Python Development in Visual Studio Code: An Overview
Python is a popular programming language used by software developers worldwide. Its versatility and ease of use have made it a top choice for beginners and experienced programmers alike.
Visual Studio Code (VS Code) is a lightweight code editor created by Microsoft that has quickly risen to prominence and now boasts a huge following among developers. In this article, we will explore Python development in VS Code, its benefits, and how to install and configure it for optimal coding performance.
Whether you’re a seasoned developer or just starting your journey with Python development, weve got you covered.
Benefits of Visual Studio Code for Python Development
VS Code is a cross-platform code editor that runs on Windows, Linux, and macOS. It has many benefits for Python developers, including:
Interactive debugging: VS Code facilitates interactive debugging of your Python code. This feature allows you to identify and resolve issues more efficiently.
2. Intellisense: VS Code provides advanced code suggestion, enabling you to write your code faster and more accurately.
3. Git integration: VS Code integrates well with Git, a popular version control system used by developers.
4. Extensibility: VS Code has an extensive library of extensions that can enhance your coding experience.
5. Open source: VS Code is open source and free to use.
Assumptions about Reader Knowledge and System Requirements
Assuming that our readers have fundamental knowledge of Python programming language, it’s crucial to note that they would be able to use VS Code for Python development after reading this article. Additionally, as VS Code is available on all major operating systems, readers need not worry about their system requirements.
Availability of Screenshots and Demos for Ubuntu and Windows
This article will provide screenshots for both Ubuntu and Windows users, illustrating the features and functionalities of VS Code in Python development on these platforms.
Installing and Configuring Visual Studio Code for Python Development
To get started with VS Code for Python development, you first need to install it on your system. The installation process for all platforms is straightforward.
1. Download the .deb package from the official VS Code website.
2. Open the .deb package using the Ubuntu Software Center, and click the Install button.
3. After installation, launch VS Code from the terminal by typing code.
1. Download the .exe package from the official VS Code website.
2. Double-click the .exe file, and follow the on-screen instructions to install.
3. Launch VS Code directly from the Start menu or desktop.
Once you have installed VS Code, you need to configure it for Python development. Here are the steps:
Install the Python extension for VS Code from the Extensions pane on the left-hand side. 2.
After installation, you will need to configure the interpreter to point to the location of your Python installation by pressing Ctrl+Shift+P and typing “Python: Select Interpreter.”
3. VS Code will display the list of available interpreters that you have installed on your system.
Select the one you want to use for development. 4.
VS Code will automatically detect the required packages and will prompt you to install them. 5.
Once you have completed the installation of the required packages, you are ready to start using VS Code for Python development. Explanation of Visual Studio Code’s Built-In Support for Multiple Languages and Extension Model
VS Code supports many programming languages, including Python, C++, Java, and more.
The editor’s design goals are mainly to provide a lightweight and extensible code editor with the necessary features for developers building web and cloud applications. One of the standout features of VS Code is its extension model.
In conclusion, Visual Studio Code is a powerful and versatile code editor that facilitates Python development. Its ease of use, extensive library of extensions, and cross-platform support make it an attractive option for developers.
By following the steps outlined above, you can set up VS Code for Python development on your system in no time. Happy coding!
Extensions for Python Development in Visual Studio Code
Visual Studio Code is an excellent code editor for Python development. One of its primary advantages is its vast library of extensions, which can help developers to create a more personalized environment that fits their specific needs.
In this segment, we will look at the available Visual Studio Code extensions that can help boost your Python coding experience.
The Python extension is the primary extension for Python development in Visual Studio Code. This extension provides advanced features that can help you improve your efficiency and productivity.
Some of these features include:
1. IntelliSense for Python – This feature offers code completion, code navigation, syntax highlighting, and auto-formatting for Python.
2. Linting – The extension supports popular linters such as pylint and flake8.
It alerts you when there is a potential error in your code. 3.
Debugging – The extension comes with a debugger for Python. It enables you to interactively debug your code and watch expressions.
4. Virtual Environments – The extension can detect and use virtual environments for Python projects that use virtualenvwrapper, Pipenv, and Conda.
5. Unit Testing – The extension integrates with popular test frameworks such as pytest and unittest to run tests and display the test output.
Additional Extensions and Settings for Python Development
Aside from the Python extension, other extensions and settings can enhance your Python coding experience. 1.
Code Runner – This extension can run your Python code directly from the editor. 2.
MagicPython – This extension adds useful features specific to Python, such as automatic function annotations and code highlighting. 3.
Django Extensions – If you are developing a Django project, this extension provides many useful features for working with Django like autocompletion of Django-related modules, integration with Django Test Runner, syntax highlighting for Django templates, and snippets. 4.
GitLens – GitLens provides advanced Git functionality from within Visual Studio Code. 5.
Python Docstring Generator – This extension can generate a docstring template automatically based on your function definition. 6.
Settings Sync – This extension can sync your VS Code settings across multiple computers and devices. 7.
IntelliCode – IntelliCode has deep learning technology that offers AI-assisted coding, suggesting whole lines or entire functions based on your context.
Visual Studio Code Configuration Files
Visual Studio Code provides you with two types of settings: user settings and workspace settings. User settings are global and apply to all projects, while workspace settings are specific to the project you are working on.
By default, Workspace settings override User settings. However, configuration files such as the .json files in .vscode folder can assist in customizing the behavior.
User and Workspace Settings
User settings are application-level settings that apply to all instances of Visual Studio Code. They can be accessed by pressing `Ctrl (cmd)` + `,` keys.
These settings apply to the VS Code application and affect all your projects. Workspace settings are project-specific settings that override default settings for your current project.
You can enable the `auto-detect` option to detect respective settings for different projects automatically. You can also create and modify `settings.json` in the `.vscode` directory of the workspace using the vscode settings editor.
These settings are stored in the workspace folder in a `.vscode` folder and can be shared with other developers working on the same project.
Benefits of Workspace Settings
Workspace settings make it possible to use different settings for different projects, which is particularly helpful when working on similar projects, and at the same time, cater to different preferences. Instead of setting up the same preferences on a per-project basis, you can provide these settings in the settings.json file for every project.
JSON configuration files
Visual Studio Code uses JSON to store configuration files for projects. JSON is a lightweight data format that makes it easy to store and transfer data between different platforms and programming languages.
JSON files are used to store settings, preferences, and project-specific configurations. Configuration files in JSON format stored in the `.vscode` folder in the workspace or in user settings.
An example of a JSON configuration file:
In conclusion, Visual Studio Code is a popular choice for Python development. The Python extension provides advanced features, and additional extensions can enhance your coding experience.
Workspace settings and configuration files in the `.vscode` folder aid developers in customizing their environment. By using these extensions and settings, you can create an environment that suits your needs and workflow.
Starting a New Python Program in Visual Studio Code
Visual Studio Code is a popular code editor for Python development. It is packed with features that make coding more efficient and productive.
Here, we will explore the steps necessary to start a new Python program in VS Code.
Opening a New File in Visual Studio Code
The first step is to create a new file. You can create a new file by selecting `File` -> `New File` or pressing `Ctrl+N`.
It will take you to the new file tab in your currently opened window.of the Command Palette
The Command Palette is an excellent feature in Visual Studio Code that enables you to execute commands or configure settings with ease. The Command Palette can be opened by pressing `Ctrl+Shift+P`.
By typing a few characters in the Command Palette’s search bar, you can access options such as `Create New File` or `Save As.`
Saving a File with .py extension for Python Interpretation and Formatting
After creating the new file, it must be saved with the .py extension to interpret the Python language and format the code accordingly. You can save the file by selecting `File` -> `Save` or `Ctrl+S`.
Save it with a relevant name and extension type, e.g., `example.py.`
Automatic formatting and IntelliSense features for Python code
Visual Studio Code’s Integrated Development Environment provides advanced features such as automatic formatting and IntelliSense for Python code. Autoformatting can improve the readability of your code.
To format the code, you can use the keyboard shortcut `Shift+Alt+F.` Additionally, IntelliSense provides hints when writing code and is essential, especially when working with a new library. To enable IntelliSense, you must ensure that the Python extension is installed.
Running Python Code in Visual Studio Code
Visual Studio Code’s built-in terminal enables you to run Python code without leaving the editor. Here are the steps:
Open the Python file in Visual Studio Code. 2.
Right-click on the file, and select `Run Python File in Terminal` from the context menu. 3.
The Terminal pane will appear below the editor with your code output.
Using the Right-Click Context Menu to Run Python File in Terminal
If you have multiple files open, it is essential to know how to run a particular file easily. You can run the Python file by right-clicking on the file and selecting “Run Python File in Terminal” from the context menu.
Output shown in Terminal pane beneath editor window
The output will be shown in the terminal pane that appears beneath the editor window. Subsequent runs will have their output shown at the bottom of the terminal pain, with a prompt at the top of the Terminal, indicating how many entries are displayed.
Alternatively, you can use the python extension debugger to debug your program step by step.
In conclusion, starting a new Python program in Visual Studio Code is a straightforward process. By utilizing the Command Palette, automatic formatting, and IntelliSense, you can streamline your Python development workflow.
The built-in terminal in VS Code makes it easy to run Python code without leaving the editor, and the output is shown in a dedicated pane at the bottom of the window. By following these tips, you can improve productivity and write better Python code in Visual Studio Code.
Python Linting Support in Visual Studio Code
Linting in programming refers to analyzing code for potential errors, performance issues, or style inconsistencies. For Python development in Visual Studio Code, linting support is built-in.
Linting support can ensure that your code adheres to standards and does not contain potential errors. This feature can be accessed from the python extension.
Supported linters for Python in Visual Studio Code include Flake8, Pylint, and mypy. Each linter has its benefits, and it is essential to find the one that fits your development needs.
For more information about Python linting in Visual Studio Code, check out the Microsoft documentation page.
Editing an Existing Python Project in Visual Studio Code
Visual Studio Code has project-focused features that enhance the Python development experience. You can create or open a new Python project in Visual Studio Code and add files to it as needed.
Opening a Local Folder and Files in Visual Studio Code
To open an existing Python project in Visual Studio Code, follow these steps:
1. Open Visual Studio Code.
2. Click on `File` -> `Open Folder`.
3. Select the folder with your project files, and click the “Open” button.
4. You will see the `Explorer` view on the left-hand side of the screen, which will display files within your project.
Functionality of Explorer View in Activity Bar for Viewing and Editing Project Files
The Explorer view in Visual Studio Code’s Activity Bar displays your project files such as directories and file structures. This view has functionality that makes it easy to view and edit files within your project, including:
Search and Navigate you can search for files and easily navigate through your project files. 2.
Add, Delete, and Rename files and folders You can add, delete or rename files and folders effortlessly. 3.
File Diff feature the File Diff feature shows the changes made in a specific file. 4.
Integrated Terminal You can launch a terminal within the Explorer window and access it from there. 5.
Git Integration The Explorer view includes Git integration, allowing you to manage Git repositories related to the project. 6.
Multi-File Selection You can select and edit multiple files in your project simultaneously. Other essential features available on the Explorer view include folder filtering and expand/collapse directory hierarchy.
The Explorer view makes it easy to manage and navigate through your project files while working in Visual Studio Code.
In conclusion, Visual Studio Code has built-in linting support and a project-centric approach to development, which enhances the Python development experience. Linting support helps detect errors, performance issues, and style inconsistencies.
Visual Studio Code’s project-focused features such as the `Explorer` view enable programmers to easily edit, view, and manage project files. The `Explorer` view comes with various functionalities such as Git integration, multi-file selection, expand/collapse directory hierarchy, and file diff, streamlining workflows and improving productivity.
Visual Studio Code’s Python development capability ranks it among the top integrated development environments for Python programming.
Testing Support in Visual Studio Code
To ensure that your Python code works reliably and as intended, testing it is essential. Visual Studio Code without doubt offers complete testing support for Python applications.
Python Testing frameworks such as unittest, pytest, and Nose can be integrated into the Visual Studio Code’s testing support. Visual Studio Code automatically detects existing tests present in your Python code and provides the ability to execute them.
Test results can be viewed within the editor with great ease. To create new tests, one can use the Command Palette, select `Python: Create Unit Test For Class or Module`, and select the testing framework of your choice.
Alternatively, you can quickly create a new test file by right-clicking the file in the Explorer view, selecting the `New File` option, and adding `_test` to the end of the filename. Running existing tests or creating new ones can be done using the Command Palette or using the Run Tests option.