graphRL

This repository contains a PIP package which is an OpenAI environment for simulating directed acyclic graphs for workflow scheduling.

Installation

Install the OpenAI gym.

Then install this package via

pip install -e .

import gym
import graphRL

env = gym.make('graphRL-v0')

Tbc.

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for graphRL 0.0.1
File	Size	Uploaded
graphRL-0.0.1.tar.gz	2.9 kB	Dec 14, 2018	Details

Table of built distributions (wheels) for graphRL 0.0.1
File	Interpreter	ABI	Platform	Reset
graphRL-0.0.1-py3-none-any.whl 4.3 kB Dec 14, 2018	Python 3	none	any	Details

Total release size: 7.2 kB

Download URL	graphRL-0.0.1.tar.gz
Size	2.9 kB
Tags	Source
SHA-256 checksum How to use checksums	`04d5da9434cf6494cf7d017d6ad3334d621720365dbef88c391ea7feaec727b9`
BLAKE2b-256 checksum How to use checksums	`31104c27b61501ff5c402c3a6ead5237231df042e2ec3f8bdd5554a09453953e`
Upload date	Dec 14, 2018
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.7.1`

Download URL	graphRL-0.0.1-py3-none-any.whl
Size	4.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`fdf3ab7f6095db9a44dfaad087fd459cd2ec66e6ae4c7bbaa49fc605871a6335`
BLAKE2b-256 checksum How to use checksums	`4a3c21872f097872ef00fd1a4adb588a3e25a2dfcfcd8f379eccbeb0b2c97f65`
Upload date	Dec 14, 2018
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.12.1 pkginfo/1.4.2 requests/2.20.1 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.28.1 CPython/3.7.1`

This release

0.0.1 This release