![]() ![]() JupyterLab is a modern redesign of Jupyter Notebook.Jupyter Notebook is a highly popular visualization software.Project Jupyter provides standards to visualize programming languages.If all these project names are getting mixed up in your head, remember these points: "IPython provides a rich architecture for interactive computing." "JupyterLab is the next-generation web-based user interface for Project Jupyter." "The notebook extends the console-based approach to interactive computing in a qualitatively new direction." "Project Jupyter exists to develop open source software, open standards, and services for interactive computing across dozens of programming languages." Any IPython file (.ipynb) can run in Jupyter projects for an incredible development experience. What does this all have to do with programming in Python? Python is the wildly popular programming language that's growing more popular for data science analysis. It also solved for Jupyter Notebook's extension challenges by building on top of an extension system that will get away from the challenges faced in extending Notebook. Its decision to start recently, when there is more certainty around standardization and how to provide a high-performance notebook experience, makes sense to me. In 2018, the JupyterLab project announced it was ready for users. 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. ![]() 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. In 2015, Jupyter notebook was released as a part of The Big Split™ of the IPython codebase. Jupyter notebook is a language-agnostic HTML notebook application for Project Jupyter. ![]() The Jupyter Notebook README gives a summary: IPython maintains a standard method of writing notebooks in the Python language, and in recent years, Jupyter projects became the place to render them. Way back in 2001, IPython, a Python-specific notebook standard, was developed by Fernando Perez. Jupyter Notebook's long history comes with some cost to flexibility.Īccording to Jupyter's blog, the project's background dating from 2011 makes it "difficult to customize and extend." That made sense as I read more about how all of these tools and standards developed over a long period. Why JupyterLab instead of Jupyter Notebook? ![]() More recently, JupyterLab launched as a more modular design for the future of Jupyter UIs.īoth Jupyter Notebook and JupyterLab allow for Python development in a more visual way and are powerful ways to edit code. Jupyter Notebook is considered to be the organization's flagship project, and it's had a massive impact on code visualization since it began back in 2011. 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. The more visible part of the Jupyter project comes in the form of its user interfaces (UIs) where developers can visually program in any language supported by a kernel. The most well-known UI under the project's umbrella is Jupyter Notebook, where users develop software in a notebook. As of today, 128 kernels are listed on the project wiki for everything from Ansible to Fortran. The original kernel is for Python, called IPython, though there are many more available. The power of Jupyter projects comes in the form of kernels, which act as a “computational engine” to execute code contained in a document. Jupyter will always be 100% open source software, free for all to use and released under the liberal terms of the modified BSD license. Project Jupyter is a non-profit, open source project, born out of the IPython Project in 2014 as it evolved to support interactive data science and scientific computing across all programming languages. Project Jupyter is the umbrella organization overseeing the design of several interactive and highly visual software development interfaces that allow for code to be executed in a visual way. Project Jupyter, Jupyter Notebook, JupyterLab, and Pythonīefore P圜on, I'd heard of Jupyter Notebook, but I never quite understood how it relates to Python. Here is a little bit about that magic and how you can get hands-on with it. I felt like a wizard when working on Python code in JupyterLab, long before I felt as confident developing data science-related Python from the command line. ![]()
0 Comments
Leave a Reply. |