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almond-sh/examples: A collection of Jupyter notebooks showing what you can do wi ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称:

almond-sh/examples

开源软件地址:

https://github.com/almond-sh/examples

开源编程语言:

Jupyter Notebook 99.1%

开源软件介绍:

Almond Examples Binder nbviewer Deepnote

A collection of Jupyter notebooks showing what you can do with the Almond Scala kernel.

Run interactively on Binder

The easiest way to get started is to run the examples on Binder. All your need is a browser!

Binder is an amazing service that allows you to create an executable environment out of a Git repository containing Jupyter notebooks. That way, you can play with the examples and try new things without having to install anything locally.

See Notebook Output in nbviewer

You can view the notebooks directly on GitHub, as it has a basic renderer for Jupyter notebooks. It doesn't execute any JavaScript though, which severly limits its ability to show dynamically generated plots i.e. from plotly and vegas.

A much better option is to render them through nbviewer. nbviewer supports loading notebooks directly from a repo on GitHub.

List of all notebooks in this project in nbviewer

Run interactively in Deepnote

You can also try Almond very quickly by cloning this Deepnote project with Almond kernel and examples. Deepnote offers hosted notebooks with real-time collaboration capabilities for free.

Running locally

An even better way to learn about Jupyter and Almond is to run it locally so you can try things out for yourself.

Via docker

We provide a docker image for the current almond version, based on the latest almond docker image. Run it with

docker run -it --rm -p 8888:8888 almondsh/examples:latest

Then copy the URL shown in the Docker output into your browser. To use JupyterLab instead of the classic Notebook interface, replace tree with lab after opening the URL.

Locally on your machine

To run these notebooks locally:

  1. Install Jupyter Notebook or JupyterLab
  2. Install an Almond kernel
  3. Clone the project and run jupyter notebook or jupyter lab in the project directory
  4. Open one of the example notebooks and play with it!



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