Hosting
This chapter provides an introduction to popular hosting providers.
Binder
Binder is a cloud-based platform that allows users to share and execute Jupyter Notebooks as interactive environments. It utilizes Docker containers to create custom environments for notebooks and provides public and private hosting options. Binder runs on a public infrastructure and is provided as a free service by the Binder team.
BinderHub
BinderLab is a development environment for JupyterLab that runs on top of Binder. It allows users to create and run custom JupyterLab environments and provides a collaborative workspace for multiple users. Unlike Binder, BinderLab is designed for development purposes rather than just sharing and executing notebooks.
BitBucket
BitBucket is a popular hosting provider for Git repositories. It provides users with a cloud-based platform to store and manage their Git projects, and includes features such as code collaboration and continuous integration.
DockerHub
DockerHub is a cloud-based repository for Docker images and containers. It provides users with a centralized location to store, manage and share their Docker images, and allows for easy distribution and deployment of containerized applications. DockerHub also provides features such as automated builds, which allows users to automatically build Docker images from source code repositories.
GitHub
GitHub is a widely used platform for hosting Git repositories, collaborating on code, and managing projects. In addition to hosting Git repositories, GitHub provides users with a variety of tools for project management, such as issue tracking, code reviews, and continuous integration.
GitHub Pages
GitHub Pages is a free service for hosting static websites directly from a GitHub repository. Users can create websites using static site generators or by manually writing HTML, CSS, and JavaScript. GitHub Pages also provides custom domain support, SSL encryption, and GitHub Actions for automating website builds and deployments.
JupyterHub
JupyterHub is a multi-user server for Jupyter Notebooks that allows multiple users to access and use the same Jupyter Notebook environment simultaneously.
Choosing Hosting for Jupyter Notebooks
The choice of platform to share a Jupyter Notebook depends on the intended use case, audience, and level of collaboration required.
Here are some guidelines for when to use each platform.
GitHub
Use GitHub to share Jupyter Notebooks that are part of a larger project, and to collaborate on code with others. GitHub provides version control, code reviews, and issue tracking, making it an ideal platform for collaborating on code. However, GitHub is not optimized for executing Jupyter Notebooks in the cloud, and users may need to download and run the notebooks locally to interact with them.
Binder
Use Binder to share Jupyter Notebooks that require specific software dependencies, or to share a single notebook with a small group of users. Binder provides a cloud-based environment that allows users to interact with Jupyter Notebooks directly in their web browser, without having to install any software. However, Binder is not intended for large-scale collaboration, and may not be suitable for running notebooks with high computational requirements.
BinderHub
Use BinderHub to create a custom, scalable cloud-based environment for running Jupyter Notebooks. BinderHub is built on top of Kubernetes and Docker, providing automatic scaling and load balancing for your Jupyter Notebook environments. BinderHub is suitable for sharing Jupyter Notebooks with a large audience, and provides customizable environments and version control integration. However, setting up and managing a BinderHub instance requires technical expertise and resources.
JupyterHub
Use JupyterHub to provide a shared computing environment for a group of users. JupyterHub allows multiple users to access and use the same Jupyter Notebook environment simultaneously, making it suitable for classroom settings or collaborative research projects. JupyterHub provides user authentication and access control, and can be customized to provide specific software dependencies and resources for different groups of users. However, setting up and managing a JupyterHub instance requires technical expertise and resources.