What is a virtual environment in Python?

Virtual environment - this is an isolated environment that allows managing dependencies of different Python projects independently of each other. Each virtual environment has its own set of installed Python packages, which do not conflict with packages in the global Python installation or in other virtual environments.

Advantages of using virtual environments:

• Dependency isolation: Different projects may require different versions of the same libraries. A virtual environment ensures that dependencies of one project do not affect others.
• Clean global Python installation: Packages are installed only in the project's virtual environment, not in the global Python installation. This prevents clutter and conflicts.
• Reproducibility: Ensures that the code will work predictably regardless of the environment it is run on.
• Simplified project management: Allows easy deletion and recreation of environments for each project.

Main tools for creating and managing virtual environments in Python:

• venv (built into Python 3.3+): Recommended and most common method.
• virtualenv: Older but still popular tool, works with earlier Python versions.
• pipenv: A tool that combines dependency management and virtual environments.
• poetry: Another modern tool for managing dependencies and projects.

Example of creating a virtual environment using venv:

# Creating a virtual environment named my_env
python3 -m venv my_env

Example of activating a virtual environment:

# Activation on Linux/macOS
source my_env/bin/activate

# Activation on Windows (Command Prompt)
my_env\Scripts\activate.bat

# Activation on Windows (PowerShell)
my_env\Scripts\Activate.ps1

Example of installing a package in the activated virtual environment:

# Installing the requests package
pip install requests

Example of deactivating the virtual environment:

# Deactivating from any active virtual environment
deactivate