Appendix A — Glossary of Python Development Terms

A.1 A

API (Application Programming Interface): A set of definitions and protocols for building and integrating application software.
Artifact: Any file or package produced during the software development process, such as documentation or distribution packages.

CI/CD (Continuous Integration/Continuous Deployment): Practices where code changes are automatically tested (CI) and deployed to production (CD) when they pass quality checks.
CLI (Command Line Interface): A text-based interface for interacting with software using commands.
Code Coverage: A measure of how much of your code is executed during testing.
Code Linting: The process of analyzing code for potential errors, style issues, and suspicious constructs.

Dependency: An external package or module that your project requires to function properly.
Docstring: A string literal specified in source code that is used to document a specific segment of code.
Dynamic Typing: A programming language feature where variable types are checked during runtime rather than compile time.
- Cookiecutter: A project templating tool that helps developers create new projects with a predefined structure, configuration files, and boilerplate code. Cookiecutter uses Jinja2 templating to customize files based on user inputs during project generation.

Entry Point: A function or method that serves as an access point to an application, module, or library.

Fixture: In testing, a piece of code that sets up a system for testing and provides test data.

Git: A distributed version control system for tracking changes in source code.
GitHub Repository Template: A repository that can be used as a starting point for new projects on GitHub.
GitHub/GitLab: Web-based platforms for hosting Git repositories with collaboration features.

Integration Testing: Testing how different parts of the system work together.

Lock File: A file that records the exact versions of dependencies needed by a project to ensure reproducible installations.

Mocking: Simulating the behavior of real objects in controlled ways during testing.
Module: A file containing Python code that can be imported and used by other Python files.
Monorepo: A software development strategy where many projects are stored in the same repository.

Namespace Package: A package split across multiple directories or distribution packages.

Package: A directory of Python modules containing an additional __init__.py file.
PEP (Python Enhancement Proposal): A design document providing information to the Python community, often proposing new features.
PEP 8: The style guide for Python code.
PyPI (Python Package Index): The official repository for third-party Python software.

Refactoring: Restructuring existing code without changing its external behavior.
Repository: A storage location for software packages and version control.
Requirements File: A file listing the dependencies required for a Python project.
Reproducible Build: A build that can be recreated exactly regardless of when or where it’s built.

Semantic Versioning: A versioning scheme in the format MAJOR.MINOR.PATCH, where each number increment indicates the type of change.
Static Analysis: Analyzing code without executing it to find potential issues.
Static Typing: Specifying variable types at compile time instead of runtime.
Stub Files: Files that contain type annotations for modules that don’t have native typing support.

Test-Driven Development (TDD): A development process where tests are written before the code.
Type Annotation: Syntax for indicating the expected type of variables, function parameters, and return values.
Type Hinting: Adding type annotations to Python code to help with static analysis and IDE assistance.

Unit Testing: Testing individual components in isolation from the rest of the system.

Virtual Environment: An isolated Python environment that allows packages to be installed for use by a particular project, without affecting other projects.

Wheel: A built-package format for Python that can be installed more quickly than source distributions.