import gym
import random

#env
env_name = 'CartPole-v1'
env_name='FrozenLake8x8-v1'

env = gym.make(env_name)
print("Observation space:",env.observation_space)
print('Action space:',env.action_space)

#Agent
class Agent():
    def __init__(self,env):
        self.action_size =  env.action_space.n
        print(self.action_size)
    def get_action(self,state):
        action=random.choice(range(self.action_size))
        return action

#interaction
state=env.reset()
agent = Agent(env)
for _ in range(200):
    #action = env.action_space.sample()
    action = agent.get_action(state)
    state,reward,done,info=env.step(action)
    env.render()