Working with Python in Visual Studio Code, using the Microsoft Python extension, is simple, fun, and productive. The extension makes VS Code an excellent Python editor, and works on any operating system with a variety of Python interpreters. It leverages all of VS Code's power to provide auto complete and IntelliSense, linting, debugging, and unit testing, along with the ability to easily switch between Python environments, including virtual and conda environments.
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This article provides only an overview of the different capabilities of the Python extension for VS Code. For a walkthrough of editing, running, and debugging code, use the button below.
Install Python and the Python extension
The tutorial guides you through installing Python and using the extension. You must install a Python interpreter yourself separately from the extension. For a quick install, use Python 3.7 from python.org and install the extension from the VS Code Marketplace.
Once you have a version of Python installed, activate it using the Python: Select Interpreter command. If VS Code doesn't automatically locate the interpreter you're looking for, refer to Environments - Manually specify an interpreter.
You can configure the Python extension through settings. Learn more in the Python Settings reference.
Windows Subsystem for Linux: If you are on Windows, WSL is a great way to do Python development. You can run Linux distributions on Windows and Python is often already installed. When coupled with the Remote - WSL extension, you get full VS Code editing and debugging support while running in the context of WSL. To learn more, go to Developing in WSL or try the Working in WSL tutorial.
Insiders program
The Insiders program allows you to try out and automatically install new versions of the Python extension prior to release, including new features and fixes.
Visual Studio also provides tight integration between the Python code editor and the Interactive window. The Ctrl + Enter keyboard shortcut conveniently sends the current line of code (or code block) in the editor to the Interactive window, then moves to the next line (or block). To run code: use shortcut Ctrl+Alt+N; or press F1 and then select/type Run Code, or right click the Text Editor and then click Run Code in editor context menu; or click Run Code button in editor title menu; or click Run Code button in context menu of file explorer; To stop the running code: use shortcut Ctrl+Alt+M; or press F1 and then select. Run Python program in Visual studio code on windows OSHi, Guys In this video I'm going to explainHow to download Python IDEL and its installingHow to downl. Run Python program in visual studio code on windows operating system.Hey, guys in this video I'm going to show you how you can configure visual studio code (. In Visual Studio, select File New Project (Ctrl + Shift + N), which brings up the New Project dialog. Here you browse templates across different languages, then select one for your project and specify where Visual Studio places files. To view Python templates, select Installed Python on.
If you'd like to opt into the program, you can either open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) and select Python: Switch to Insiders Daily/Weekly Channel or else you can open settings (⌘, (Windows, Linux Ctrl+,)) and look for Python: Insiders Channel to set the channel to 'daily' or 'weekly'.
Run Python code
To experience Python, create a file (using the File Explorer) named hello.py and paste in the following code (assuming Python 3):
The Python extension then provides shortcuts to run Python code in the currently selected interpreter (Python: Select Interpreter in the Command Palette):
- In the text editor: right-click anywhere in the editor and select Run Python File in Terminal. If invoked on a selection, only that selection is run.
- In Explorer: right-click a Python file and select Run Python File in Terminal.
You can also use the Terminal: Create New Integrated Terminal command to create a terminal in which VS Code automatically activates the currently selected interpreter. See Environments below. The Python: Start REPL activates a terminal with the currently selected interpreter and then runs the Python REPL.
For a more specific walkthrough on running code, see the tutorial.
Autocomplete and IntelliSense
The Python extension supports code completion and IntelliSense using the currently selected interpreter. IntelliSense is a general term for a number of features, including intelligent code completion (in-context method and variable suggestions) across all your files and for built-in and third-party modules.
IntelliSense quickly shows methods, class members, and documentation as you type, and you can trigger completions at any time with ⌃Space (Windows, Linux Ctrl+Space). You can also hover over identifiers for more information about them.
Tip: Check out the IntelliCode extension for VS Code (preview). IntelliCode provides a set of AI-assisted capabilities for IntelliSense in Python, such as inferring the most relevant auto-completions based on the current code context.
Linting
Linting analyzes your Python code for potential errors, making it easy to navigate to and correct different problems.
The Python extension can apply a number of different linters including Pylint, pycodestyle, Flake8, mypy, pydocstyle, prospector, and pylama. See Linting.
Debugging
No more print statement debugging! Set breakpoints, inspect data, and use the debug console as you run your program step by step. Debug a number of different types of Python applications, including multi-threaded, web, and remote applications.
For Python-specific details, including setting up your launch.json configuration and remote debugging, see Debugging. General VS Code debugging information is found in the debugging document. The Django and Flask tutorials also demonstrate debugging in the context of those web apps, including debugging Django page templates.
Environments
The Python extension automatically detects Python interpreters that are installed in standard locations. It also detects conda environments as well as virtual environments in the workspace folder. See Configuring Python environments. You can also use the python.pythonPath setting to point to an interpreter anywhere on your computer.
The current environment is shown on the left side of the VS Code Status Bar:
The Status Bar also indicates if no interpreter is selected:
The selected environment is used for IntelliSense, auto-completions, linting, formatting, and any other language-related feature other than debugging. It is also activated when you use run Python in a terminal.
To change the current interpreter, which includes switching to conda or virtual environments, select the interpreter name on the Status Bar or use the Python: Select Interpreter command.
VS Code prompts you with a list of detected environments as well as any you've added manually to your user settings (see Configuring Python environments).
Installing packages
Packages are installed using the Terminal panel and commands like pip install <package_name> (Windows) and pip3 install <package_name> (macOS/Linux). VS Code installs that package into your project along with its dependencies. Examples are given in the Python tutorial as well as the Django and Flask tutorials.
Jupyter notebooks
If you open a Jupyter notebook file (.ipynb) in VS Code, you can use the Jupyter Notebook Editor to directly view, modify, and run code cells.
You can also convert and open the notebook as a Python code file. The notebook's cells are delimited in the Python file with #%% comments, and the Python extension shows Run Cell or Run All Cells CodeLens. Selecting either CodeLens starts the Jupyter server and runs the cell(s) in the Python interactive window:
Opening a notebook as a Python file allows you to use all of VS Code's debugging capabilities. You can then save the notebook file and open it again as a notebook in the Notebook Editor, Jupyter, or even upload it to a service like Azure Notebooks.
Using either method, Notebook Editor or a Python file, you can also connect to a remote Jupyter server for running the code. For more information, see Jupyter support.
Testing
The Python extension supports testing with the unittest, pytest, and nose test frameworks.
To run tests, you enable one of the frameworks in settings. Each framework also has specific settings, such as arguments that identify paths and patterns for test discovery.
Once discovered, VS Code provides a variety of commands (on the Status Bar, the Command Palette, and elsewhere) to run and debug tests, including the ability to run individual test files and individual methods.
Configuration
The Python extension provides a wide variety of settings for its various features. These are described on their relevant topics, such as Editing code, Linting, Debugging, and Testing. The complete list is found in the Settings reference.
Other popular Python extensions
The Microsoft Python extension provides all of the features described previously in this article. Additional Python language support can be added to VS Code by installing other popular Python extensions.
- Open the Extensions view (⇧⌘X (Windows, Linux Ctrl+Shift+X)).
- Filter the extension list by typing 'python'.
The extensions shown above are dynamically queried. Click on an extension tile above to read the description and reviews to decide which extension is best for you. See more in the Marketplace.
Next steps
- Python Hello World tutorial - Get started with Python in VS Code.
- Editing Python - Learn about auto-completion, formatting, and refactoring for Python.
- Basic Editing - Learn about the powerful VS Code editor.
- Code Navigation - Move quickly through your source code.
Python is a popular programming language that is reliable, flexible, easy to learn, free to use on all operating systems, and supported by both a strong developer community and many free libraries. Python supports all manners of development, including web applications, web services, desktop apps, scripting, and scientific computing, and is used by many universities, scientists, casual developers, and professional developers alike. You can learn more about the language on python.org and Python for Beginners.
Visual Studio is a powerful Python IDE on Windows. Visual Studio provides open-source support for the Python language through the Python Development and Data Science workloads (Visual Studio 2017 and later) and the free Python Tools for Visual Studio extension (Visual Studio 2015 and earlier).
Python is not presently supported in Visual Studio for Mac, but is available on Mac and Linux through Visual Studio Code (see questions and answers).
To get started:
- Follow the installation instructions to set up the Python workload.
- Familiarize yourself with the Python capabilities of Visual Studio through the sections in this article.
- Go through one or more of the Quickstarts to create a project. If you're unsure, start with Create a web app with Flask.
- Go through one or more of the Quickstarts to create a project. If you're unsure, start with Quickstart: Open and run Python code in a folder or Create a web app with Flask.
- Follow the Work with Python in Visual Studio tutorial for a full end-to-end experience.
Note
Visual Studio supports Python version 2.7, as well as version 3.5 through 3.7. While it is possible to use Visual Studio to edit code written in other versions of Python, those versions are not officially supported and features such as IntelliSense and debugging might not work. Python version 3.8 support is still under development, specific details about support can be seen in this tracking issue on GitHub.
Support for multiple interpreters
Visual Studio's Python Environments window (shown below in a wide, expanded view) gives you a single place to manage all of your global Python environments, conda environments, and virtual environments. Visual Studio automatically detects installations of Python in standard locations, and allows you to configure custom installations. With each environment, you can easily manage packages, open an interactive window for that environment, and access environment folders.
Use the Open interactive window command to run Python interactively within the context of Visual Studio. Use the Open in PowerShell command to open a separate command window in the folder of the selected environment. From that command window you can run any python script.
For more information:
Rich editing, IntelliSense, and code comprehension
Visual Studio provides a first-class Python editor, including syntax coloring, auto-complete across all your code and libraries, code formatting, signature help, refactoring, linting, and type hints. Visual Studio also provides unique features like class view, Go to Definition, Find All References, and code snippets. Direct integration with the Interactive window helps you quickly develop Python code that's already saved in a file.
For more information:
- Docs: Edit Python code
- Docs: Format code
- Docs: Refactor code
- Docs: Use a linter
- General Visual Studio feature docs: Features of the code editor
Interactive window
For every Python environment known to Visual Studio, you can easily open the same interactive (REPL) environment for a Python interpreter directly within Visual Studio, rather than using a separate command prompt. You can easily switch between environments as well. (To open a separate command prompt, select your desired environment in the Python Environments window, then select the Open in PowerShell command as explained earlier under Support for multiple interpreters.)
Run Python Script In C# Visual Studio
Visual Studio also provides tight integration between the Python code editor and the Interactive window. The Ctrl+Enter keyboard shortcut conveniently sends the current line of code (or code block) in the editor to the Interactive window, then moves to the next line (or block). Ctrl+Enter lets you easily step through code without having to run the debugger. You can also send selected code to the Interactive window with the same keystroke, and easily paste code from the Interactive window into the editor. Together, these capabilities allow you to work out details for a segment of code in the Interactive window and easily save the results in a file in the editor.
Visual Studio also supports IPython/Jupyter in the REPL, including inline plots, .NET, and Windows Presentation Foundation (WPF).
For more information:
Project system, and project and item templates
Note
Visual Studio 2019 supports opening a folder containing Python code and running that code without creating Visual Studio project and solution files. For more information, see Quickstart: Open and run Python code in a folder. There are, however, benefits to using a project file, as explained in this section.
Visual Studio helps you manage the complexity of a project as it grows over time. A Visual Studio project is much more than a folder structure: it includes an understanding of how different files are used and how they relate to each other. Visual Studio helps you distinguish app code, test code, web pages, JavaScript, build scripts, and so on, which then enable file-appropriate features. A Visual Studio solution, moreover, helps you manage multiple related projects, such as a Python project and a C++ extension project.
Project and item templates automate the process of setting up different types of projects and files, saving you valuable time and relieving you from managing intricate and error-prone details. Visual Studio provides templates for web, Azure, data science, console, and other types of projects, along with templates for files like Python classes, unit tests, Azure web configuration, HTML, and even Django apps.
For more information:
- Docs: Manage Python projects
- Docs: Item templates reference
- Docs: Python project templates
- Docs: Work with C++ and Python
- General Visual Studio feature docs: Project and item templates
- General Visual Studio feature docs: Solutions and projects in Visual Studio
Full-featured debugging
One of Visual Studio's strengths is its powerful debugger. For Python in particular, Visual Studio includes Python/C++ mixed-mode debugging, remote debugging on Linux, debugging within the Interactive window, and debugging Python unit tests.
In Visual Studio 2019, you can run and debug code without having a Visual Studio project file. See Quickstart: Open and run Python code in a folder for an example.
For more information:
- Docs: Debug Python
- Docs: Python/C++ mixed-mode debugging
- Docs: Remote debugging on Linux
- General Visual Studio feature docs: Feature tour of the Visual Studio Debugger
Profiling tools with comprehensive reporting
Profiling explores how time is being spent within your application. Visual Studio supports profiling with CPython-based interpreters and includes the ability to compare performance between different profiling runs.
For more information:
- Docs: Python profiling tools
- General Visual Studio feature docs: Profiling Feature Tour. (Not all Visual Studio profiling features are available for Python).
Unit testing tools
Discover, run, and manage tests in Visual Studio Test Explorer, and easily debug unit tests.
For more information:
- Docs: Unit testing tools for Python
- General Visual Studio feature docs: Unit test your code.
Azure SDK for Python
The Azure libraries for Python simplify consuming Azure services from Windows, Mac OS X, and Linux apps. You can use them to create and manage Azure resources, as well as to connect to Azure services.
For more information, see Azure SDK for Python and Azure libraries for Python.
Questions and answers
Q. Is Python support available with Visual Studio for Mac?
A. Not at this time, but you can up vote the request on Developer Community. The Visual Studio for Mac documentation identifies the current types of development that it does support. In the meantime, Visual Studio Code on Windows, Mac, and Linux works well with Python through available extensions.
Q. What can I use to build UI with Python?
A. The main offering in this area is the Qt Project, with bindings for Python known as PySide (the official binding) (also see PySide downloads) and PyQt. At present, Python support in Visual Studio does not include any specific tools for UI development.
Q. Can a Python project produce a stand-alone executable?
A. Python is generally an interpreted language, with which code is run on demand in a suitable Python-capable environment such as Visual Studio and web servers. Visual Studio itself does not at present provide the means to create a stand-alone executable, which essentially means a program with an embedded Python interpreter. However, the Python community supplied different means to create executables as described on StackOverflow. CPython also supports being embedded within a native application, as described on the blog post, Using CPython's embeddable zip file.
Feature support
Python features can be installed in the following editions of Visual Studio as described in the installation guide:
- Visual Studio 2017 (all editions)
- Visual Studio 2015 (all editions)
- Visual Studio 2013 Community Edition
- Visual Studio 2013 Express for Web, Update 2 or higher
- Visual Studio 2013 Express for Desktop, Update 2 or higher
- Visual Studio 2013 (Pro edition or higher)
- Visual Studio 2012 (Pro edition or higher)
- Visual Studio 2010 SP1 (Pro edition or higher; .NET 4.5 required)
Visual Studio 2015 and earlier are available at visualstudio.microsoft.com/vs/older-downloads/.
Important
Features are fully supported and maintained for only the latest version of Visual Studio. Features are available in older versions but are not actively maintained.
| Python support | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Manage multiple interpreters | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Auto-detect popular interpreters | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Add custom interpreters | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Virtual Environments | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Pip/Easy Install | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Project system | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| New project from existing code | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Show all files | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Source control | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Git integration | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔1 | ✗ |
| Editing | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Syntax highlighting | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Auto-complete | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Signature help | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Quick info | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Object browser/class view | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Navigation bar | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Go to Definition | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Navigate to | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Find All References | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Auto indentation | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Code formatting | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Refactor - rename | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Refactor - extract method | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Refactor - add/remove import | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| PyLint | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Interactive window | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Interactive window | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| IPython with inline graphs | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
How To Run Python Code In Visual Studio
| Desktop | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Console/Windows application | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| IronPython WPF (with XAML designer) | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| IronPython Windows Forms | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Web | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Django web project | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔ |
| Bottle web project | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔ |
| Flask web project | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔ |
| Generic web project | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔ |
| Azure | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Deploy to web site | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔2 |
| Deploy to web role | ✔ | ✔ | ✔ | ✗ | ✔4 | ✔4 | ✔3 | ✗ |
| Deploy to worker role | ? | ? | ? | ✗ | ✔4 | ✔4 | ✔3 | ✗ |
| Run in Azure emulator | ? | ? | ? | ✗ | ✔4 | ✔4 | ✔3 | ✗ |
| Remote debugging | ✔ | ✔ | ✔ | ✗ | ✔6 | ✔8 | ✔8 | ✗ |
| Attach Server Explorer | ✔ | ✔ | ✔ | ✗ | ✔7 | ✔7 | ✗ | ✗ |
| Django templates | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Debugging | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ | ✔ |
| Auto-complete | ✔ | ✔ | ✔ | ✗ | ✔5 | ✔5 | ✔ | ✔ |
| Auto-complete for CSS and JavaScript | ✔ | ✔ | ✔ | ✗ | ✔5 | ✔5 | ✗ | ✗ |
| Debugging | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Debugging | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Debugging without a project | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Debugging - attach to editing | ✔ | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ |
| Mixed-mode debugging | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✗ |
| Remote debugging (Windows, Mac OS X, Linux) | ✔ | ✔ | ✔ | ✔ | ✗ | ✔ | ✔ | ✔ |
| Debug Interactive window | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ |
| Profiling | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Profiling | ✔ | ✔ | ✔ | ✗ | ✗ | ✔ | ✔ | ✔ |
Run Python Code In Visual Studio 2015
How To Use Visual Studio Code
| Test | 2017+ | 2015 | 2013 Comm | 2013 Desktop | 2013 Web | 2013 Pro+ | 2012 Pro+ | 2010 SP1 Pro+ |
|---|---|---|---|---|---|---|---|---|
| Test explorer | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✗ |
| Run test | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✗ |
| Debug test | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✔ | ✗ |
Run Python Code In Visual Studio 2019
Git support for Visual Studio 2012 is available in the Visual Studio Tools for Git extension, available on the Visual Studio Marketplace.
Deployment to Azure Web Site requires Azure SDK for .NET 2.1 - Visual Studio 2010 SP1. Later versions don't support Visual Studio 2010.
Support for Azure Web Role and Worker Role requires Azure SDK for .NET 2.3 - VS 2012 or later.
Support for Azure Web Role and Worker Role requires Azure SDK for .NET 2.3 - VS 2013 or later.
Django template editor in Visual Studio 2013 has some known issues that are resolved by installing Update 2.
Requires Windows 8 or later. Visual Studio 2013 Express for Web doesn't have the Attach to Process dialog, but Azure Web Site remote debugging is still possible using the Attach Debugger (Python) command in Server Explorer. Remote debugging requires Azure SDK for .NET 2.3 - Visual Studio 2013 or later.
Requires Windows 8 or later. Attach Debugger (Python) command in Server Explorer requires Azure SDK for .NET 2.3 - Visual Studio 2013 or later.
Requires Windows 8 or later.