Visual Studio Code for Python

Proper setup of the development environment is the first and critically important step in learning programming. If you plan to learn Python, it’s worth choosing an editor right away that won’t hinder the learning process, but rather accelerate it. Visual Studio Code is considered one of the most reliable solutions for beginners. It’s not a heavyweight IDE, but it offers enough functionality even for professional tasks. Its ease of installation, extensibility, and performance make it a universal tool for both educational projects and serious development.

The editor supports auto-formatting, debugging, dependency management, a terminal, and version control right out of the box.

It is also important that it is actively supported and developed by both the community and Microsoft itself. Installing and configuring VS Code for Python takes no more than 10 minutes — and after that, you’re ready to start coding.

Is Visual Studio Code Good for Python?

Visual Studio Code is considered the optimal choice for both beginners and experienced developers. It’s free, cross-platform, stable, and has a flexible extension architecture. Thanks to the official Python plugin from Microsoft and a wide range of supported features — it is a full-fledged environment for writing, debugging, and running scripts.

Advantages of using Visual Studio Code:

• Official Python support. The Python extension from Microsoft is regularly updated and supports all key features.
• Support for virtual environments. Easy switching between venv, conda, system, and custom environments.
• Integrated terminal. Ability to run commands directly in the editor without switching to a separate console.
• Debugging and breakpoints. Clear step-by-step execution with display of variables and program state.
• Automatic code formatting. Integration with black, flake8, pylint — for clean and readable code.
• Support for Jupyter Notebook. Open and run .ipynb files directly in the editor.
• Convenient dependency management. View and install libraries via the interface.
• Easy customization for any task. Extensions for Django, Flask, Pandas, NumPy, and other popular libraries.

This combination makes VS Code an ideal starting point for any beginner Python developer.

How to Setup Visual Studio Code for Python Development?

Before getting started, make sure that the Python interpreter is installed on your system. If not yet installed — follow this guide and complete the installation. Without it, the editor won’t be able to run scripts or recognize syntax.

Step-by-step Visual Studio Code setup

1. Download the editor. Go to the official website. Click Download for... (the site will detect your OS automatically) and download the installer file. Choose the version depending on your platform:

• Windows — .exe
• macOS — .dmg
• Linux — .deb, .rpm or archive

2. Install the editor

Once downloaded, install VS Code:

• Windows: run the .exe, leave all options as default, especially check Add to PATH.
• macOS: drag the application to the Applications folder.
• Linux: use terminal or package manager installation.

3. First Launch and Language Setup

After installation, open the editor and follow these steps:

• Go to the Extensions section (cube icon on the left or Ctrl+Shift+X shortcut).
• Type Python in the search bar.
• Install Python Extension for Visual Studio Code by Microsoft.
• Restart the editor.

After this, Visual Studio Code will automatically recognize .py files and prompt you to select an interpreter.

4. Selecting an Interpreter (mandatory!)

Open the Command Palette (Ctrl+Shift+P) → type Python: Select Interpreter.

You will see a list of available installed interpreters and environments. Choose the appropriate Python version (usually Python 3.x in the folder /usr/bin/, C:\Users\...\AppData\, or a virtual environment like .venv).

Without selecting an interpreter, the editor won't be able to run scripts, install dependencies, or provide code suggestions.

5. Creating and Running Your First Script

• Click File → New File, select file type: Python or save with the .py extension.
• Enter, for example:

• Save the file.
• Run the script: right-click → Run Python File in Terminal or press Ctrl+F5.

If everything is done correctly, you'll see the script output at the bottom of the terminal.

Other VS Code Installation Methods

Visual Studio Code can be installed not only via the website. Different systems offer alternative methods that simplify installation and updates via command line. Below is a list of methods with brief descriptions:

• Winget (Windows). Install using winget install --id Microsoft.VisualStudioCode. Convenient for automation on Windows 10/11.
• Microsoft Store (Windows). Quick install with minimal configuration. Suitable for beginners.
• Chocolatey Software (Windows). Command: choco install vscode. Used in CI/CD and system administration.
• Scoop (Windows). Simple installation via scoop install vscode.
• Homebrew (macOS). Install with brew install --cask visual-studio-code. Works for macOS and Linux with Homebrew installed.
• Snap Store (Linux). Install using sudo snap install code --classic. Easy integration for Ubuntu and derivatives.
• APT (Debian/Ubuntu). Add the Microsoft repository and run sudo apt install code.
• Flatpak. Install with flatpak install flathub com.visualstudio.code.

Each method installs the full version of the editor with extension and update support.

How to Install Python Extension?

To fully work with the Python programming language in Visual Studio Code, you need to install the official Python extension. This extension provides syntax support, debugging, autocomplete, and other tools to simplify development.

Step-by-step guide:

1. Open Visual Studio Code.
2. Go to the Extensions section:
   • Click the Extensions icon on the sidebar or use the shortcut Ctrl+Shift+X.
3. Find the Python extension:
   • Type Python in the search bar.
   • In the results, select the extension from Microsoft with a yellow snake icon.
4. Install the extension:
   • Click the Install button.
   • After the installation, it's recommended to restart VS Code to ensure the extension works properly.
5. Select the Python interpreter:
   • After restarting, open the Command Palette by pressing Ctrl+Shift+P.
   • Type Python: Select Interpreter and choose the relevant command.
   • In the list that appears, select the appropriate interpreter version.

List of Essential Python Extensions

After installing the core Python extension from Microsoft, you can significantly enhance the editor's functionality with additional tools. Below is a list of the most useful extensions that will simplify development, improve code quality, and increase productivity. These additions are suitable for both beginners and those planning to move on to more serious projects.

Pylance

Purpose: intelligent autocompletion, type hints, code analysis
Description: official extension by Microsoft, works alongside the Python Extension. Provides fast and accurate code analysis, enhances IntelliSense functionality, displays variable types, and helps catch errors before running the script.
Recommended: must-have installation.

Jupyter

Purpose: Working with Jupyter Notebook within VS Code
Description: Allows opening .ipynb files directly in the editor, running cells, viewing graphs, and using Markdown blocks. Ideal for Data Science, machine learning, and data analysis.
Recommended: For those working with data and models.

Flake8

Purpose: Code style analysis and detection of syntax errors
Description: Integration of the Flake8 linter into the editor. Checks code style for compliance with the PEP8 standard, helps maintain a consistent coding style.
Recommended: For everyone who wants to write clean and readable code.

Black Formatter

Purpose: Automatic Python code formatting
Description: Automatically formats code according to strict rules. Eliminates inconsistencies in indents, spaces, quotes, and brackets. Works quickly and stably.
Recommended: Especially useful for team development.

isort

Purpose: Sorting imports
Description: Automatically groups and sorts imports alphabetically and logically. Improves readability, eliminates duplicates. Works perfectly with Black.
Recommended: For those working with large files and libraries.

Python Environment Manager

Purpose: Managing virtual environments
Description: Allows creating, activating, and deleting venv, conda, and other environments directly from the interface. Simplifies working with dependencies.
Recommended: For beginners and those working on multiple projects.

Test Explorer for Python

Purpose: Running and managing tests
Description: Visual interface for testing with support for unittest, pytest, and other frameworks. Shows results, errors, and coverage.
Recommended: For those writing automated tests and debugging.

Visual Studio IntelliCode

Purpose: AI-based smart suggestions
Description: Enhances auto-completion considering context, suggests the most likely options based on analysis of popular code.
Recommended: For speeding up work with large projects.

These extensions help create a complete development environment based on Visual Studio Code. Install them as needed—don't overload the editor immediately. Start with Pylance, Black, and Jupyter—this is sufficient for comfortable work at the beginning.

Python Environments in VS Code

Working with environments allows you to use different versions of libraries and the interpreter within a single project. This is especially important if you are developing multiple applications with different dependencies.

Types of environments and their features:

How to Create Python Environments

Setting up virtual environments in Visual Studio Code (VS Code) plays a crucial role in effective Python development. Virtual environments allow you to isolate dependencies of different projects, preventing package conflicts and maintaining a clean workspace. Below are the main methods for creating and managing virtual environments in VS Code.

1. Using the Create Environment command

VS Code has a built-in command to simplify the process of creating virtual environments:

1. Open the command palette: press Ctrl+Shift+P and type Python: Create Environment.
2. Select the environment type: a list will appear with options — Venv or Conda.
   • Venv: the standard tool for creating virtual environments in Python.
   • Conda: used in Anaconda to manage packages and environments, especially in scientific computing.
3. Select the interpreter: after choosing the environment type, a list of available interpreters will be displayed. Select the one suitable for your project.
4. Creation process: VS Code will create a virtual environment in the project's root folder and install the necessary dependencies listed in the requirements.txt, pyproject.toml, or environment.yml files, if present.
5. Activating the environment: once created, the environment will be automatically activated in the VS Code terminal.

2. Manually creating a virtual environment via the terminal

If you prefer to create virtual environments manually:

1. Open the terminal in VS Code.
2. Enter the command to create the environment:

• On macOS/Linux:

• On Windows:

Here .venv is the name of the folder for the virtual environment.

3. Activating the environment:

• On macOS/Linux:

• On Windows (Command Prompt):

• On Windows (PowerShell):

4. Installing dependencies: after activating the environment, install the required packages:

3. Creating a Conda environment via the terminal

For Anaconda users:

1. Open the terminal in VS Code.
2. Enter the command to create the environment:

Here myenv is the name of the new environment, and python=3.9 specifies the Python version.

3. Activating the environment:

4. Installing packages:

4. Selecting and Activating the Environment in VS Code

After creating the environment, you need to tell VS Code to use it:

1. Open the command palette: Ctrl+Shift+P and type Python: Select Interpreter.
2. Select the desired environment from the list. If it doesn’t appear, use the Enter interpreter path... option and manually provide the path to the interpreter.

5. Enabling automatic environment activation in the terminal

To ensure VS Code automatically activates the selected environment when opening a new terminal:

1. Open Settings: File > Preferences > Settings.
2. Search for the setting: Python › Terminal: Activate Environment.
3. Ensure it is enabled: this will make sure the environment is activated automatically in the terminal.

Setting up and using virtual environments in VS Code contributes to a more organized and efficient development process, allowing you to isolate dependencies and avoid conflicts between projects.

Frequently Asked Questions