Significance of Python Virtual Environment

A Python Virtual Environment is a self-contained directory which contains specific Python interpreter and its own set of installed packages, completely isolated from the global Python installation (system-wide).
Why Python Virtual Environment is important?

1. Project Isolation
   Each project has its own dependencies, versions and configurations without affecting one another.
   Example:-
   Project A works in Django==3.2
   Project B works in Django==4.0
   With virtual environment both can run without any conflicts.

2. Avoids Global package pollution
   Installing packages globally can cause
   • Version conflicts
   • Overwriting
   • Errors in system tools or other projects
   Virtual Environment avoid this by keeping packages local to the projects.

3. Reproducibility
   You can freeze all packages used in a project into a requirements.txt file and recreate the environment anywhere.
   bash
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pip freeze > requirements.txt
Later...
pip install -r requirements.txt
   Useful in team work, deployment tc.

4. No Need of Admin Rights
   You don’t need administrator/root permissions to install packages inside a virtual environment.
   Great for restricted systems like University servers or Corporate machines.

5. Cleaner Development
   You can easily create, activate, and delete environments without affecting anything outside your project.
   How to use Virtual Environment?

6. Create a Virtual Environment
   bash
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python -m venv myenv

7. Activate Virtual environment
   • On windows
   bash
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myenv\Scripts\activate
   • On Linux/macOS
   bash
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source myenv/bin/activate
   Now our shell prompt will change to show (myenv)—you're working inside the environment.

8. Install Packages Locally
   bash
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pip install requests
   requests will only be available inside myenv, not system-wide.

9. Deactivate
   bash
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Deactivate
   Using Virtual Environment in PyCharm
   When Creating a New Project:

10. Go to File > New Project

11. Select "New environment using venv"

12. PyCharm will automatically create and use that virtual environment.
    For Existing Project:

13. File > Settings > Project > Python Interpreter

14. Click Add

15. Choose “Existing environment”
    Now PyCharm will run project using the virtual environment.