run --all-files`, and if needed they can be skipped (not recommended) with `git commit --no-verify`. **Note:** you may have to run `pre-commit run --all-files` manually a couple of times to make it pass when you commit, as each formatting tool will first format the code and fail the first time but should pass the second time.

README.md

@@ -1,3 +1,5 @@
+[![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)
+
 ## Gym
 
 Gym is an open source Python library for developing and comparing reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API. Since its release, Gym's API has become the field standard for doing this.

gym/__init__.py

@@ -1,3 +1,5 @@
+# isort: skip_file
+
 from gym import error
 from gym.version import VERSION as __version__
 

gym/core.py

@@ -1,12 +1,12 @@
 from __future__ import annotations
 
 from abc import abstractmethod
-from typing import TypeVar, Generic, Tuple, Union, Optional, SupportsFloat
+from typing import Generic, Optional, SupportsFloat, Tuple, TypeVar, Union
 
 import gym
 from gym import spaces
-from gym.utils import seeding
 from gym.logger import deprecation
+from gym.utils import seeding
 from gym.utils.seeding import RandomNumberGenerator
 
 ObsType = TypeVar("ObsType")

gym/envs/__init__.py

@@ -1,10 +1,5 @@
-from gym.envs.registration import (
-    registry,
-    register,
-    make,
-    spec,
-    load_env_plugins as _load_env_plugins,
-)
+from gym.envs.registration import load_env_plugins as _load_env_plugins
+from gym.envs.registration import make, register, registry, spec
 
 # Hook to load plugins from entry points
 _load_env_plugins()

gym/envs/box2d/__init__.py

@@ -1,7 +1,8 @@
 try:
     import Box2D
-    from gym.envs.box2d.lunar_lander import LunarLander, LunarLanderContinuous
+
     from gym.envs.box2d.bipedal_walker import BipedalWalker, BipedalWalkerHardcore
     from gym.envs.box2d.car_racing import CarRacing
+    from gym.envs.box2d.lunar_lander import LunarLander, LunarLanderContinuous
 except ImportError:
     Box2D = None

gym/envs/box2d/bipedal_walker.py

@@ -1,27 +1,25 @@
 __credits__ = ["Andrea PIERRÉ"]
 
-import sys
 import math
+import sys
 from typing import Optional
 
+import Box2D
 import numpy as np
 import pygame
-from pygame import gfxdraw
-
-import Box2D
 from Box2D.b2 import (
-    edgeShape,
     circleShape,
+    contactListener,
+    edgeShape,
     fixtureDef,
     polygonShape,
     revoluteJointDef,
-    contactListener,
 )
+from pygame import gfxdraw
 
 import gym
 from gym import error, spaces
-from gym.utils import colorize, seeding, EzPickle
-
+from gym.utils import EzPickle, colorize, seeding
 
 FPS = 50
 SCALE = 30.0  # affects how fast-paced the game is, forces should be adjusted as well
@@ -582,7 +580,7 @@ class BipedalWalker(gym.Env, EzPickle):
                 continue
             scaled_poly = []
             for coord in poly:
-                scaled_poly.append(([coord[0] * SCALE, coord[1] * SCALE]))
+                scaled_poly.append([coord[0] * SCALE, coord[1] * SCALE])
             pygame.draw.polygon(self.surf, color=color, points=scaled_poly)
             gfxdraw.aapolygon(self.surf, scaled_poly, color)
 

gym/envs/box2d/car_dynamics.py

@@ -7,17 +7,18 @@ This simulation is a bit more detailed, with wheels rotation.
 Created by Oleg Klimov
 """
 
-import numpy as np
 import math
-import pygame.draw
+
 import Box2D
+import numpy as np
+import pygame.draw
 from Box2D.b2 import (
-    edgeShape,
     circleShape,
+    contactListener,
+    edgeShape,
     fixtureDef,
     polygonShape,
     revoluteJointDef,
-    contactListener,
     shape,
 )
 

gym/envs/box2d/car_racing.py

@@ -1,22 +1,19 @@
 __credits__ = ["Andrea PIERRÉ"]
 
-import sys
 import math
+import sys
 from typing import Optional
 
+import Box2D
 import numpy as np
 import pygame
+from Box2D.b2 import contactListener, fixtureDef, polygonShape
 from pygame import gfxdraw
 
-import Box2D
-from Box2D.b2 import fixtureDef
-from Box2D.b2 import polygonShape
-from Box2D.b2 import contactListener
-
 import gym
 from gym import spaces
 from gym.envs.box2d.car_dynamics import Car
-from gym.utils import seeding, EzPickle
+from gym.utils import EzPickle, seeding
 
 STATE_W = 96  # less than Atari 160x192
 STATE_H = 96

gym/envs/box2d/lunar_lander.py

@@ -4,23 +4,22 @@ import math
 import sys
 from typing import Optional
 
+import Box2D
 import numpy as np
 import pygame
-from pygame import gfxdraw
-
-import Box2D
 from Box2D.b2 import (
-    edgeShape,
     circleShape,
+    contactListener,
+    edgeShape,
     fixtureDef,
     polygonShape,
     revoluteJointDef,
-    contactListener,
 )
+from pygame import gfxdraw
 
 import gym
 from gym import error, spaces
-from gym.utils import seeding, EzPickle
+from gym.utils import EzPickle, seeding
 
 FPS = 50
 SCALE = 30.0  # affects how fast-paced the game is, forces should be adjusted as well

gym/envs/classic_control/__init__.py

@@ -1,5 +1,5 @@
-from gym.envs.classic_control.cartpole import CartPoleEnv
-from gym.envs.classic_control.mountain_car import MountainCarEnv
-from gym.envs.classic_control.continuous_mountain_car import Continuous_MountainCarEnv
-from gym.envs.classic_control.pendulum import PendulumEnv
 from gym.envs.classic_control.acrobot import AcrobotEnv
+from gym.envs.classic_control.cartpole import CartPoleEnv
+from gym.envs.classic_control.continuous_mountain_car import Continuous_MountainCarEnv
+from gym.envs.classic_control.mountain_car import MountainCarEnv
+from gym.envs.classic_control.pendulum import PendulumEnv

gym/envs/classic_control/acrobot.py

@@ -3,8 +3,8 @@ from typing import Optional
 
 import numpy as np
 import pygame
+from numpy import cos, pi, sin
 from pygame import gfxdraw
-from numpy import sin, cos, pi
 
 from gym import core, spaces
 from gym.utils import seeding
@@ -240,15 +240,15 @@ class AcrobotEnv(core.Env):
         dtheta1 = s[2]
         dtheta2 = s[3]
         d1 = (
-            m1 * lc1 ** 2
-            + m2 * (l1 ** 2 + lc2 ** 2 + 2 * l1 * lc2 * cos(theta2))
+            m1 * lc1**2
+            + m2 * (l1**2 + lc2**2 + 2 * l1 * lc2 * cos(theta2))
             + I1
             + I2
         )
-        d2 = m2 * (lc2 ** 2 + l1 * lc2 * cos(theta2)) + I2
+        d2 = m2 * (lc2**2 + l1 * lc2 * cos(theta2)) + I2
         phi2 = m2 * lc2 * g * cos(theta1 + theta2 - pi / 2.0)
         phi1 = (
-            -m2 * l1 * lc2 * dtheta2 ** 2 * sin(theta2)
+            -m2 * l1 * lc2 * dtheta2**2 * sin(theta2)
             - 2 * m2 * l1 * lc2 * dtheta2 * dtheta1 * sin(theta2)
             + (m1 * lc1 + m2 * l1) * g * cos(theta1 - pi / 2)
             + phi2
@@ -256,13 +256,13 @@ class AcrobotEnv(core.Env):
         if self.book_or_nips == "nips":
             # the following line is consistent with the description in the
             # paper
-            ddtheta2 = (a + d2 / d1 * phi1 - phi2) / (m2 * lc2 ** 2 + I2 - d2 ** 2 / d1)
+            ddtheta2 = (a + d2 / d1 * phi1 - phi2) / (m2 * lc2**2 + I2 - d2**2 / d1)
         else:
             # the following line is consistent with the java implementation and the
             # book
             ddtheta2 = (
-                a + d2 / d1 * phi1 - m2 * l1 * lc2 * dtheta1 ** 2 * sin(theta2) - phi2
-            ) / (m2 * lc2 ** 2 + I2 - d2 ** 2 / d1)
+                a + d2 / d1 * phi1 - m2 * l1 * lc2 * dtheta1**2 * sin(theta2) - phi2
+            ) / (m2 * lc2**2 + I2 - d2**2 / d1)
         ddtheta1 = -(d2 * ddtheta2 + phi1) / d1
         return (dtheta1, dtheta2, ddtheta1, ddtheta2, 0.0)
 

gym/envs/classic_control/cartpole.py

@@ -11,7 +11,7 @@ import pygame
 from pygame import gfxdraw
 
 import gym
-from gym import spaces, logger
+from gym import logger, spaces
 from gym.utils import seeding
 
 
@@ -125,10 +125,10 @@ class CartPoleEnv(gym.Env[np.ndarray, Union[int, np.ndarray]]):
         # For the interested reader:
         # https://coneural.org/florian/papers/05_cart_pole.pdf
         temp = (
-            force + self.polemass_length * theta_dot ** 2 * sintheta
+            force + self.polemass_length * theta_dot**2 * sintheta
         ) / self.total_mass
         thetaacc = (self.gravity * sintheta - costheta * temp) / (
-            self.length * (4.0 / 3.0 - self.masspole * costheta ** 2 / self.total_mass)
+            self.length * (4.0 / 3.0 - self.masspole * costheta**2 / self.total_mass)
         )
         xacc = temp - self.polemass_length * thetaacc * costheta / self.total_mass
 

gym/envs/classic_control/pendulum.py

@@ -1,7 +1,7 @@
 __credits__ = ["Carlos Luis"]
 
-from typing import Optional
 from os import path
+from typing import Optional
 
 import numpy as np
 import pygame
@@ -113,9 +113,9 @@ class PendulumEnv(gym.Env):
 
         u = np.clip(u, -self.max_torque, self.max_torque)[0]
         self.last_u = u  # for rendering
-        costs = angle_normalize(th) ** 2 + 0.1 * thdot ** 2 + 0.001 * (u ** 2)
+        costs = angle_normalize(th) ** 2 + 0.1 * thdot**2 + 0.001 * (u**2)
 
-        newthdot = thdot + (3 * g / (2 * l) * np.sin(th) + 3.0 / (m * l ** 2) * u) * dt
+        newthdot = thdot + (3 * g / (2 * l) * np.sin(th) + 3.0 / (m * l**2) * u) * dt
         newthdot = np.clip(newthdot, -self.max_speed, self.max_speed)
         newth = th + newthdot * dt
 

gym/envs/mujoco/__init__.py

@@ -1,15 +1,14 @@
-from gym.envs.mujoco.mujoco_env import MujocoEnv
-
 # ^^^^^ so that user gets the correct error
 # message if mujoco is not installed correctly
 from gym.envs.mujoco.ant import AntEnv
 from gym.envs.mujoco.half_cheetah import HalfCheetahEnv
 from gym.envs.mujoco.hopper import HopperEnv
-from gym.envs.mujoco.walker2d import Walker2dEnv
 from gym.envs.mujoco.humanoid import HumanoidEnv
-from gym.envs.mujoco.inverted_pendulum import InvertedPendulumEnv
+from gym.envs.mujoco.humanoidstandup import HumanoidStandupEnv
 from gym.envs.mujoco.inverted_double_pendulum import InvertedDoublePendulumEnv
+from gym.envs.mujoco.inverted_pendulum import InvertedPendulumEnv
+from gym.envs.mujoco.mujoco_env import MujocoEnv
+from gym.envs.mujoco.pusher import PusherEnv
 from gym.envs.mujoco.reacher import ReacherEnv
 from gym.envs.mujoco.swimmer import SwimmerEnv
-from gym.envs.mujoco.humanoidstandup import HumanoidStandupEnv
-from gym.envs.mujoco.pusher import PusherEnv
+from gym.envs.mujoco.walker2d import Walker2dEnv

gym/envs/mujoco/ant.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/ant_v3.py

@@ -1,8 +1,8 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 
-
 DEFAULT_CAMERA_CONFIG = {
     "distance": 4.0,
 }

gym/envs/mujoco/half_cheetah.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/half_cheetah_v3.py

@@ -1,9 +1,9 @@
 __credits__ = ["Rushiv Arora"]
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 
-
 DEFAULT_CAMERA_CONFIG = {
     "distance": 4.0,
 }

gym/envs/mujoco/hopper.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/hopper_v3.py

@@ -1,9 +1,9 @@
 __credits__ = ["Rushiv Arora"]
 
 import numpy as np
-from gym.envs.mujoco import mujoco_env
-from gym import utils
 
+from gym import utils
+from gym.envs.mujoco import mujoco_env
 
 DEFAULT_CAMERA_CONFIG = {
     "trackbodyid": 2,

gym/envs/mujoco/humanoid.py

@@ -1,6 +1,7 @@
 import numpy as np
-from gym.envs.mujoco import mujoco_env
+
 from gym import utils
+from gym.envs.mujoco import mujoco_env
 
 
 def mass_center(model, sim):

gym/envs/mujoco/humanoid_v3.py

@@ -1,7 +1,7 @@
 import numpy as np
-from gym.envs.mujoco import mujoco_env
-from gym import utils
 
+from gym import utils
+from gym.envs.mujoco import mujoco_env
 
 DEFAULT_CAMERA_CONFIG = {
     "trackbodyid": 1,

gym/envs/mujoco/humanoidstandup.py

@@ -1,7 +1,8 @@
-from gym.envs.mujoco import mujoco_env
-from gym import utils
 import numpy as np
 
+from gym import utils
+from gym.envs.mujoco import mujoco_env
+
 
 class HumanoidStandupEnv(mujoco_env.MujocoEnv, utils.EzPickle):
     """

gym/envs/mujoco/inverted_double_pendulum.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 
@@ -117,9 +118,9 @@ class InvertedDoublePendulumEnv(mujoco_env.MujocoEnv, utils.EzPickle):
         self.do_simulation(action, self.frame_skip)
         ob = self._get_obs()
         x, _, y = self.sim.data.site_xpos[0]
-        dist_penalty = 0.01 * x ** 2 + (y - 2) ** 2
+        dist_penalty = 0.01 * x**2 + (y - 2) ** 2
         v1, v2 = self.sim.data.qvel[1:3]
-        vel_penalty = 1e-3 * v1 ** 2 + 5e-3 * v2 ** 2
+        vel_penalty = 1e-3 * v1**2 + 5e-3 * v2**2
         alive_bonus = 10
         r = alive_bonus - dist_penalty - vel_penalty
         done = bool(y <= 1)

gym/envs/mujoco/inverted_pendulum.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/mujoco_env.py

@@ -1,12 +1,13 @@
-from collections import OrderedDict
 import os
+from collections import OrderedDict
+from os import path
 from typing import Optional
 
+import numpy as np
+
+import gym
 from gym import error, spaces
 from gym.utils import seeding
-import numpy as np
-from os import path
-import gym
 
 try:
     import mujoco_py

gym/envs/mujoco/pusher.py

@@ -1,9 +1,9 @@
+import mujoco_py
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 
-import mujoco_py
-
 
 class PusherEnv(mujoco_env.MujocoEnv, utils.EzPickle):
     """

gym/envs/mujoco/reacher.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/swimmer.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/swimmer_v3.py

@@ -1,9 +1,9 @@
 __credits__ = ["Rushiv Arora"]
 
 import numpy as np
-from gym.envs.mujoco import mujoco_env
-from gym import utils
 
+from gym import utils
+from gym.envs.mujoco import mujoco_env
 
 DEFAULT_CAMERA_CONFIG = {}
 

gym/envs/mujoco/walker2d.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import utils
 from gym.envs.mujoco import mujoco_env
 

gym/envs/mujoco/walker2d_v3.py

@@ -1,7 +1,7 @@
 import numpy as np
-from gym.envs.mujoco import mujoco_env
-from gym import utils
 
+from gym import utils
+from gym.envs.mujoco import mujoco_env
 
 DEFAULT_CAMERA_CONFIG = {
     "trackbodyid": 2,

gym/envs/registration.py

@@ -1,24 +1,24 @@
 from __future__ import annotations
 
-import re
-import sys
+import contextlib
 import copy
 import difflib
 import importlib
 import importlib.util
-import contextlib
+import re
+import sys
 from typing import (
-    Callable,
-    Type,
-    Optional,
-    Union,
-    Tuple,
-    Generator,
-    Sequence,
-    cast,
-    SupportsFloat,
-    overload,
     Any,
+    Callable,
+    Generator,
+    Optional,
+    Sequence,
+    SupportsFloat,
+    Tuple,
+    Type,
+    Union,
+    cast,
+    overload,
 )
 
 if sys.version_info < (3, 10):
@@ -26,16 +26,15 @@ if sys.version_info < (3, 10):
 else:
     import importlib.metadata as metadata
 
-from dataclasses import dataclass, field, InitVar
 from collections import defaultdict
 from collections.abc import MutableMapping
+from dataclasses import InitVar, dataclass, field
 
 import numpy as np
 
-from gym import error, logger, Env
+from gym import Env, error, logger
 from gym.envs.__relocated__ import internal_env_relocation_map
 
-
 if sys.version_info >= (3, 8):
     from typing import Literal
 else:
@@ -670,9 +669,9 @@ def make(id: Literal[
 # ----------------------------------------
 
 @overload
-def make(id: str, **kwargs) -> "Env": ...
+def make(id: str, **kwargs) -> Env: ...
 # fmt: on
-def make(id: str, **kwargs) -> "Env":
+def make(id: str, **kwargs) -> Env:
     return registry.make(id, **kwargs)
 
 

gym/envs/toy_text/__init__.py

@@ -1,4 +1,4 @@
 from gym.envs.toy_text.blackjack import BlackjackEnv
-from gym.envs.toy_text.frozen_lake import FrozenLakeEnv
 from gym.envs.toy_text.cliffwalking import CliffWalkingEnv
+from gym.envs.toy_text.frozen_lake import FrozenLakeEnv
 from gym.envs.toy_text.taxi import TaxiEnv

gym/envs/toy_text/blackjack.py

@@ -1,5 +1,5 @@
-from typing import Optional
 import os
+from typing import Optional
 
 import numpy as np
 import pygame

gym/envs/toy_text/cliffwalking.py

@@ -4,6 +4,7 @@ from io import StringIO
 from typing import Optional
 
 import numpy as np
+
 from gym import Env, spaces
 from gym.envs.toy_text.utils import categorical_sample
 

gym/envs/toy_text/frozen_lake.py

@@ -2,9 +2,10 @@ from contextlib import closing
 from io import StringIO
 from os import path
 from typing import Optional
+
+import numpy as np
 import pygame
 from pygame.constants import SRCALPHA
-import numpy as np
 
 from gym import Env, spaces, utils
 from gym.envs.toy_text.utils import categorical_sample

gym/envs/toy_text/taxi.py

@@ -4,6 +4,7 @@ from io import StringIO
 from typing import Optional
 
 import numpy as np
+
 from gym import Env, spaces, utils
 from gym.envs.toy_text.utils import categorical_sample
 

gym/spaces/__init__.py

@@ -1,15 +1,11 @@
-from gym.spaces.space import Space
 from gym.spaces.box import Box
-from gym.spaces.discrete import Discrete
-from gym.spaces.multi_discrete import MultiDiscrete
-from gym.spaces.multi_binary import MultiBinary
-from gym.spaces.tuple import Tuple
 from gym.spaces.dict import Dict
-
-from gym.spaces.utils import flatdim
-from gym.spaces.utils import flatten_space
-from gym.spaces.utils import flatten
-from gym.spaces.utils import unflatten
+from gym.spaces.discrete import Discrete
+from gym.spaces.multi_binary import MultiBinary
+from gym.spaces.multi_discrete import MultiDiscrete
+from gym.spaces.space import Space
+from gym.spaces.tuple import Tuple
+from gym.spaces.utils import flatdim, flatten, flatten_space, unflatten
 
 __all__ = [
     "Space",

gym/spaces/box.py

@@ -1,12 +1,13 @@
 from __future__ import annotations
 
-from typing import Tuple, SupportsFloat, Union, Type, Optional, Sequence
+from typing import Optional, Sequence, SupportsFloat, Tuple, Type, Union
 
 import numpy as np
 
-from .space import Space
 from gym import logger
 
+from .space import Space
+
 
 def _short_repr(arr: np.ndarray) -> str:
     """Create a shortened string representation of a numpy array.

gym/spaces/dict.py

@@ -3,7 +3,9 @@ from __future__ import annotations
 from collections import OrderedDict
 from collections.abc import Mapping, Sequence
 from typing import Dict as TypingDict
+
 import numpy as np
+
 from .space import Space
 
 

gym/spaces/discrete.py

@@ -1,6 +1,7 @@
 from typing import Optional
 
 import numpy as np
+
 from .space import Space
 
 

gym/spaces/multi_binary.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
 
-from typing import Optional, Union, Sequence
+from typing import Optional, Sequence, Union
+
 import numpy as np
+
 from .space import Space
 
 

gym/spaces/multi_discrete.py

@@ -1,10 +1,13 @@
 from __future__ import annotations
 
 from collections.abc import Sequence
+
 import numpy as np
+
 from gym import logger
-from .space import Space
+
 from .discrete import Discrete
+from .space import Space
 
 
 class MultiDiscrete(Space[np.ndarray]):

gym/spaces/space.py

@@ -1,20 +1,11 @@
 from __future__ import annotations
 
-from typing import (
-    TypeVar,
-    Generic,
-    Optional,
-    Sequence,
-    Iterable,
-    Mapping,
-    Type,
-)
+from typing import Generic, Iterable, Mapping, Optional, Sequence, Type, TypeVar
 
 import numpy as np
 
 from gym.utils import seeding
 
-
 T_cov = TypeVar("T_cov", covariant=True)
 
 

gym/spaces/tuple.py

@@ -1,6 +1,8 @@
 from collections.abc import Sequence
 from typing import Iterable, List, Optional, Union
+
 import numpy as np
+
 from .space import Space
 
 

gym/spaces/utils.py

@@ -1,18 +1,13 @@
 from __future__ import annotations
 
-from collections import OrderedDict
-from functools import singledispatch, reduce
-from typing import TypeVar, Union
-import numpy as np
 import operator as op
+from collections import OrderedDict
+from functools import reduce, singledispatch
+from typing import TypeVar, Union
 
-from gym.spaces import Box
-from gym.spaces import Discrete
-from gym.spaces import MultiDiscrete
-from gym.spaces import MultiBinary
-from gym.spaces import Tuple
-from gym.spaces import Dict
-from gym.spaces import Space
+import numpy as np
+
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Space, Tuple
 
 
 @singledispatch

gym/utils/env_checker.py

@@ -10,13 +10,13 @@ Original Author: J K Terry
 These projects are covered by the MIT License.
 """
 
-from typing import Union, Optional
 import inspect
+from typing import Optional, Union
+
+import numpy as np
 
 import gym
-import numpy as np
-from gym import logger
-from gym import spaces
+from gym import logger, spaces
 
 
 def _is_numpy_array_space(space: spaces.Space) -> bool:

gym/utils/play.py

@@ -1,7 +1,9 @@
-import gym
-import pygame
-import matplotlib
 import argparse
+
+import matplotlib
+import pygame
+
+import gym
 from gym import logger
 
 try:
@@ -12,6 +14,7 @@ except ImportError as e:
     plt = None
 
 from collections import deque
+
 from pygame.locals import VIDEORESIZE
 
 

gym/utils/seeding.py

@@ -1,7 +1,7 @@
 import hashlib
-from typing import Optional, List, Tuple, Union, Any
 import os
 import struct
+from typing import Any, List, Optional, Tuple, Union
 
 import numpy as np
 from numpy.random import Generator
@@ -198,6 +198,6 @@ def _int_list_from_bigint(bigint: int) -> List[int]:
 
     ints: List[int] = []
     while bigint > 0:
-        bigint, mod = divmod(bigint, 2 ** 32)
+        bigint, mod = divmod(bigint, 2**32)
         ints.append(mod)
     return ints

gym/vector/async_vector_env.py

@@ -1,31 +1,31 @@
-from typing import Optional, Union, List
+import multiprocessing as mp
+import sys
+import time
+from copy import deepcopy
+from enum import Enum
+from typing import List, Optional, Union
 
 import numpy as np
-import multiprocessing as mp
-import time
-import sys
-from enum import Enum
-from copy import deepcopy
 
 from gym import logger
-from gym.logger import warn
-from gym.vector.vector_env import VectorEnv
 from gym.error import (
     AlreadyPendingCallError,
-    NoAsyncCallError,
     ClosedEnvironmentError,
     CustomSpaceError,
+    NoAsyncCallError,
 )
+from gym.logger import warn
 from gym.vector.utils import (
-    create_shared_memory,
-    create_empty_array,
-    write_to_shared_memory,
-    read_from_shared_memory,
-    concatenate,
-    iterate,
     CloudpickleWrapper,
     clear_mpi_env_vars,
+    concatenate,
+    create_empty_array,
+    create_shared_memory,
+    iterate,
+    read_from_shared_memory,
+    write_to_shared_memory,
 )
+from gym.vector.vector_env import VectorEnv
 
 __all__ = ["AsyncVectorEnv"]
 

gym/vector/sync_vector_env.py

@@ -1,12 +1,12 @@
-from typing import List, Union, Optional
+from copy import deepcopy
+from typing import List, Optional, Union
 
 import numpy as np
-from copy import deepcopy
 
 from gym import logger
 from gym.logger import warn
+from gym.vector.utils import concatenate, create_empty_array, iterate
 from gym.vector.vector_env import VectorEnv
-from gym.vector.utils import concatenate, iterate, create_empty_array
 
 __all__ = ["SyncVectorEnv"]
 

gym/vector/utils/numpy_utils.py

@@ -1,10 +1,10 @@
+from collections import OrderedDict
+from functools import singledispatch
+
 import numpy as np
 
-from gym.spaces import Space, Box, Discrete, MultiDiscrete, MultiBinary, Tuple, Dict
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Space, Tuple
 from gym.vector.utils.spaces import _BaseGymSpaces
-from collections import OrderedDict
-
-from functools import singledispatch
 
 __all__ = ["concatenate", "create_empty_array"]
 

gym/vector/utils/shared_memory.py

@@ -1,15 +1,15 @@
-import numpy as np
 import multiprocessing as mp
-from ctypes import c_bool
 from collections import OrderedDict
+from ctypes import c_bool
+from functools import singledispatch
+
+import numpy as np
 
 from gym import logger
-from gym.spaces import Space, Box, Discrete, MultiDiscrete, MultiBinary, Tuple, Dict
 from gym.error import CustomSpaceError
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Space, Tuple
 from gym.vector.utils.spaces import _BaseGymSpaces
 
-from functools import singledispatch
-
 __all__ = ["create_shared_memory", "read_from_shared_memory", "write_to_shared_memory"]
 
 

gym/vector/utils/spaces.py

@@ -1,9 +1,10 @@
-import numpy as np
 from collections import OrderedDict
 from functools import singledispatch
 
-from gym.spaces import Space, Box, Discrete, MultiDiscrete, MultiBinary, Tuple, Dict
+import numpy as np
+
 from gym.error import CustomSpaceError
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Space, Tuple
 
 _BaseGymSpaces = (Box, Discrete, MultiDiscrete, MultiBinary)
 __all__ = ["_BaseGymSpaces", "batch_space", "iterate"]
@@ -131,8 +132,7 @@ def iterate(space, items):
     StopIteration
     """
     raise ValueError(
-        "Space of type `{0}` is not a valid `gym.Space` "
-        "instance.".format(type(space))
+        "Space of type `{}` is not a valid `gym.Space` " "instance.".format(type(space))
     )
 
 

gym/vector/vector_env.py

@@ -1,7 +1,7 @@
-from typing import Optional, Union, List
+from typing import List, Optional, Union
 
 import gym
-from gym.logger import warn, deprecation
+from gym.logger import deprecation, warn
 from gym.spaces import Tuple
 from gym.vector.utils.spaces import batch_space
 

gym/wrappers/__init__.py

@@ -1,19 +1,18 @@
 from gym import error
-from gym.wrappers.time_limit import TimeLimit
-from gym.wrappers.filter_observation import FilterObservation
 from gym.wrappers.atari_preprocessing import AtariPreprocessing
-from gym.wrappers.time_aware_observation import TimeAwareObservation
-from gym.wrappers.rescale_action import RescaleAction
+from gym.wrappers.autoreset import AutoResetWrapper
+from gym.wrappers.clip_action import ClipAction
+from gym.wrappers.filter_observation import FilterObservation
 from gym.wrappers.flatten_observation import FlattenObservation
+from gym.wrappers.frame_stack import FrameStack, LazyFrames
 from gym.wrappers.gray_scale_observation import GrayScaleObservation
-from gym.wrappers.frame_stack import LazyFrames
-from gym.wrappers.frame_stack import FrameStack
+from gym.wrappers.normalize import NormalizeObservation, NormalizeReward
+from gym.wrappers.order_enforcing import OrderEnforcing
+from gym.wrappers.record_episode_statistics import RecordEpisodeStatistics
+from gym.wrappers.record_video import RecordVideo, capped_cubic_video_schedule
+from gym.wrappers.rescale_action import RescaleAction
+from gym.wrappers.resize_observation import ResizeObservation
+from gym.wrappers.time_aware_observation import TimeAwareObservation
+from gym.wrappers.time_limit import TimeLimit
 from gym.wrappers.transform_observation import TransformObservation
 from gym.wrappers.transform_reward import TransformReward
-from gym.wrappers.resize_observation import ResizeObservation
-from gym.wrappers.clip_action import ClipAction
-from gym.wrappers.record_episode_statistics import RecordEpisodeStatistics
-from gym.wrappers.normalize import NormalizeObservation, NormalizeReward
-from gym.wrappers.record_video import RecordVideo, capped_cubic_video_schedule
-from gym.wrappers.order_enforcing import OrderEnforcing
-from gym.wrappers.autoreset import AutoResetWrapper

gym/wrappers/atari_preprocessing.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 import gym
 from gym.spaces import Box
 

gym/wrappers/clip_action.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 from gym import ActionWrapper
 from gym.spaces import Box
 

gym/wrappers/filter_observation.py

@@ -1,6 +1,6 @@
 import copy
-from gym import spaces
-from gym import ObservationWrapper
+
+from gym import ObservationWrapper, spaces
 
 
 class FilterObservation(ObservationWrapper):

gym/wrappers/frame_stack.py

@@ -2,8 +2,9 @@ from collections import deque
 from typing import Optional
 
 import numpy as np
-from gym.spaces import Box
+
 from gym import ObservationWrapper
+from gym.spaces import Box
 
 
 class LazyFrames:

gym/wrappers/gray_scale_observation.py

@@ -1,6 +1,7 @@
 import numpy as np
-from gym.spaces import Box
+
 from gym import ObservationWrapper
+from gym.spaces import Box
 
 
 class GrayScaleObservation(ObservationWrapper):

gym/wrappers/monitoring/video_recorder.py

@@ -1,3 +1,5 @@
+import distutils.spawn
+import distutils.version
 import json
 import os
 import os.path
@@ -6,8 +8,6 @@ import subprocess
 import tempfile
 from io import StringIO
 
-import distutils.spawn
-import distutils.version
 import numpy as np
 
 from gym import error, logger

gym/wrappers/normalize.py

@@ -1,6 +1,7 @@
 from typing import Optional
 
 import numpy as np
+
 import gym
 
 

gym/wrappers/pixel_observation.py

@@ -1,11 +1,10 @@
 import collections
-from collections.abc import MutableMapping
 import copy
+from collections.abc import MutableMapping
+
 import numpy as np
 
-from gym import spaces
-from gym import ObservationWrapper
-
+from gym import ObservationWrapper, spaces
 
 STATE_KEY = "state"
 

gym/wrappers/record_episode_statistics.py

@@ -3,6 +3,7 @@ from collections import deque
 from typing import Optional
 
 import numpy as np
+
 import gym
 
 

gym/wrappers/record_video.py

@@ -1,7 +1,7 @@
 import os
-import gym
 from typing import Callable, Optional
 
+import gym
 from gym import logger
 from gym.wrappers.monitoring import video_recorder
 

gym/wrappers/rescale_action.py

@@ -1,4 +1,5 @@
 import numpy as np
+
 import gym
 from gym import spaces
 

gym/wrappers/resize_observation.py

@@ -1,6 +1,7 @@
 import numpy as np
-from gym.spaces import Box
+
 from gym import ObservationWrapper
+from gym.spaces import Box
 
 
 class ResizeObservation(ObservationWrapper):

gym/wrappers/time_aware_observation.py

@@ -1,8 +1,9 @@
 from typing import Optional
 
 import numpy as np
-from gym.spaces import Box
+
 from gym import ObservationWrapper
+from gym.spaces import Box
 
 
 class TimeAwareObservation(ObservationWrapper):

setup.py

@@ -1,6 +1,6 @@
+import itertools
 import os.path
 import sys
-import itertools
 
 from setuptools import find_packages, setup
 
@@ -20,7 +20,7 @@ extras = {
 }
 
 # Meta dependency groups.
-nomujoco_blacklist = set(["mujoco", "accept-rom-license", "atari"])
+nomujoco_blacklist = {"mujoco", "accept-rom-license", "atari"}
 nomujoco_groups = set(extras.keys()) - nomujoco_blacklist
 
 extras["nomujoco"] = list(
@@ -28,7 +28,7 @@ extras["nomujoco"] = list(
 )
 
 
-all_blacklist = set(["accept-rom-license"])
+all_blacklist = {"accept-rom-license"}
 all_groups = set(extras.keys()) - all_blacklist
 
 extras["all"] = list(

tests/envs/spec_list.py

@@ -1,6 +1,6 @@
-from gym import envs, logger
 import os
 
+from gym import envs, logger
 
 SKIP_MUJOCO_WARNING_MESSAGE = (
     "Cannot run mujoco test (either license key not found or mujoco not"

tests/envs/test_action_dim_check.py

@@ -3,8 +3,7 @@ import pickle
 import pytest
 
 from gym import envs
-from tests.envs.spec_list import skip_mujoco, SKIP_MUJOCO_WARNING_MESSAGE
-
+from tests.envs.spec_list import SKIP_MUJOCO_WARNING_MESSAGE, skip_mujoco
 
 ENVIRONMENT_IDS = ("HalfCheetah-v2",)
 

tests/envs/test_atari_legacy_env_specs.py

@@ -2,10 +2,10 @@ import pytest
 
 pytest.importorskip("gym.envs.atari")
 
-from gym.envs.registration import registry
-
 from itertools import product
 
+from gym.envs.registration import registry
+
 
 def test_ale_legacy_env_specs():
     versions = ["-v0", "-v4"]

tests/envs/test_envs.py

@@ -1,10 +1,10 @@
-import pytest
 import numpy as np
+import pytest
 
 from gym import envs
-from tests.envs.spec_list import spec_list
 from gym.spaces import Box
 from gym.utils.env_checker import check_env
+from tests.envs.spec_list import spec_list
 
 
 # This runs a smoketest on each official registered env. We may want

tests/envs/test_frozenlake_dfs.py

@@ -1,5 +1,5 @@
-import pytest
 import numpy as np
+import pytest
 
 from gym.envs.toy_text.frozen_lake import generate_random_map
 

tests/envs/test_lunar_lander.py

@@ -2,10 +2,8 @@ import pytest
 
 try:
     import Box2D
-    from gym.envs.box2d.lunar_lander import (
-        LunarLander,
-        demo_heuristic_lander,
-    )
+
+    from gym.envs.box2d.lunar_lander import LunarLander, demo_heuristic_lander
 except ImportError:
     Box2D = None
 

tests/envs/test_mujoco_v2_to_v3_conversion.py

@@ -1,7 +1,9 @@
 import unittest
+
 import numpy as np
+
 from gym import envs
-from tests.envs.spec_list import skip_mujoco, SKIP_MUJOCO_WARNING_MESSAGE
+from tests.envs.spec_list import SKIP_MUJOCO_WARNING_MESSAGE, skip_mujoco
 
 
 def verify_environments_match(

tests/envs/test_registration.py

@@ -1,8 +1,7 @@
-# -*- coding: utf-8 -*-
 import pytest
 
 import gym
-from gym import error, envs
+from gym import envs, error
 from gym.envs import registration
 from gym.envs.classic_control import cartpole
 from gym.envs.registration import EnvSpec, EnvSpecTree

tests/spaces/test_spaces.py

@@ -1,12 +1,12 @@
-import json  # note: ujson fails this test due to float equality
 import copy
+import json  # note: ujson fails this test due to float equality
 import pickle
 import tempfile
 
 import numpy as np
 import pytest
 
-from gym.spaces import Tuple, Box, Discrete, MultiDiscrete, MultiBinary, Dict
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Tuple
 
 
 @pytest.mark.parametrize(

tests/spaces/test_utils.py

@@ -5,7 +5,6 @@ import pytest
 
 from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Tuple, utils
 
-
 spaces = [
     Discrete(3),
     Box(low=0.0, high=np.inf, shape=(2, 2)),

tests/test_core.py

@@ -1,10 +1,10 @@
 from typing import Optional
 
-import pytest
 import numpy as np
+import pytest
 
 from gym import core, spaces
-from gym.wrappers import TimeLimit, OrderEnforcing
+from gym.wrappers import OrderEnforcing, TimeLimit
 
 
 class ArgumentEnv(core.Env):

tests/utils/test_env_checker.py

@@ -1,10 +1,10 @@
 from typing import Optional
 
-import gym
 import numpy as np
 import pytest
-from gym.spaces import Box, Dict, Discrete
 
+import gym
+from gym.spaces import Box, Dict, Discrete
 from gym.utils.env_checker import check_env
 
 

tests/vector/test_async_vector_env.py

@@ -1,18 +1,18 @@
-import pytest
-import numpy as np
-
 from multiprocessing import TimeoutError
-from gym.spaces import Box, Tuple, Discrete, MultiDiscrete
-from gym.error import AlreadyPendingCallError, NoAsyncCallError, ClosedEnvironmentError
+
+import numpy as np
+import pytest
+
+from gym.error import AlreadyPendingCallError, ClosedEnvironmentError, NoAsyncCallError
+from gym.spaces import Box, Discrete, MultiDiscrete, Tuple
+from gym.vector.async_vector_env import AsyncVectorEnv
 from tests.vector.utils import (
     CustomSpace,
+    make_custom_space_env,
     make_env,
     make_slow_env,
-    make_custom_space_env,
 )
 
-from gym.vector.async_vector_env import AsyncVectorEnv
-
 
 @pytest.mark.parametrize("shared_memory", [True, False])
 def test_create_async_vector_env(shared_memory):

tests/vector/test_numpy_utils.py

@@ -1,14 +1,13 @@
-import pytest
-import numpy as np
-
 from collections import OrderedDict
 
-from gym.spaces import Tuple, Dict
+import numpy as np
+import pytest
+
+from gym.spaces import Dict, Tuple
+from gym.vector.utils.numpy_utils import concatenate, create_empty_array
 from gym.vector.utils.spaces import _BaseGymSpaces
 from tests.vector.utils import spaces
 
-from gym.vector.utils.numpy_utils import concatenate, create_empty_array
-
 
 @pytest.mark.parametrize(
     "space", spaces, ids=[space.__class__.__name__ for space in spaces]

tests/vector/test_shared_memory.py

@@ -1,22 +1,20 @@
-import pytest
-import numpy as np
-
 import multiprocessing as mp
-from multiprocessing.sharedctypes import SynchronizedArray
-from multiprocessing import Array, Process
 from collections import OrderedDict
+from multiprocessing import Array, Process
+from multiprocessing.sharedctypes import SynchronizedArray
+
+import numpy as np
+import pytest
 
-from gym.spaces import Tuple, Dict
 from gym.error import CustomSpaceError
-from gym.vector.utils.spaces import _BaseGymSpaces
-from tests.vector.utils import spaces, custom_spaces
-
+from gym.spaces import Dict, Tuple
 from gym.vector.utils.shared_memory import (
     create_shared_memory,
     read_from_shared_memory,
     write_to_shared_memory,
 )
-
+from gym.vector.utils.spaces import _BaseGymSpaces
+from tests.vector.utils import custom_spaces, spaces
 
 expected_types = [
     Array("d", 1),

tests/vector/test_spaces.py

@@ -1,10 +1,9 @@
-import pytest
 import numpy as np
+import pytest
 
-from gym.spaces import Box, MultiDiscrete, Tuple, Dict
-from tests.vector.utils import spaces, custom_spaces, CustomSpace
-
+from gym.spaces import Box, Dict, MultiDiscrete, Tuple
 from gym.vector.utils.spaces import batch_space, iterate
+from tests.vector.utils import CustomSpace, custom_spaces, spaces
 
 expected_batch_spaces_4 = [
     Box(low=-1.0, high=1.0, shape=(4,), dtype=np.float64),

tests/vector/test_sync_vector_env.py

@@ -1,10 +1,9 @@
-import pytest
 import numpy as np
+import pytest
 
-from gym.spaces import Box, Tuple, Discrete, MultiDiscrete
-from tests.vector.utils import CustomSpace, make_env, make_custom_space_env
-
+from gym.spaces import Box, Discrete, MultiDiscrete, Tuple
 from gym.vector.sync_vector_env import SyncVectorEnv
+from tests.vector.utils import CustomSpace, make_custom_space_env, make_env
 
 
 def test_create_sync_vector_env():

tests/vector/test_vector_env.py

@@ -1,12 +1,11 @@
-import pytest
 import numpy as np
+import pytest
 
 from gym.spaces import Tuple
-from tests.vector.utils import CustomSpace, make_env
-
 from gym.vector.async_vector_env import AsyncVectorEnv
 from gym.vector.sync_vector_env import SyncVectorEnv
 from gym.vector.vector_env import VectorEnv
+from tests.vector.utils import CustomSpace, make_env
 
 
 @pytest.mark.parametrize("shared_memory", [True, False])

tests/vector/test_vector_env_wrapper.py

@@ -1,6 +1,5 @@
 import gym
-from gym.vector import make
-from gym.vector import VectorEnvWrapper
+from gym.vector import VectorEnvWrapper, make
 
 
 class DummyWrapper(VectorEnvWrapper):

tests/vector/utils.py

@@ -1,10 +1,10 @@
+import time
 from typing import Optional
 
 import numpy as np
-import gym
-import time
 
-from gym.spaces import Box, Discrete, MultiDiscrete, MultiBinary, Tuple, Dict
+import gym
+from gym.spaces import Box, Dict, Discrete, MultiBinary, MultiDiscrete, Tuple
 
 spaces = [
     Box(low=np.array(-1.0), high=np.array(1.0), dtype=np.float64),

tests/wrappers/flatten_test.py

@@ -7,7 +7,7 @@ import numpy as np
 import pytest
 
 import gym
-from gym.spaces import Box, Dict, unflatten, flatten
+from gym.spaces import Box, Dict, flatten, unflatten
 from gym.wrappers import FlattenObservation
 
 

tests/wrappers/nested_dict_test.py

@@ -1,11 +1,11 @@
 """Tests for the filter observation wrapper."""
 from typing import Optional
 
-import pytest
 import numpy as np
+import pytest
 
 import gym
-from gym.spaces import Dict, Box, Discrete, Tuple
+from gym.spaces import Box, Dict, Discrete, Tuple
 from gym.wrappers import FilterObservation, FlattenObservation
 
 

tests/wrappers/test_atari_preprocessing.py

@@ -1,7 +1,8 @@
 import numpy as np
+import pytest
+
 import gym
 from gym.wrappers import AtariPreprocessing
-import pytest
 
 pytest.importorskip("gym.envs.atari")
 

tests/wrappers/test_autoreset.py

@@ -1,7 +1,7 @@
-import pytest
 from typing import Optional
 
 import numpy as np
+import pytest
 
 import gym
 from gym.wrappers import AutoResetWrapper

tests/wrappers/test_filter_observation.py

@@ -1,7 +1,7 @@
 from typing import Optional
 
-import pytest
 import numpy as np
+import pytest
 
 import gym
 from gym import spaces