A sample episode through the Open AI gym cartpole environment taking random actions.

cartpole-episode.py

import gym

# Use the cartpole environment.
env = gym.make('CartPole-v0')
# environment has to be reset first.
env.reset()
# This flag to is used to represent the end of an episode.
# An episode ends when the pole falls down.
done = False
# counter to check the number of moves for which the balance of the pole 
# is maintained before it falls down.
t = 0

# run till end of the episode.
while not done:
        # The episode animation will be displayed.
        env.render()
        # choose a random action from the set of available actions.
        action = env.action_space.sample()
        # take the action.
        # The new state and the corresponding reward returned.
        # done flag will be set to true when the episode ends.
        state, reward, done, _ = env.step(action)
        t = t + 1
        print("Action taken : ", action)
        print("Reward obtained: ",reward)


print("Balanced the pole for this many moves: ",t)