Glossary

An open-source service that allows users to create sharable, interactive computing environments from Jupyter Notebooks and other repositories. Binder can reproduce a computational environment directly from a GitHub repository, providing a seamless way to share and interact with code and data.

The public service to run Binder is on https://mybinder.org, which is running BinderHub. The Binder links on most Project Pythia pages point to https://binder.projectpythia.org, which is a Pythia-specific implementation of BinderHub running on the NSF-supported Jetstream2 cloud computing service.

The underlying technology and infrastructure that powers Binder. BinderHub deploys and manages the interactive computing environments for Jupyter Notebooks, ensuring that users can access and share reproducible computational work.

Conda is an open-source, cross-platform, language-agnostic package manager and environment management system that allows you to quickly install, run, and update packages within your work environment(s). To install conda, we recommend miniconda.

See Conda documentation and the Conda cheat sheet and Useful Conda commands in the context of Project Pythia.

The Jupyter Notebook software is an open-source web application that allows you to create and share Jupyter Notebooks (*.ipynb files). Jupyter Notebooks contain executable code, LaTeX equations, visualizations (e.g., plots, pictures), and narrative text. The code does not have to just be Python, other languages such as Julia or R are supported as well. Jupyter Notebooks are celebrated for their interactive output that allows movement between code, code output, explanations, and more code - similar to how scientists think and solve problems. Jupyter Notebooks can be thought of as a living, runnable publication and make for a great presentation platform. See also Jupyter Kernels, Jupyter Lab, Jupyter Hub, Binder, and BinderHub.

Software engines and their environments (e.g., conda environments) that execute the code contained in Jupyter Notebooks.

A popular web application on which users can create and write their Jupyter Notebooks, as well as explore data, install software, etc. You can find more information on running Jupyter Lab here.

See Installing Python in Jupyter for more.

A web-based platform that authenticates users and launches Jupyter Lab applications for users on remote systems.

Miniconda is a free minimal installer for Conda. Miniconda only comes with the Conda package management system; it is a pared-down version of the full Anaconda Python distribution.

See Installing Conda.

Miniforge is the community driven and more permissively licensed minimal installer.

The NCAR Command Language (NCL) is an interpreted language designed specifically for scientific data analysis and visualization.

A Python package is a collection of modules, which, in turn, are essentially Python scripts that contain published functionality. There are Python packages for data input, data analysis, data visualization, etc. Each package offers a unique toolset and may have its own unique syntax rules. You can install Python packages with conda.