Virtual Environments

Manage project dependencies and isolate Python environments

Why Virtual Environments?

Isolate project dependencies from system Python
Avoid version conflicts between projects
Easy to share project requirements
Keep global Python installation clean

# Virtual environments solve these problems:
# - Project A needs Django 3.2
# - Project B needs Django 4.0
# - Without venv, only one version can be installed globally
# - With venv, each project has its own isolated environment

Creating Virtual Environments

Use venv module (built into Python 3.3+)
Creates isolated Python environment in a folder
Contains its own Python interpreter and packages
Common convention: name folder 'venv' or '.venv'

# Create virtual environment
# Command: python -m venv myenv

# On Windows:
# python -m venv venv

# On Mac/Linux:
# python3 -m venv venv

# This creates a 'venv' folder with:
# - Python interpreter
# - pip package manager
# - Site-packages directory for installed packages

Activating Virtual Environments

Must activate before using the environment
Activation changes PATH to use venv's Python
Different commands for Windows vs Mac/Linux
Prompt usually shows (venv) when activated

# Activate virtual environment

# On Windows:
# venv\Scripts\activate

# On Mac/Linux:
# source venv/bin/activate

# After activation, your prompt shows:
# (venv) C:\Users\YourName\project>

# Deactivate when done:
# deactivate

Managing Dependencies

Use pip to install packages in venv
requirements.txt lists all dependencies
pip freeze saves current packages
Easy to recreate environment on another machine

# Install packages in activated venv
# pip install requests
# pip install django==4.0
# pip install pandas numpy matplotlib

# Save dependencies to file
# pip freeze > requirements.txt

# Install from requirements.txt
# pip install -r requirements.txt

# Example requirements.txt:
# requests==2.28.0
# django==4.0.0
# pandas==1.5.0

# Uninstall package
# pip uninstall requests