How to Create a Python Project with VS Code

Edited 2 days ago by ExtremeHow Editorial Team

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Creating a Python project using Visual Studio Code (VS Code) is a straightforward process that can greatly benefit both beginners and experienced programmers. VS Code is a versatile and lightweight code editor developed by Microsoft that supports various programming languages, especially Python. It offers features such as debugging, task running, version control, and an extensive marketplace for extensions to enhance your coding experience. This step-by-step guide will help you set up a Python project from scratch using VS Code.

Requirements

Before we begin, make sure you have the following prerequisites installed on your computer:

• Python Runtime: You need to download and install Python from the official Python website. Make sure the installation option to add Python to your system's PATH variable is enabled.
• VS Code: Available from the official Visual Studio Code website, VS Code is a free source-code editor.
• Python Extension for VS Code: This extension provides all the necessary support for coding in Python, such as Intellisense (code autocompletion), linting, and debugging. It can be easily installed from the VS Code Extension Marketplace.

Installing VS Code

To begin, download the VS Code installer for your operating system from the official website. Follow the installation instructions provided, making sure all the required components, especially those related to development, are selected. Once installed, launch VS Code.

Setting up the Python environment

Installing Python

To install Python, visit the official Python website and download the installer for your OS. Run the installer and choose the configuration options that best suit you, making sure to add Python to the system PATH if prompted.

Installing Python Extensions in VS Code

Launch VS Code and open the Extensions view by clicking the extensions icon in the Activity Bar on the side of the window or using the Ctrl+Shift+X shortcut. Search for "Python" in the Extension Marketplace. Click Install to add the Python extension by Microsoft. This extension adds essential Python-specific features to the editor, which are necessary for developing Python applications.

Creating a new Python project

After setting up Python and the required extensions, the next step is to create a new Python project. You can do this using VS Code with the following method:

Opening a new workplace

A workspace in VS Code is a container in which you can manage your Python project files. To get started, open VS Code, and select “Open Folder” from the File menu. Create a new folder in your desired directory where you want to store your Python project files. Once the folder is created, select it and open it in VS Code.

Creating a Python file

Inside your project folder, create a new Python file. You can do this by clicking the "New File" icon in the Explorer view (the left sidebar with the folders/files) or by using the File menu and selecting "New File". Name it something descriptive, such as main.py This will be your main Python script file where you will write your code.

Writing Python code

Python is an interpreted language, so you can write and execute your code immediately after creating your Python file.

Writing a simple program

To begin, let's create a simple program that prints "Hello, World!" to the console. This can be done by writing the following code in your main.py file:

print("Hello, World!")

Running your Python code

To run your Python script, you have several options. The easiest way is to open the terminal directly in VS Code. You can open the terminal by selecting "Terminal" in the top menu and then "New Terminal". In the terminal, make sure you are in the correct directory that contains your main.py file, and execute the script by typing the command:

python main.py

If everything is set up correctly, its output should be like this:

Hello, World!

Using the VS Code Debugger

One of the powerful features of VS Code is its built-in debugger, which can be used to identify and fix problems in your code. To use the debugger, set a breakpoint in your script file by clicking in the gutter to the left of the line numbers. This will create a small red dot indicating where the execution of your script will stop.

Configuring the debugger

To start debugging, go to the Debug icon in the Activity bar and click the gear icon to open launch.json configuration file. VS Code will suggest a default configuration for Python projects, which you can adjust as needed.

Example launch.json configuration:

{ "version": "0.2.0", "configurations": [ { "name": "Python: Current File", "type": "python", "request": "launch", "program": "${file}", "console": "integratedTerminal" } ] }

Starting a debug session

After setting breakpoints and verifying your debugger configuration, start the debugger by pressing F5 or clicking the "Start Debugging" option in the Debug menu. Your Python script will run and stop execution at the breakpoint, allowing you to inspect variables, step through the code, and identify any problems.

Managing Python project dependencies

Managing dependencies is crucial for any Python project, and it can be managed efficiently using virtual environments.

Creation of virtual environments

In your project folder, create a virtual environment by running the following command in the terminal:

python -m venv venv

This command will create a new directory named venv that will contain a standalone Python installation along with other scripts and executables. It is a best practice to organize your dependencies separately from the global packages installed on your system.

Activating the virtual environment

To activate the virtual environment, run:

• for Windows:

  .\venv\Scripts\activate

• For MacOS/Linux:

  source venv/bin/activate

Once activated, your terminal prompt should reflect the active environment, usually by prefixing the command line with (venv).

Installing packages using pip

When the virtual environment is activated, you can install packages using pip. For example, if your project requires the numpy package, install it with the command:

pip install numpy

To freeze your current environment dependencies into a requirements.txt file that you can submit to your version control repository, use:

pip freeze > requirements.txt

Later, anyone with access to your project can install the dependencies by running pip install -r requirements.txt.

Using Git version control

Git is an essential tool for managing code versions and collaborating with others. VS Code has built-in Git support that makes it easy to track changes and collaborate on projects.

Initializing the Git Repository

To initialize a Git repository in your project folder, open the terminal in VS Code and type:

git init

This command creates a new Git repository in your project directory. Your project folder now contains a .git directory, which is hidden by default.

Making your first commitment

After the repository is initialized, make your first commit by staging any changes and committing them. Use these commands:

git add . 
git commit -m "Initial commit"

The first command stages all files, and the second one commits with the message "Initial commit".

Using the Source Control view

VS Code provides an intuitive UI for Git operations. Click the Source Control icon from the Activity bar to view a list of changes, stage changes, and make commits using the VS Code interface.

Summary

Visual Studio Code provides a highly integrated development environment that supports the entire lifecycle of a Python project, from writing and running code to debugging, managing dependencies, and version control.

This guide covers installing VS Code, setting up Python, creating a project workspace, writing and executing code, using debugging tools, managing dependencies with virtual environments, and integrating Git version control. By effectively leveraging these tools, you can streamline the process of developing, testing, and deploying Python applications, increasing both individual and collaborative coding productivity.

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