Notebook: Jupyter interactive Notebook

Jupyter Notebook

The Jupyter notebook is a web-based notebook environment for interactive computing.

Jupyter notebook example

Maintained versions

We maintain the two most recently released major versions of Jupyter Notebook, Notebook v5 and Classic Notebook v6. After Notebook v7.0 is released, we will no longer maintain Notebook v5. All Notebook v5 users are strongly advised to upgrade to Classic Notebook v6 as soon as possible.

The Jupyter Notebook project is currently undertaking a transition to a more modern code base built from the ground-up using JupyterLab components and extensions.

There is new stream of work which was submitted and then accepted as a Jupyter Enhancement Proposal (JEP) as part of the next version (v7): https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html

There is also a plan to continue maintaining Notebook v6 with bug and security fixes only, to ease the transition to Notebook v7: https://github.com/jupyter/notebook-team-compass/issues/5#issuecomment-1085254000

Notebook v7

The next major version of Notebook will be based on:

  • JupyterLab components for the frontend
  • Jupyter Server for the Python server

This represents a significant change to the jupyter/notebook code base.

To learn more about Notebook v7: https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html

Classic Notebook v6

Maintainance and security-related issues are now being addressed in the 6.4.x branch.

A 6.5.x branch will be soon created and will depend on nbclassic for the HTML/JavaScript/CSS assets.

New features and continuous improvement is now focused on Notebook v7 (see section above).

If you have an open pull request with a new feature or if you were planning to open one, we encourage switching over to the Jupyter Server and JupyterLab architecture, and distribute it as a server extension and / or JupyterLab prebuilt extension. That way your new feature will also be compatible with the new Notebook v7.

Jupyter notebook, the language-agnostic evolution of IPython notebook

Jupyter notebook is a language-agnostic HTML notebook application for Project Jupyter. In 2015, Jupyter notebook was released as a part of The Big Split™ of the IPython codebase. IPython 3 was the last major monolithic release containing both language-agnostic code, such as the IPython notebook, and language specific code, such as the IPython kernel for Python. As computing spans across many languages, Project Jupyter will continue to develop the language-agnostic Jupyter notebook in this repo and with the help of the community develop language specific kernels which are found in their own discrete repos.

Installation

You can find the installation documentation for the Jupyter platform, on ReadTheDocs. The documentation for advanced usage of Jupyter notebook can be found here.

For a local installation, make sure you have pip installed and run:

pip install notebook

Usage - Running Jupyter notebook

Running in a local installation

Launch with:

jupyter notebook

Running in a remote installation

You need some configuration before starting Jupyter notebook remotely. See Running a notebook server.

Development Installation

See CONTRIBUTING.md for how to set up a local development installation.

Contributing

If you are interested in contributing to the project, see CONTRIBUTING.md.

Community Guidelines and Code of Conduct

This repository is a Jupyter project and follows the Jupyter Community Guides and Code of Conduct.

Resources

Download Details:

Author: Jupyter
Source Code: https://github.com/jupyter/notebook 
License: View license

#jupyter #notebook 

What is GEEK

Buddha Community

Notebook: Jupyter interactive Notebook

Rodrigo Senra - Jupyter Notebooks

Nosso convidado de hoje é diretor técnico na Work & Co, PhD em Ciências da Computação, já contribuiu com inúmeros projetos open source em Python, ajudou a fundar a Associação Python Brasil e já foi premiado com o Prêmio Dorneles Tremea por contribuições para a comunidade Python Brasil.

#alexandre oliva #anaconda #apache zeppelin #associação python brasil #azure notebooks #beakerx #binder #c++ #closure #colaboratory #donald knuth #fernando pérez #fortran #graphql #guido van rossum #ipython #java #javascript #json #jupyter kenels #jupyter notebooks #jupyterhub #jupyterlab #latex #lisp #literate programming #lua #matlab #perl #cinerdia #prêmio dorneles tremea #python #r #rodrigo senra #scala #spark notebook #tcl #typescript #zope

Notebook: Jupyter interactive Notebook

Jupyter Notebook

The Jupyter notebook is a web-based notebook environment for interactive computing.

Jupyter notebook example

Maintained versions

We maintain the two most recently released major versions of Jupyter Notebook, Notebook v5 and Classic Notebook v6. After Notebook v7.0 is released, we will no longer maintain Notebook v5. All Notebook v5 users are strongly advised to upgrade to Classic Notebook v6 as soon as possible.

The Jupyter Notebook project is currently undertaking a transition to a more modern code base built from the ground-up using JupyterLab components and extensions.

There is new stream of work which was submitted and then accepted as a Jupyter Enhancement Proposal (JEP) as part of the next version (v7): https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html

There is also a plan to continue maintaining Notebook v6 with bug and security fixes only, to ease the transition to Notebook v7: https://github.com/jupyter/notebook-team-compass/issues/5#issuecomment-1085254000

Notebook v7

The next major version of Notebook will be based on:

  • JupyterLab components for the frontend
  • Jupyter Server for the Python server

This represents a significant change to the jupyter/notebook code base.

To learn more about Notebook v7: https://jupyter.org/enhancement-proposals/79-notebook-v7/notebook-v7.html

Classic Notebook v6

Maintainance and security-related issues are now being addressed in the 6.4.x branch.

A 6.5.x branch will be soon created and will depend on nbclassic for the HTML/JavaScript/CSS assets.

New features and continuous improvement is now focused on Notebook v7 (see section above).

If you have an open pull request with a new feature or if you were planning to open one, we encourage switching over to the Jupyter Server and JupyterLab architecture, and distribute it as a server extension and / or JupyterLab prebuilt extension. That way your new feature will also be compatible with the new Notebook v7.

Jupyter notebook, the language-agnostic evolution of IPython notebook

Jupyter notebook is a language-agnostic HTML notebook application for Project Jupyter. In 2015, Jupyter notebook was released as a part of The Big Split™ of the IPython codebase. IPython 3 was the last major monolithic release containing both language-agnostic code, such as the IPython notebook, and language specific code, such as the IPython kernel for Python. As computing spans across many languages, Project Jupyter will continue to develop the language-agnostic Jupyter notebook in this repo and with the help of the community develop language specific kernels which are found in their own discrete repos.

Installation

You can find the installation documentation for the Jupyter platform, on ReadTheDocs. The documentation for advanced usage of Jupyter notebook can be found here.

For a local installation, make sure you have pip installed and run:

pip install notebook

Usage - Running Jupyter notebook

Running in a local installation

Launch with:

jupyter notebook

Running in a remote installation

You need some configuration before starting Jupyter notebook remotely. See Running a notebook server.

Development Installation

See CONTRIBUTING.md for how to set up a local development installation.

Contributing

If you are interested in contributing to the project, see CONTRIBUTING.md.

Community Guidelines and Code of Conduct

This repository is a Jupyter project and follows the Jupyter Community Guides and Code of Conduct.

Resources

Download Details:

Author: Jupyter
Source Code: https://github.com/jupyter/notebook 
License: View license

#jupyter #notebook 

Emilie  Okumu

Emilie Okumu

1632567600

How to Create interactive Visualizations Displayed on Jupyter Notebook

Use Bokeh to create interactive visualizations displayed on Jupyter Notebook

#notebooks #jupyter 

Arne  Denesik

Arne Denesik

1603263600

Why switch to JupyterLab from jupyter-notebook?

First, let’s talk about both Lab and Notebook separately and then will talk about the differences.

Jupyter Notebook is a web-based interactive computational environment for creating Jupyter notebook documents. It supports several languages like Python (IPython), Julia, R, etc. and is mostly used for data analysis, data visualization, and other interactive, exploratory computing. For beginners in data science, jupyter notebook is more preferred; it only consists of a file browser and a (notebook) editor view, which is easier to use. When you get familiar with it and need more features(which we will talk about later), you can then definitely switch to JupyterLab.

JupyterLab is the next-generation user interface, including notebooks. It has a modular structure, where you can open several notebooks or files (e.g., HTML, Text, Markdowns, etc.) as tabs in the same window. It offers more of an IDE-like experience. JupyterLab uses the same Notebook server and file format as the classic Jupyter Notebook to be fully compatible with the existing notebooks and kernels. The Classic Notebook and Jupyterlab can run side to side on the same computer. One can easily switch between the two interfaces. The interface of both Lab and notebook are similar, except the panel of the file system on the left side in Jupyter lab. You can see that in the images below.

#programming #jupyter #jupyter-notebook #jupyterlab #data-science

Sarai  Thompson

Sarai Thompson

1625284380

Get started with Jupyter Notebook

Jupyter Notebook is an online computational notebook that allows you to combine code, comments, media, and visualizations in interactive documents. It has quickly become one of the most popular online computational notebooks, used by top companies such as Google, Microsoft, and NASA. Today, we’re going to explore Jupyter Notebooks and discuss their benefits and how to get started.

We’ll cover:

#jupyter #python #jupyter-notebook