Setting Up Python Virtual Environment and Integrating It with VS Code

In this article, we will walk you through the process of setting up a Python virtual environment and integrating it with Visual Studio Code (VS Code) for the Auto Sales Insights project. A properly configured virtual environment ensures isolated package management and helps avoid conflicts between different projects. By the end of this guide, you will have a fully functional Python virtual environment and a project ready to begin data analysis.

Steps to Set Up Python Virtual Environment

1. Launch the Terminal in VS Code

To create a Python virtual environment, start by launching the integrated terminal in VS Code:

• Click on the Toggle Panel icon.
• If no panel is visible, a new panel will be created.
• Select Terminal from the options.

2. Check the Default Python Version

Before creating the virtual environment, it’s a good practice to check the default Python version installed on your system. Run the following command:

python --version        

3. Create the Python Virtual Environment

Once you have confirmed the Python version, create a virtual environment using the following command:

python -m venv ASI_VENV        

• This command creates a virtual environment named ASI_VENV inside the project folder.
• You can verify that the folder is created by checking the Explorer panel in VS Code.

4. Select the Python Interpreter

To ensure that VS Code uses the correct Python version from the virtual environment:

1. Press Ctrl + Shift + P (Windows) or Cmd + Shift + P (Mac) to open the Command Palette.
2. Search for Select Interpreter and click on it.
3. You will see a list of Python interpreters. Select the one that corresponds to your virtual environment (ASI_VENV).

Once selected, VS Code will be integrated with the Python virtual environment.

5. Activate the Python Virtual Environment

After selecting the interpreter, activating the virtual environment becomes easier:

• Click on the terminal toggle icon to open the terminal.
• The virtual environment should activate automatically.
• If you see a message stating that the Python virtual environment was successfully activated, you are good to go.

Note: On Windows, you might not see the virtual environment name in the terminal prompt unless you install an extension. However, the virtual environment will still be active.

6. Validate the Setup

To validate whether the Python virtual environment is correctly configured, follow these steps:

1. Check the Python version by running:
2. Create a simple Python script to confirm that everything is working as expected:

If you see the message "Hello, World!" and the terminal shows the path of the Python interpreter from ASI_VENV, your setup is complete.

Next Steps

Now that your Python virtual environment is set up and integrated with VS Code, you are ready to install dependencies like Pandas. In the next article, we will cover:

• Installing Pandas using pip.
• Running basic Pandas commands to validate the installation.

Stay tuned as we continue building the foundation for data analysis with Pandas!

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Conclusion

Setting up a Python virtual environment and integrating it with VS Code is a crucial step for any Python project. By following the steps outlined in this article, you have ensured that your Auto Sales Insights project is properly configured, isolated, and ready for advanced data analysis tasks.

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Thank you for reading. Stay tuned for the next article, where we install Pandas and validate the setup!