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A Jupyter Notebook document is a JSON file, following a versioned schema, usually ending with the ".ipynb" extension. The main parts of the Jupyter Notebooks are: Metadata, Notebook format and list of cells. Metadata is a data Dictionary of definitions to set up and display the notebook. Notebook Format is a version number of the software.
IPython continued to exist as a Python shell and kernel for Jupyter, but the notebook interface and other language-agnostic parts of IPython were moved under the Jupyter name. [11] [12] Jupyter is language agnostic and its name is a reference to core programming languages supported by Jupyter, which are Julia, Python, and R. [13]
A notebook interface or computational notebook is a virtual notebook environment used for literate programming, a method of writing computer programs. [1] Some notebooks are WYSIWYG environments including executable calculations embedded in formatted documents; others separate calculations and text into separate sections.
It also launched PyData community workshops and the Jupyter Cloud Notebook service (Wakari.io). [14] In 2013, it received funding from DARPA. [20] In 2015, the company had two million users including 200 of the Fortune 500 companies [10] and raised $24 million in a Series A funding round led by General Catalyst and BuildGroup. [21]
A common use of Binder is for sharing a Jupyter notebook in a way that the recipient can immediately execute in a browser. [3] The Binder project maintains core libraries and documentation for running Binder services, which make those projects available, as well as BinderHub, a tool for deploying such services via common cloud computing ...
LeDock utilizes a simulated annealing and genetic algorithm approach for facilitating the docking process of ligands with protein targets. The software employs a knowledge-based scoring scheme that is derived from extensive prospective virtual screening campaigns.
Mojo is a programming language in the Python family that is currently under development. [10] [11] [12] It is available both in browsers via Jupyter notebooks, [12] [13] and locally on Linux and macOS.
Scientific tools integration: integrates with Jupyter Notebook, supports Anaconda as well as multiple scientific packages including Matplotlib and NumPy. Front-end and back-end web development: special support for Django, [9] Flask, [10] FastAPI [11] and Pyramid, [12] CSS [13] and JavaScript [14] assistance, Npm, Webpack and other JavaScript tools