Virtual Environment in Python

A Virtual Environment in Python is an isolated environment that allows you to install and manage project-specific packages without affecting the global Python installation.

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Why Use Virtual Environment?

• Avoids package version conflicts
• Keeps project dependencies isolated
• Makes projects portable and reproducible
• Best practice for automation and development

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Problem Without Virtual Environment

Suppose one project needs selenium 3 and another needs selenium 4. Installing both globally will cause conflicts.

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Types of Virtual Environments in Python

• venv (Built-in module)
• virtualenv (Third-party)
• conda (Anaconda)

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Create Virtual Environment Using venv

Step 1: Check Python Version

python --version

Step 2: Create Virtual Environment

python -m venv myenv

This will create a folder named myenv.

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Activate Virtual Environment

Windows

myenv\Scripts\activate

Linux / Mac

source myenv/bin/activate

After activation, the environment name appears in the terminal.

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Deactivate Virtual Environment

deactivate

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Installing Packages Inside Virtual Environment

pip install selenium
pip install requests

Packages installed inside the virtual environment are available only to that environment.

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List Installed Packages

pip list

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Freeze Dependencies (requirements.txt)

Used to share exact package versions with others.

pip freeze > requirements.txt

Install from requirements.txt

pip install -r requirements.txt

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Virtual Environment in Automation Testing

automation_project/
│
├── venv/
├── tests/
├── pages/
├── utils/
├── requirements.txt
└── README.md

Common packages:

• selenium
• robotframework
• requests
• pytest

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Common Mistakes

• Forgetting to activate virtual environment
• Installing packages globally by mistake
• Not sharing requirements.txt

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Best Practices

• Create one virtual environment per project
• Never commit venv folder to Git
• Always use requirements.txt
• Use meaningful environment names

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Common Interview Questions

• What is a virtual environment?
• Why do we need virtual environments?
• Difference between venv and virtualenv?
• What is requirements.txt?

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Conclusion

Using a virtual environment is a best practice in Python development and automation testing. It keeps dependencies clean, isolated, and manageable across projects.

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