Download CocoNotebook for Jupyter for macOS 10.8 or later and enjoy it on your Mac. ‎About CocoNotebook CocoNotebook is an interface that can be used to open Jupyter notebooks files (.ipynb) into a new, or existing, browser window. Let's navigate to the Py3 Coursera course, download the Jupyter Notebook files with the ipynb extensions, and their accompanying data files, and put those into the Py3 directory on our own computer. To run these files, simply navigate to our folder in terminal and type 'jupyter notebook' There you should see a folder for your files, and you'll. If you’re a data scientist or developer and upgraded to macOS Catalina 10.15, then you might have faced some issues with the jupyter notebook. The latest version of Mac Catalina functionality is. Click Download As; Choose a file format, then download your notebook. Download all of your notebooks at the same time. To download all of your Jupyter Workspace files at the same time: Launch one of your notebooks from coursera.org; In the upper right, click the Coursera logo; You'll see a file view page that lists all Jupyter resources in your.

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Released:

Python game programming in Jupyter notebooks.

Project description

Jupylet is a Python library that lets you create 2D and 3D games, graphics,

music and sound synthesizers, interactively in a Jupyter notebook. It is

intended for three types of audiences:

• Computer scientists, researchers, and students of deep reinforcement learning.
• Musicians interested in sound synthesis and live music coding.
• Kids and their parents interested in learning to program.

 

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<p float=”left”>

<img src=”docs/images/spaceship.gif” width=”256” />

<img src=”docs/images/spaceship_3d.gif” width=”384” />

</p>

## Jupylet for Kids

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 wonderfully easy to use for creating simple 2D and 3D games and

music interactively and experimentally. Change a variable or a function and

see how the game is affected immediately while running.

## Jupylet for Deep Reinforcement Learning

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

experiment with deep reinforcement learning algorithms and it includes the API

to programmatically control multiple simultaneous games and render thousands

of frames per second.

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

lines of code you can modify the colors of the game 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

also fun.

Head to [examples/22-pong-RL.ipynb](examples/22-pong-RL.ipynb) to see how to programmatically control a 2-player version of pong.

## Jupylet for Musicians

Jupylet imports ideas and methods from machine learning into the domain

of sound synthesis to easily let you create sound synthesizers as wild as you

can dream up - it includes impulse response reverb effects, colored noise

generators, resonant filters with cutoff frequency sweeping, oscillators with

LFO modulation, multi sampled instruments, and much more… And all of it in

pure Python for you to modify and experiment with.

In addition Jupylet draws inspiration from the wonderful [Sonic Pi](https://sonic-pi.net/)

and brings live loops and live music coding to Jupyter and Python. Hook up

your MIDI keyboard and take off.

See [examples/14-piano.ipynb](examples/14-piano.ipynb) for a basic demo.

## Requirements

_jupylet_ should run on Python 3.6+ 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

To install it with MIDI support type the following command instead:

pip install jupylet[midi]

If you are using Python 3.8 on Windows you also need to run following command:

python -m jupylet postinstall

Next, if you want to run the example notebooks, download the jupylet code

base. If you have [Git](https://git-scm.com/) installed type the following

command:

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

Alternatively, you can download and unzip the jupylet code base by

copying-pasting the following commands into the console:

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

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

move jupylet-master jupylet

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=”docs/images/spaceship.gif” width=”256” height=”256” />

Alternatively, you can run the same game as a Python script from the console with:

python spaceship.py

## Documentation

At the moment the bulk of Jupylet’s documentation is to be found in the [example notebooks](examples/). Head to [examples/01-hello-world.ipynb](examples/01-hello-world.ipynb) to get started.

I have started writing a [guide](https://jupylet.readthedocs.io/en/latest/). If you like Jupylet, one of the best ways to contribute to this project is to help to document it.

## Contact

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

Keywords: reinforcement learning,deep learning,synthesizers,moderngl,children,jupyter,python,games,midi,kids,RLPlatform: UNKNOWNClassifier: Development Status :: 4 - BetaClassifier: Intended Audience :: EducationClassifier: Intended Audience :: DevelopersClassifier: Intended Audience :: Science/ResearchClassifier: Topic :: EducationClassifier: Topic :: Multimedia :: GraphicsClassifier: Topic :: Multimedia :: Graphics :: 3D RenderingClassifier: Topic :: Multimedia :: Sound/AudioClassifier: Topic :: Multimedia :: Sound/Audio :: MIDIClassifier: Topic :: Multimedia :: Sound/Audio :: Sound SynthesisClassifier: Topic :: Scientific/Engineering :: Artificial IntelligenceClassifier: License :: OSI Approved :: BSD LicenseClassifier: Programming Language :: Python :: 3.6Classifier: Programming Language :: Python :: 3.7Classifier: Programming Language :: Python :: 3.8Description-Content-Type: text/markdownProvides-Extra: midi

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Getting started with JupyterLab

How To Download Jupyter Notebook On Mac

The installation guide contains more detailed instructions

Install with conda

If you use conda, you can install it with:

Install with pip

If you use pip, you can install it with:

If installing using pip install --user, you must add the user-level bin directory to your PATH environment variable in order to launch jupyter lab. If you are using a Unix derivative (FreeBSD, GNU / Linux, OS X), you can achieve this by using export PATH='$HOME/.local/bin:$PATH' command.

Run JupyterLab

Once installed, launch JupyterLab with:

Getting started with the classic Jupyter Notebook

conda

We recommend installing the classic Jupyter Notebook using the conda package manager. Either the miniconda or the miniforge conda distributions include a minimal conda installation.

Then you can install the notebook with:

Jupyter Notebook On Mac

pip

If you use pip, you can install it with:

Congratulations, you have installed Jupyter Notebook! To run the notebook, run the following command at the Terminal (Mac/Linux) or Command Prompt (Windows):

See Running the Notebook for more details.

Getting started with Voilà

Installation

Voilà can be installed using conda or pip. For more detailed instructions, consult the installation guide.

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conda

Jupyter Macos

If you use conda, you can install it with:

pip

If you use pip, you can install it with: