Run OpenAI Gym environments on an external process or remote machine using gRPC.
Installation
Install Gym (not required if using Docker) and run:
pip install gymx
It is recommended to use a virtual environment.
Usage
Server
To start the server run:
python -m gymx
To use a different port run:
python -m gymx --port=54321
You can also run the server using Docker:
docker run -p 54321:54321 album/gymx
Client
Inside your application use:
from gymx import Env
env = Env('CartPole-v0')
To specify the server address use:
env = Env('CartPole-v0', address='localhost:54321')
API
env.reset(): Reset the environment's state. Returnsobservation.env.step(action): Step the environment by one timestep. Returnsobservation,reward,done,next_episode. Unlike the original gym API, it automatically resets the environment when done and returns next episode's observation instead ofinfo.
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Metadata
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Release files for gymx 0.0.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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Release files / gymx-0.0.1.tar.gz
| Download URL | gymx-0.0.1.tar.gz |
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