Cloud Jupyter is an open source web application used for programming, computation, and data science projects in cloud computing environments. It is based on the open source Jupyter Notebook and is created and maintained by the Jupyter Project. Cloud Jupyter is natively available in many services, including Google Colaboratory (Colab), Databricks (Azure and AWS), and Google Cloud Platform (GCP).
Originally developed in the 2014, Cloud Jupyter provides users with Jupyter Notebooks in the cloud. It specializes in data science programming, statistical analysis, and large-scale data engineering projects. Cloud Jupyter works best in collaboration, as it provides a platform to manage notebooks and code written by a team of developers.
Cloud Jupyter works in three main components: a front-end user interface, a back-end web-based kernel, and a data layer for storing users’ files. The user interface enables users to access their notebooks, setup kernels for running notebooks, and execute code. The web-based kernel is responsible for running the code as well as interfacing with the data. The data layer ensures users are able to access their files from any location or device.
Cloud Jupyter is also incredibly versatile in its file formats. It supports over 40 different file formats, including JSON, Markdown, HTML, Excel, CSV, and Python. This also means users can work with data directly in the cloud without having to download and process it on their local computer.
Overall, Cloud Jupyter provides a powerful and convenient platform for users to work with data, create models, and develop applications. It is a popular choice for many developers and data scientists, as it offers a cloud-based interactive environment and the potential to collaborate on projects together.
