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16. Introduction to Virtual Environments

1. Introduction​

A virtual environment is an isolated Python workspace.
It lets you install packages for one project without affecting other projects or the system Python installation.

This is especially useful when:

  • Different projects require different package versions.
  • You want to avoid breaking system-installed Python packages.

2. Checking if venv is Installed​

Python 3.3+ includes the venv module by default.
Check by running:

python3 -m venv --help

If you see usage instructions, it’s available.

3. Creating a Virtual Environment​

Navigate to your project folder and run:

python3 -m venv myenv

This creates a folder called myenv that contains a local Python installation.

4. Activating the Virtual Environment​

  • On Windows (Command Prompt):
myenv\Scripts\activate
  • On PowerShell:
.\myenv\Scripts\Activate.ps1
  • On Linux/macOS:
source myenv/bin/activate

When active, your shell prompt will show (myenv).

5. Installing Packages Inside the Virtual Environment​

Once activated, any pip commands only affect the environment:

pip install requests

Check installed packages:

pip list

6. Deactivating the Environment​

To leave the virtual environment, simply run:

deactivate

7. Removing a Virtual Environment​

Since it’s just a folder, you can delete it safely:

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

8. Why Use Virtual Environments?​

  • Prevents dependency conflicts between projects.
  • Keeps your global Python installation clean.
  • Required in most professional Python projects.

9. Alternatives​

  • virtualenv: An older tool with extra features.
  • conda environments: Used with Anaconda for data science projects.
  • pipenv or poetry: Modern tools that combine dependency and environment management.

10. Next Steps​

✅ You now know how to create and use virtual environments.
In the next chapter, we’ll start exploring Python’s core language basics, beginning with variables and assignment rules.