Python Virtual Environments - Full Tutorial for Beginners

How to Create and Manage Python Virtual Environments

1. Understanding Virtual Environments:

   • A virtual environment is a self-contained location that allows you to maintain separate and isolated environments for your Python projects.
   • It helps manage dependencies, versions, and packages without conflicts across different projects.

2. Creating a Virtual Environment:

   • Open a terminal or command prompt.
   • Navigate to the directory where you want to create the virtual environment.
   • Use the command python -m venv env_name to create a new virtual environment directory.

3. Activating the Virtual Environment:

   • For Windows: env_name\Scripts\activate.
   • For Mac or Linux: source env_name/bin/activate.
   • You should see the environment name prefix in your terminal prompt once activated.

4. Installing Packages:

   • Use pip install package_name to install packages into the virtual environment.
   • Use pip list to view the installed packages in the current environment.

5. Saving Dependencies to a File:

   • Create a requirements.txt file by running pip freeze > requirements.txt.
   • This file contains a list of all dependencies used in the environment.

6. Installing Packages from File:

   • To install packages from the requirements.txt file, use pip install -r requirements.txt.

7. Managing the Environment:

   • To deactivate the virtual environment, use the command deactivate.
   • To delete the virtual environment, you can use rm -r env_name or delete the folder manually.

8. Best Practices:

   • Create a virtual environment folder within the directory where your Python files exist.
   • Keep your custom Python code separate from the virtual environment folder.

9. Additional Tips:

   • Remember to activate the virtual environment before working on your Python project.
   • Use virtual environments to avoid conflicts between different projects' dependencies.

10. Conclusion:

    • You now have the knowledge to create, activate, install packages, and manage Python virtual environments effectively.

By following these steps, you can easily set up and manage virtual environments for your Python projects, ensuring a clean and organized development environment.