Glossary

A quick reference for the key terms and concepts used throughout this course.

Term	aka	Definition
Alias		A shorter nickname given to a package when importing it (e.g. import numpy as np makes np an alias for numpy). Conventional aliases (like np, pd, plt) are widely recognized and should be preferred.
API		Application Programming Interface. A defined set of functions and rules that lets you interact with a library, service, or program. When you call numpy.mean(...), you are using numpy’s API.
base		The default system-wide Python environment that is active unless you switch to another environment.
Cell		The basic unit of a Jupyter Notebook. Each cell contains either Python code or text (Markdown) and can be run independently.
conda-forge		A community-maintained package repository, common in scientific computing. Packages hosted there cannot be installed with uv — use conda, mamba, or pixi instead.
Dependencies	Packages, Libraries	The external packages that a script or notebook needs in order to run.
IDE		Integrated Development Environment. A code editor with extras like syntax highlighting, autocomplete, error detection, and AI tools. VS Code is a popular free choice.
Import		A statement (import package_name) that makes a package’s functionality available inside a script or notebook cell. Packages must be imported before they can be used, even if they are already installed.
Interpreter	Python Interpreter	The program installed on your computer that reads and executes Python code. When you run python script.py, the interpreter is what actually runs the instructions.
Jupyter Notebook	.ipynb file	An interactive file format (.ipynb — interactive python notebook) that lets you write and run Python code in small chunks called cells, and mix code with text, images, and equations.
JupyterLab		The browser-based application used to open and work with Jupyter Notebooks. Launched automatically by uvx juv run.
juv		A command-line tool built on top of uv, specifically designed for Jupyter Notebooks. It reads the ///script block of a notebook and automatically sets up the environment before launching JupyterLab.
Kernel		The Python process running behind a Jupyter Notebook. All cells in a notebook share the same kernel. If something goes wrong (stale state, infinite loop), you can restart it with the ⟳ button.
Library	Package, Dependency	See Package.
Module		A single .py file containing Python code (functions, classes, variables) that can be imported. A package is a collection of modules grouped together. For example, matplotlib.pyplot is the pyplot module inside the matplotlib package.
Package	Library, Dependency	A collection of Python code grouped together to provide a specific set of functionality (e.g. numpy for numerical computing). Packages must be installed before they can be imported.
PEP		Python Enhancement Proposal. A document that describes a new feature or convention for the Python language. See peps.python.org.
PEP 723		A PEP that defines a standard way to declare a script’s dependencies directly inside the file itself, using a ///script comment block. Both uv and juv use this standard.
///script block	inline script metadata	The special comment block defined by PEP 723, placed at the top of a .py or .ipynb file to declare its Python version and package dependencies.
pip		The standard Python package installer. uv pip install mimics and replaces it. Packages are downloaded from PyPI.
Python		Both the programming language (the rules and syntax for writing instructions) and the interpreter (the program that reads and executes those instructions).
Python Version		The specific release of Python in use (e.g. 3.11, 3.12, 3.13). Different projects may require different versions; uv can install and manage multiple versions side by side.
PyPI	Python Package Index	The central online repository at pypi.org from which pip and uv pip install download packages.
Standard Library		The collection of packages that come bundled with Python and are available by default, without any installation (e.g. packages for working with files, dates, or CSV data).
Terminal	Command line, Shell	A text-based interface for interacting with your computer’s operating system. On macOS/Linux it is called the Terminal; on Windows, use PowerShell.
uv		A modern, extremely fast tool for managing Python versions, virtual environments, and packages — all in one. Used via the uv command in the terminal.
uvx	uv tool run	A shortcut for uv tool run. Runs a command-line tool from a package on the fly, installing it into a temporary isolated environment without any manual install step.
Virtual Environment	.venv, env	An isolated workspace (a folder on your computer) containing its own Python interpreter and its own installed packages, completely separate from other environments. Prevents package conflicts between projects.

uv ↔️ conda Translation Table

If you are already familiar with conda, here is a quick translation table to help you understand how uv commands map to conda commands:

uv command	conda equivalent	Description
uv venv	conda create	Create a new virtual environment.
source .venv/bin/activate .venv\Scripts\activate	conda activate	Activate the virtual environment.
uv pip install [PACKAGE]	conda install	Install a package into the active environment.
uv pip uninstall [PACKAGE]	conda remove	Remove a package from the active environment.
uv pip list	conda list	List all packages in the active environment.