Installation

Guide for Python and Visual Studio Code

Step 1: Download and Install Python

1. Go to the Python download page
   • Visit the official Python download page.
2. Download the appropriate installer
   • Choose the correct version for your operating system:
     • Windows: .exe installer (64-bit recommended)
     • macOS: .pkg file
     • Linux: Python is often pre-installed; otherwise, install it via the package manager (apt, dnf, yum, etc.).
3. Start the installation
   • Run the installer.
   • Important: Check the box “Add Python to PATH”.
   • Click “Install Now” or “Customize Installation” if you need to adjust specific settings.
4. Verify the installation
   • Open a terminal or command prompt and enter:

     python --version
     

   • If the command does not work, restart your computer and check if Python is added to the PATH.

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Step 2: Download and Install Visual Studio Code

1. Go to the Visual Studio Code download page
   • Visit the official VS Code download page.
2. Download the appropriate installer
   • Choose the correct installer for your operating system:
     • Windows: .exe
     • macOS: .zip or .dmg
     • Linux: .deb or .rpm
3. Start the installation
   • Run the installer and follow the instructions.
   • Windows users: Enable the option “Add to PATH” if available.
4. Verify the installation
   • Open a terminal or command prompt and enter:

     code --version
     

   • If VS Code starts or displays the version, the installation was successful.

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Step 3: Install Extensions in Visual Studio Code

1. Install the Python extension

1. Open Visual Studio Code.
2. Open the Extensions view
   • Click on the Extensions icon or press Ctrl+Shift+X.
3. Search for the Python extension
   • Type “Python” in the search bar.
   • Select the Python extension by Microsoft and click Install.

2. Install the Jupyter extension

1. Open the Extensions view (Ctrl+Shift+X).
2. Search for the Jupyter extension
   • Type “Jupyter” in the search bar.
   • Select the Jupyter extension by Microsoft and install it.

3. Additional Tests After Installation

Run Python in VS Code

1. Open VS Code.
2. Create a new file test.py with the following content:

   print("Hello, world!")
   

3. Press F5 or go to Run → Run Python File.

Test Jupyter Notebook

1. Open VS Code.
2. Create a new file test.ipynb.
3. Add a new cell and write:

   print("Jupyter Notebook is running!")
   

4. Run the cell.

4. Check and Select the Python Interpreter in VS Code

After installing Python and Visual Studio Code, it’s important to make sure the correct Python interpreter is selected.

Use the Command Palette

1. Open VS Code.
2. Press Ctrl+Shift+P (or Cmd+Shift+P on macOS) to open the Command Palette.
3. Type Python: Select Interpreter and hit Enter.
4. Select the interpreter you want to use (e.g. a global install, virtual environment, or Conda environment).
5. VS Code will remember your selection per workspace/project.

💡 Why this is powerful:

One of the biggest advantages of VS Code is that you can assign a different Python interpreter or environment per project.
This means:

• Different Python versions for different projects
• Clean and isolated environments (especially useful for data science or academic projects)
• No interference between project dependencies

(Optional): Install Miniconda

Miniconda is optional but useful if you’re working in Data Science, AI, or scientific computing.

What is Miniconda?

Miniconda is a minimal version of Anaconda. It allows you to create isolated Python environments and install scientific packages more easily.

Install Miniconda

1. Download Miniconda
   • https://docs.conda.io/en/latest/miniconda.html
2. Run the installer
   • For Windows, you may select “Add Miniconda to my PATH environment variable” (only if you are not using another Python version).
3. Verify the installation
   • Open a terminal and run:

     conda --version
     conda create -n myproject python=3.11
     conda activate myproject
     

(Optional): Use Miniconda with VS Code

Miniconda works seamlessly with Visual Studio Code and is ideal for creating isolated environments with specific Python versions and packages.

1. Create a new environment
   Open your terminal (or Anaconda Prompt on Windows):

   conda create -n myenv python=3.11
   conda activate myenv
   

2. Install packages (optional)
   You can install packages like numpy or pandas:

   conda install numpy pandas
   

3. Launch VS Code from the same terminal
   This ensures the environment is automatically detected:

   code .
   

4. Or manually select the environment in VS Code
   • Open VS Code
   • Press Ctrl+Shift+P → Python: Select Interpreter
   • Choose the one that looks like: Python 3.11.x ('myenv': conda)

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With this setup, you can work efficiently on multiple Python projects, each with its own isolated environment.