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An OpenAI Gym for Shopping Cart Reinforcement Learning

Project description

gym-display-advertising

An OpenAI Gym for Shopping Cart Reinforcement Learning.

This is a project by Winder Research, a Cloud-Native Data Science consultancy.

Installation

pip install gym-shopping-cart

Usage

This example will use the small example data included in the repo.

import gym
import gym_shopping_cart

env = gym.make("ShoppingCart-v0")
episode_over = False
rewards = 0
while not episode_over:
    state, reward, episode_over, _ = env.step(env.action_space.sample())
    print(state, reward)
    rewards += reward
print("Total reward: {}".format(rewards))

Real Shopping Cart Data

This environment uses real shopping cart information from the Instacart dataset.

To help read this data the library also comes with a data parser. This loads the raw data and cleans the data to be in a format expected by the environment.

Credits

Gitlab icon made by Freepik from www.flaticon.com.

Project details


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Files for gym-shopping-cart, version 0.2.0
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