Business & Industry Applications
Higher Education Research & Teaching


and 50–100 other languages


Data Wrangling
High Performance Computing
Big Data
Statistical Computing
Numerical Computing
Data Mining
Text Processing
Machine Learning
Computing Language
Educational Outreach
Computational thinking
Version control

Project Jupyter is a collection of open-source projects for interactive and collaborative computing. The project, which began with iPython, now supports over 50 programming languages. Jupyter Notebook, its flagship application, leverages the browser to create and share live code, visualizations, markdown text, and LaTeX equations. Many of our libraries extend the notebook application to other areas of interactive computing and scientific communication. nbconvert converts notebooks into other formats such as Reveal JS slides, PDF documents, and HTML files. ipywidgets allows users to create HTML widgets within the Notebook. JupyterHub allows the Notebook to be spawned, proxied, and managed in a multi-user environment. BinderHub shares notebooks over a public IP address with JupyterHub and Docker. nbgrader provides educators with tools to evaluate students’ code within the notebook. Our latest project, JupyterLab, allows users to interact with notebooks, kernels, software files, and data in an IDE. Project Jupyter also continues to develop IPython, a rich Python shell that can be accessed through all the Jupyter tools.
Project Jupyter (including IPython) is transforming interactive development and data exploration across multiple industries. There are now more than 2 million Jupyter notebooks on GitHub, as compared to 200,000 in 2015. GitHub has made built-in support for rendering Jupyter notebooks.

Several companies have released Jupyter-based products, including Google (Cloud DataLab), Microsoft (AzureML, HDInsight), IBM (IBM Watson Studio), and Intel (Trusted Analytics Platform). It is used in Anaconda Enterprise and Conda, and Netflix uses Jupyter internally. Quantopian has hosted notebooks for financial modeling. It is also in use at the NBA and Bloomberg.

Jupyter is used in educational materials at Software and Data Carpentries and is used in courses at many universities including: Bryn Mawr College, Cal Poly, Clemson University, George Washington University, Michigan State University, New York University, Northwestern University, UC Berkeley, and University of Sheffield.

Brookhaven National Laboratory uses Jupyter in analysis of data from scientific instruments (light sources). NASA uses it for data analysis and internally uses nbviewer for collaboration. Lawrence Berkeley National Laboratory uses Jupyter in multiple scientific projects, including KBase and a Materials Project.

Traditional published books have been written using notebooks or ship the code that accompanies the books as notebooks, such as at O’Reilly Media. News organizations are writing data-driven news articles for the traditional consumer market and sharing their code and data from those articles as notebooks.

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