Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. The notebook extends the console-based approach to interactive computing in a qualitatively new direction, providing a web-based application suitable for capturing the whole computation process: developing, documenting, and executing code, as well as communicating the results.

Jupyter Notebook combines two components:

  • web application: a browser-based tool for interactive authoring of documents which combine explanatory text, mathematics, computations and their rich media output.
  • Notebook documents: a representation of all content visible in the web application, including inputs and outputs of the computations, explanatory text, mathematics, images, and rich media representations of objects.


JupyterLab is the next-generation web-based user interface for Project Jupyter, it’s a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible: configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular: write plugins that add new components and integrate with existing ones.

For more information on Jupyter Notebooks, visit the official documentation of Jupyter Notebook. (https://jupyter-notebook.readthedocs.io/en/latest)

For more information on JupyterLab user interface, visit the official documentation of JupyterLab. (https://jupyterlab.readthedocs.io/en/stable/user/interface.html)

User manual and installation guide: https://occopus.readthedocs.io/en/latest/tutorial-bigdata-ai.html#jupyterlab