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• Jupylet is a Python library that lets you create and run games interactively. In a Jupyter notebook. It is intended for two types of audiences: Kids and their parents interested in learning to program, Researchers and students of deep reinforcement learning.
• You want to develop a Jupyter notebook or series of notebooks for uses such as supplementing teaching material, or for a scholarly journal article, for example. In both cases, you will want to start the Jupyter notebook in a specific folder. Starting a Jupyter Notebook in a Specific Folder. On Mac OS X, create a Desktop folder with the Finder.
• Windows Video Tutorial. Download the Git for Windows installer.; Run the installer and follow the steps bellow. Click on 'Next'. Click on 'Next'. Keep 'Use Git from the Windows Command Prompt' selected and click on 'Next'. If you forgot to do this programs that you need for the workshop will not work properly.
• Maybe this does not work at all, because its a Mac, but maybe there is a way to open a jupyter notebook on a Mac? I tried the following command jupyter notebook Manager.ipynb and I got an error.

Released:

A marriage of Jupyter and the pyglet game programming library

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Project description

Every time you open Jupyter, you must select the mlcc environment. Install notebook within the mlcc environment, as shown here: Once notebook is installed, click Launch. This will open a web browser. Next, run the exercises. Install and Run Jupyter on Mac OS X. If you have not installed XCode, install it by running this command (this takes a. Install Anaconda and Jupyter Notebook. Open the Terminal by clicking on the Spotlight magnifying glass at the top right of the screen, typing “Terminal” then clicking the Terminal icon. Type the commands in red to go to the Downloads directory and download Anaconda3 2020.07. Anaconda may take a few minutes to download.

Jupylet is a Python library that lets you create and run games interactively

in a Jupyter notebook. It is intended for two types of audiences:

• Kids and their parents interested in learning to program,
• Researchers and students of deep reinforcement learning.

## TL;DR

Here are two examples of 2D and 3D games for the impatient. Their code is included in this repository:

<p float=”left”>

<img src=”https://raw.githubusercontent.com/nir/jupylet/master/docs/images/spaceship.gif” width=”256” />

<img src=”https://raw.githubusercontent.com/nir/jupylet/master/docs/images/spaceship-3d.jpg” width=”384” />

</p>

## Kids Learning to Program

A Jupyter notebook is in essence a laboratory for programming. It is the ideal

environment for playing around with code, experimenting, and exploring ideas.

It is used by professional machine learning scientists who come every day to

play at work, so why not by kids?

Jupylet is built on top of pyglet, a powerful game programming library. It is

wonderfully easy to use for creating simple 2D games and Jupylet extends it to

3D gaming.

By marrying Jupyter and pyglet, Jupylet lets you have the best of both

worlds. Create games interactively and experimentally, change a variable or a

function and see how the game is affected immediately while it is running.

## Deep Reinforcement Learning with Jupylet

Jupylet makes it is super easy to create and modify environments in which to

experiment with deep reinforcement learning algorithms and it includes the code

required to programmatically control multiple simultaneous games and render

thousands of frames per second.

Consider for example the pong game included in this repository. With a few

lines of code you can modify the colors of the game or turn the background into

a swirling giant flower to experiment with transfer learning, or turn the game

into 4-way pong with agents on all four sides of the game court to experiment

with cooperation between multiple agents. And since you can modify the game

interactively in Jupyter this process is not only easy but fun.

Head to [examples/22-pong-RL.ipynb](https://github.com/nir/jupylet/blob/master/examples/22-pong-RL.ipynb) to see how to programmatically control and render a 2-player version of pong.

## Requirements

_jupylet_ should run on Python 3.4+ on Windows, Mac, and Linux.

## How to Install and Run Jupylet

If you are new to Python, I strongly recommend that you install and use the

[Miniconda Python](https://docs.conda.io/en/latest/miniconda.html)

distribution. Download and run the 64-bit installer and stick to the default

install options.

Once Miniconda is installed start a Miniconda Prompt. To do this on Windows

click the ⊞ Winkey then type Miniconda and press the

Enter key. This should open a small dark window that programmers

call console or shell in which you can enter commands and run programs.

To run jupylet first install it by typing the following command in the

console:

pip install jupylet

Next, you need to download the jupylet repository since it contains the

example notebooks. If you have [Git](https://git-scm.com/) installed you

can use it to clone the jupylet repository with:

git clone https://github.com/nir/jupylet.git

Alternatively, if you don’t have Git installed, you can download and unzip

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the jupylet archive by typing:

python -m wget https://github.com/nir/jupylet/archive/master.zip

python -m zipfile -e jupylet-master.zip .

move jupylet-master jupylet

Download Jupyter Notebook Mac

Next, enter the jupylet/examples/ directory with the change directory

command:

cd ./jupylet/examples/

And start a jupyter notebook with:

jupyter notebook 11-spaceship.ipynb

Run the notebook by following the instructions in the notebook and a game

canvas should appear with the spaceship example:

<img src=”https://raw.githubusercontent.com/nir/jupylet/master/docs/images/spaceship.gif” width=”256” height=”256” />

You can run essentially the same code from the console with:

python spaceship.py

The only difference in the code is that the application object is instantiated with:

app = App(mode=’window’)

## Documentation

In terms of its interface _jupylet_ introduces only minor additions and modifications to the underlying pyglet library. Therefore the bulk of learning to use it is covered by the [pyglet documentation](https://pyglet.readthedocs.io/en/stable/). I have started writing a [guide](https://jupylet.readthedocs.io/en/latest/) and will add documentation in the comming days; in the mean time head to the [11-spaceship.ipynb](https://github.com/nir/jupylet/blob/master/examples/11-spaceship.ipynb) example to get started.

## Contact

For questions and feedback send an email to [Nir Aides](mailto:nir@winpdb.org).

Keywords: python,pyglet,jupyter,kids,games,children,deep learning,reinforcement learning,RLPlatform: UNKNOWNClassifier: Development Status :: 4 - BetaClassifier: Intended Audience :: EducationClassifier: Intended Audience :: DevelopersClassifier: Intended Audience :: Science/ResearchClassifier: Topic :: EducationClassifier: Topic :: Scientific/Engineering :: Artificial IntelligenceClassifier: License :: OSI Approved :: BSD LicenseClassifier: Programming Language :: Python :: 3Classifier: Programming Language :: Python :: 3.4Classifier: Programming Language :: Python :: 3.5Classifier: Programming Language :: Python :: 3.6Classifier: Programming Language :: Python :: 3.7Classifier: Programming Language :: Python :: 3.8Description-Content-Type: text/markdown

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