Python Virtual Environment – Complete Setup & Usage Guide (2025)

A virtual environment is one of the most important tools in a Python developer’s toolkit. It allows you to isolate project dependencies, prevent package conflicts, and maintain clean Python installations.

This guide explains everything about using venv, Python’s built-in virtual environment tool, step by step.

What Is a Python Virtual Environment?

A virtual environment is a self-contained directory tree that contains:

• A specific Python interpreter
• Its own site-packages directory (for pip-installed packages)
• Project-specific settings and dependencies

It avoids polluting the global Python installation and ensures different projects can use different versions of libraries.

Example Problem Without Virtual Environment:

You’re working on two projects:

• Project A uses Flask version 1.0
• Project B needs Flask version 3.0

If you install Flask globally, you can’t have both versions at the same time .

But if you create a virtual environment for each project, each one gets its own Flask version .

How to Create a Python Virtual Environment

Python comes with a built-in tool called venv for this.

Step 1: Open Terminal (macOS/Linux) or Command Prompt (Windows)

Step 2: Navigate to your project folder

If you don’t have one, create it:

mkdir myproject
cd myproject

Step 3: Create the virtual environment

python -m venv venv

• venv is the name of the folder that will store your virtual environment.
• This will create a folder named venv/ with everything you need.

How to Activate the Virtual Environment

Windows:

venv\Scripts\activate

macOS / Linux:

source venv/bin/activate

Once activated, your terminal will show something like this:

(venv) C:\Users\YourName\myproject>

This means you’re now working inside your virtual environment.

How to Deactivate It

When you’re done working:

deactivate

This takes you out of the virtual environment.

How to Install Packages Inside Virtual Environment

Now that your environment is active, use pip to install Python packages:

pip install requests flask numpy

These packages will be installed only in this environment, not globally.

How to Save and Share Your Environment

To save all your installed packages:

pip freeze > requirements.txt

This creates a file like this:

flask==2.3.3
numpy==1.25.2

Others (or your future self) can recreate the environment by running:

pip install -r requirements.txt

Typical Project Folder Structure with venv

myproject/
├── venv/                # virtual environment (ignored by Git)
├── requirements.txt     # saved packages
├── main.py              # your code
└── README.md            # description

Why Should I Use Virtual Environment?

Summary (Step-by-Step Commands)

# 1. Create project folder
mkdir myproject
cd myproject

# 2. Create virtual environment
python -m venv venv

# 3. Activate environment
# Windows:
venv\Scripts\activate
# macOS/Linux:
source venv/bin/activate

# 4. Install packages
pip install flask numpy

# 5. Save the environment
pip freeze > requirements.txt

# 6. Exit environment
deactivate

Why Use a Virtual Environment?

Summary – Virtual Environment at a Glance

FAQs – Python Virtual Environment

What is a Python virtual environment?

A Python virtual environment is an isolated folder that contains a specific version of Python and pip. It allows you to install project-specific packages without affecting your system Python or other projects.

Why should I use a virtual environment in Python?

Using a virtual environment:

• Keeps your project dependencies isolated
• Prevents version conflicts
• Makes your project easier to share and deploy
• Protects your global Python setup

How do I create a virtual environment?

Use this command inside your project folder:

python -m venv venv

This creates a new environment in the venv/ directory.

How do I activate and deactivate a virtual environment?

How do I install packages in a virtual environment?

Once the virtual environment is activated:

pip install flask pandas requests

These packages are installed only in that environment.

How do I save and load packages using requirements.txt?

To save packages:

pip freeze > requirements.txt

To load them later:

pip install -r requirements.txt

What’s the difference between venv, virtualenv, pipenv, and conda?