How to do it...

There are two ways to install Gym. The first one is to use pip, as follows:

pip install gym

For conda users, remember to install pip first in conda using the following command before installing Gym using pip:

conda install pip

This is because Gym is not officially available in conda as of early 2019.

Another approach is to build from source:

1. First, clone the package directly from its Git repository:

git clone https://github.com/openai/gym

1. Go to the downloaded folder and install Gym from there:

cd gym
pip install -e .

And now you are good to go. Feel free to play around with gym.

1. You can also check the available gym environment by typing the following lines of code:

>>> from gym import envs
>>> print(envs.registry.all())
dict_values([EnvSpec(Copy-v0), EnvSpec(RepeatCopy-v0), EnvSpec(ReversedAddition-v0), EnvSpec(ReversedAddition3-v0), EnvSpec(DuplicatedInput-v0), EnvSpec(Reverse-v0), EnvSpec(CartPole-v0), EnvSpec(CartPole-v1), EnvSpec(MountainCar-v0), EnvSpec(MountainCarContinuous-v0), EnvSpec(Pendulum-v0), EnvSpec(Acrobot-v1), EnvSpec(LunarLander-v2), EnvSpec(LunarLanderContinuous-v2), EnvSpec(BipedalWalker-v2), EnvSpec(BipedalWalkerHardcore-v2), EnvSpec(CarRacing-v0), EnvSpec(Blackjack-v0)
...
...

This will give you a long list of environments if you installed Gym properly. We will play around with some of them in the next recipe, Simulating Atari environments.