Python virtual environments are a tool used to create isolated Python environments, each with its own set of dependencies. This isolation is beneficial for several reasons:

D: Virtual environments allow developers to create a Python environment quickly for testing and debugging purposes. This is because each virtual environment can have its own set of dependencies, which may be different from those installed globally or in other virtual environments. This isolation helps ensure that the environment reflects the production environment as closely as possible, which is crucial for accurate testing and debugging12.

E: They enable the creation of an isolated Python environment with module dependencies. This means that the dependencies installed in a virtual environment do not affect the system-wide Python installation or other virtual environments. This isolation prevents conflicts between project dependencies and allows for more precise control over the environment in which your code runs12.

References:

Automating Cisco Enterprise Solutions Official Cert Guide

Real Python’s "Python Virtual Environments: A Primer"1

Dataquest’s "A Complete Guide to Python Virtual Environments"