Chapter 9 Glossary
Anaconda: a free, open-source package manager, environment manager, Python distribution, and collection of over 1,500+ open source packages including and also Jupyter. https://www.anaconda.com/what-is-anaconda/
API (Application Programming Interface): a specification of what a programmer must write or define to interact with a software library.
Binder: a hosted service that allows anyone to launch their own sandboxed notebook environment from a Git repository. https://mybinder.org
cell: the area in a Jupyter notebook where you can enter markdown, or computer code.
cloud, in the: used to describe software or documents hosted on a remote computer accessed over the internet.
CSV (Comma Separated Values): referring to a comma-separated value file. A plain-text file format such that each line is a list of data separated by commas.
DataFrame A common tabular data structure with rows and columns available in R and in Python through Pandas.
execute: technical term for having the computer perform the instructions of your program. Alias for “run it.”
extension, Jupyter: in this instance, it is not a request for more time. Rather, a Jupyter extension is a bit of code, often developed by a third-party, that adds additional functionality to Jupyter. For example, a popular extension is a Table of Contents creator.
flipped classroom: a teaching style where students work on their own outside of class to learn new material (sometimes by watching recorded lectures or reading descriptive/interactive notebooks) and the come together in the classroom to practice what they’ve learned through exercises or experiments.
Git: a popular version control system (VCS) used for keeping track of changes of files over time.
IDE (Integrated Development Environment): software that assists in the development of additional software.
Jupyter: The term “Jupyter” may refer to one of a couple of different things: a community of users and developers focused on the open source software; the collection of tools and standards that, together, allow projects like the Jupyter Notebook to operate. The name refers to the three core programming languages supported: Julia, Python, and R.
JupyterHub: a cloud service that can provide access to Jupyter notebooks and environments to multiple users via a modern web browser. http://jupyter.org/hub
kernel: In Jupyter, a kernel is the packaging up of a language, and related programs needed to run it. For example, Python2 and Python3 are separate kernels.
LMS (Learning Management System): a cloud service that helps instructors manage aspects of classrooms.
load: how many students can a computer support?
Markdown: a text format that allows for basic formatting (headers, text styles, links)
mixed inline with the text. Markdown files usually have the extension
can be rendered natively by GitHub and other tools.
magic: a meta-command typically starting with one or two percent signs.
Changes the meaning of the contents of a line (one percent sign,
%) or the cell
(two percent signs,
%%) from code to a particular meta-instruction.
%%R indicates that the cell contents will be interpreted as commands
to the R language. Magics are kernel-specific (e.g., vary with the kernel in use).
nbgrader: a tool for creating, handling, and automatically grading assignments based on Jupyter notebooks. https://nbgrader.readthedocs.io
nbviewer: a web application for rendering Jupyter notebooks as static web pages, providing a URL to share and view them with a modern web browser. https://nbviewer.jupyter.org
nbconvert: a tool for converting Jupyter notebooks into other formats such as PDF, HTML, LaTeX, Markdown, reStructuredText, and others. https://nbconvert.readthedocs.io
notebook hidden state: a technical term referring to the value of variables that may have surprising results due to cells having been executed in a non-sequential order.
open source: software and documents that are created in a manner that give you rights to be able to use, and reproduce.
pattern: A “pattern” is a technical term referring to an abstract description of a labeled process. For example, “wash, rinse, repeat” is a common pattern for cleaning various objects.
scaffold: A teaching and learning pattern that provides steps in the learning process that build on prior learned knowledge.
script: a colloquial term for a computer program.
service, JupyterHub: JupyterHub can take advantage of additional separate, but integrated, software extensions. These are called “services.”
software distribution: A collection of software that is typically installed in bulk and is designed to ensure interoperability.
unit test: a technical term for a “test” for checking to see if software is operating correctly.
URL (Universal Resource Locator): the address of a resource (e.g., webpage) on the internet.
widget: a user interface (such as buttons, sliders, and checkboxes) that allow the easy control of hidden computer code.