class_docstr: [PyGame Learning Environment](https://github.com/ntasfi/PyGame-Learning-Environment/)
  environment adapter (specification key: `ple`, `pygame_learning_environment`).
  
  May require:
  ```bash
  sudo apt-get install git python3-dev python3-setuptools python3-numpy python3-opengl     libsdl-image1.2-dev libsdl-mixer1.2-dev libsdl-ttf2.0-dev libsmpeg-dev libsdl1.2-dev     libportmidi-dev libswscale-dev libavformat-dev libavcodec-dev libtiff5-dev libx11-6     libx11-dev fluid-soundfont-gm timgm6mb-soundfont xfonts-base xfonts-100dpi xfonts-75dpi     xfonts-cyrillic fontconfig fonts-freefont-ttf libfreetype6-dev
  
  pip3 install pygame
  pip3 install git+https://github.com/ntasfi/PyGame-Learning-Environment.git
  ```
  
  Args:
      level (string | subclass of `ple.games.base`): Game instance or name of class in
          `ple.games`, like "Catcher", "Doom", "FlappyBird", "MonsterKong", "Pixelcopter", 
          "Pong", "PuckWorld", "RaycastMaze", "Snake", "WaterWorld"
          (<span style="color:#C00000"><b>required</b></span>).
      visualize (bool): Whether to visualize interaction
          (<span style="color:#00C000"><b>default</b></span>: false).
      frame_skip (int > 0): Number of times to repeat an action without observing
          (<span style="color:#00C000"><b>default</b></span>: 1).
      fps (int > 0): The desired frames per second we want to run our game at
          (<span style="color:#00C000"><b>default</b></span>: 30).
code: def __str__(self):
      return super().__str__() + "({})".format(
          self.environment.__class__.__name__
      )
  
file_path: tensorforce/tensorforce/environments/pygame_learning_environment.py
imports: from collections import OrderedDict
  import os
  import numpy
  from tensorforce import TensorforceError
  from tensorforce.environments import Environment
label_desc: Use image node_id 3 for calling the PyGameLearningEnvironment obj's underlying member method code with example usage: obj.__str__() and returns: unknown