Lesson 19: Virtual Environments in Python

🎯 Lesson Objective

To understand how to create and manage isolated Python environments using virtual environments, keeping project dependencies organized and avoiding conflicts.

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🧩 1. What Is a Virtual Environment?

A virtual environment is an isolated workspace that allows you to:

• Install project-specific Python packages
• Avoid conflicts with other projects
• Work on multiple Python versions simultaneously

It keeps dependencies separate from the system Python.

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⚙️ 2. Creating a Virtual Environment

✅ Using venv (built-in module)

# Create a virtual environment named 'myenv'
python -m venv myenv

• This creates a folder myenv/ with isolated Python binaries and libraries.

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🔄 3. Activating the Virtual Environment

OS	Command
Windows	myenv\Scripts\activate
macOS/Linux	source myenv/bin/activate

✅ Example:

# Activate on Windows
myenv\Scripts\activate

# Activate on Linux/macOS
source myenv/bin/activate

After activation, your command prompt shows (myenv) indicating the environment is active.

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🧰 4. Installing Packages in a Virtual Environment

pip install requests
pip install numpy

• Packages installed here do not affect system Python.
• Check installed packages:

pip list

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🧱 5. Deactivating the Virtual Environment

deactivate

• Returns to system Python.

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🔄 6. Removing a Virtual Environment

• Simply delete the environment folder:

rm -rf myenv   # macOS/Linux
rmdir /s myenv # Windows

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🛠️ 7. Requirements File

• Save installed packages for project sharing:

pip freeze > requirements.txt

• Install packages from requirements:

pip install -r requirements.txt

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🌍 8. Real-Life Example – Project Setup

1. Create virtual environment for web_scraper_project

python -m venv web_scraper_env

2. Activate environment

source web_scraper_env/bin/activate

3. Install dependencies

pip install requests beautifulsoup4

4. Run your scraper script

python scraper.py

5. Deactivate environment after work

deactivate