gym-http-server 0.0.1

Serve gym on a webserver and receive HTTP requests to play to the game from any client

Gym HTTP Server

This project provides a local REST API to the gym open-source library, allowing development in languages other than python.

A python client is included, to demonstrate how to interact with the server.

Installation

Install the package using pip:

pip install gym-http-server

Usage

Direct Usage

Use it simply from anywhere by calling

gym-http-server

If you would like to run on a specific port, use --listen and --port

gym-http-server -l 127.0.0.1 -p 5000

Pythonic Usage

If you want to use this inside your python script,

from gym_http_server import start_server
start_server()

If you want to specify ip and port,

start_server(listen=='127.0.0.1', port==5000)

API specification

• POST /v1/envs/

  • Create an instance of the specified environment
  • param: env_id -- gym environment ID string, such as 'CartPole-v0'
  • returns: instance_id -- a short identifier (such as '3c657dbc') for the created environment instance. The instance_id is used in future API calls to identify the environment to be manipulated

• GET /v1/envs/

  • List all environments running on the server
  • returns: envs -- dict mapping instance_id to env_id (e.g. {'3c657dbc': 'CartPole-v0'}) for every env on the server

• POST /v1/envs/<instance_id>/reset/

  • Reset the state of the environment and return an initial observation.
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance
  • returns: observation -- the initial observation of the space

• POST /v1/envs/<instance_id>/step/

  • Step though an environment using an action.
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance
  • param: action -- an action to take in the environment
  • returns: observation -- agent's observation of the current environment
  • returns: reward -- amount of reward returned after previous action
  • returns: done -- whether the episode has ended
  • returns: info -- a dict containing auxiliary diagnostic information

• GET /v1/envs/<instance_id>/action_space/

  • Get information (name and dimensions/bounds) of the env's action_space
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance
  • returns: info -- a dict containing 'name' (such as 'Discrete'), and additional dimensional info (such as 'n') which varies from space to space

• GET /v1/envs/<instance_id>/observation_space/

  • Get information (name and dimensions/bounds) of the env's observation_space
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance
  • returns: info -- a dict containing 'name' (such as 'Discrete'), and additional dimensional info (such as 'n') which varies from space to space

• POST /v1/envs/<instance_id>/monitor/start/

  • Start monitoring
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance
  • param: force (default=False) -- Clear out existing training data from this directory (by deleting every file prefixed with "openaigym.")
  • param: resume (default=False) -- Retain the training data already in this directory, which will be merged with our new data
  • (NOTE: the video_callable parameter from the native env.monitor.start function is NOT implemented)

• POST /v1/envs/<instance_id>/monitor/close/

  • Flush all monitor data to disk
  • param: instance_id -- a short identifier (such as '3c657dbc') for the environment instance

• POST /v1/upload/

  • Flush all monitor data to disk
  • param: training_dir -- A directory containing the results of a training run.
  • param: api_key -- Your OpenAI API key
  • param: algorithm_id (default=None) -- An arbitrary string indicating the paricular version of the algorithm (including choices of parameters) you are running.

• POST /v1/shutdown/

  • Request a server shutdown
  • Currently used by the integration tests to repeatedly create and destroy fresh copies of the server running in a separate thread

Forked from the archived gym-http-api

Licence

The MIT License

Copyright (c) 2019 Saravanabalagi Ramachandran

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.