We highly recommend installing Python using the standard binary distributions from python.org. These will automatically install Tcl/Tk, which of course, is needed by Tkinter. If you're instead building Python from source code, the Visual Studio projects included in the 'PCbuild' directory can automatically fetch and compile Tcl/Tk on your system. Jul 09, 2019 At the bottom left cornet of VS Code window, you can see the Python version as well. Now Visual Studio Code is ready for interpret and run Python code. It is time to create a Python source code in VS Code and check it. Create Your First Python Code In VS Code.

1. Get Started Tutorial For Python In Visual Studio Code
2. Cached
3. Mac Os Visual Studio Code Python 3

One of the coolest code editors available to programmers, Visual Studio Code, is an open-source, extensible, light-weight editor available on all platforms. It’s these qualities that make Visual Studio Code from Microsoft very popular, and a great platform for Python development.

In this article, you’ll learn about Python development in Visual Studio Code, including how to:

• Install Visual Studio Code
• Discover and install extensions that make Python development easy
• Write a simple Python application
• Learn how to run and debug existing Python programs in VS Code
• Connect Visual Studio Code to Git and GitHub to share your code with the world

We assume you are familiar with Python development and already have some form of Python installed on your system (Python 2.7, Python 3.6/3.7, Anaconda, or others). Screenshots and demos for Ubuntu and Windows are provided. Because Visual Studio Code runs on all major platforms, you may see slightly different UI elements and may need to modify certain commands.

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Installing and Configuring Visual Studio Code for Python Development

Installing Visual Studio Code is very accessible on any platform. Full instructions for Windows, Mac, and Linux are available, and the editor is updated monthly with new features and bug fixes. You can find everything at the Visual Studio Code website:

In case you were wondering, Visual Studio Code (or VS Code for short) shares almost nothing other than a name with its larger Windows-based namesake, Visual Studio.

Visual Studio Code has built-in support for multiple languages and an extension model with a rich ecosystem of support for others. VS Code is updated monthly, and you can keep up to date at the Microsoft Python blog. Microsoft even makes the VS Code GitHub repo available for anyone to clone and contribute. (Cue the PR flood.)

The VS Code UI is well documented, so I won’t rehash it here:

Extensions for Python Development

As stated above, VS Code supports development in multiple programming languages through a well-documented extension model. The Python extension enables Python development in Visual Studio Code, with the following features:

• Support for Python 3.4 and higher, as well as Python 2.7
• Code completion with IntelliSense
• Automatic use of conda and virtual environments
• Code editing in Jupyter environments and Jupyter Notebooks

Visual Studio Code extensions cover more than just programming language capabilities:

• Keymaps allow users already familiar with Atom, Sublime Text, Emacs, Vim, PyCharm, or other environments to feel at home.

• Themes customize the UI whether you like coding in the light, dark, or something more colorful.

• Language packs provide a localized experience.

Here are some other extensions and settings I find useful:

• GitLens provides tons of useful Git features directly in your editing window, including blame annotations and repository exploration features.

• Auto save is easily turned on by selecting File, Auto Save from the menu. The default delay time is 1000 milliseconds, which is also configurable.

• Settings Sync allows you to synchronize your VS Code settings across different installations using GitHub. If you work on different machines, this helps keep your environment consistent across them.

• Docker lets you quickly and easily work with Docker, helping author Dockerfile and docker-compose.yml, package and deploy your projects, and even generate the proper Docker files for your project.

Of course, you may discover other useful extensions as you use VS Code. Please share your discoveries and settings in the comments!

Discovering and installing new extensions and themes is accessible by clicking on the Extensions icon on the Activity Bar. You can search for extensions using keywords, sort the results numerous ways, and install extensions quickly and easily. For this article, install the Python extension by typing python in the Extensions item on the Activity Bar, and clicking Install:

You can find and install any of the extensions mentioned above in the same manner.

Visual Studio Code Configuration Files

One important thing to mention is that Visual Studio Code is highly configurable through user and workspace settings.

User settings are global across all Visual Studio Code instances, while workspace settings are local to the specific folder or project workspace. Workspace settings give VS Code tons of flexibility, and I call out workspace settings throughout this article. Workspace settings are stored as .json files in a folder local to the project workspace called .vscode.

Start a New Python Program

Let’s start our exploration of Python development in Visual Studio Code with a new Python program. In VS Code, type Ctrl+N to open a new File. (You can also select File, New from the menu.)

Note: The Visual Studio Code UI provides the Command Palette, from which you can search and execute any command without leaving the keyboard. Open the Command Palette using Ctrl+Shift+P, type File: New File, and hit Enter to open a new file.

No matter how you get there, you should see a VS Code window that looks similar to the following:

Once a new file is opened, you can being entering code.

Entering Python Code

For our test code, let’s quickly code up the Sieve of Eratosthenes (which finds all primes less than a given number). Begin typing the following code in the new tab you just opened:

You should see something similar to this:

Wait, what’s going on? Why isn’t Visual Studio Code doing any keyword highlighting, any auto-formatting, or anything really helpful? What gives?

The answer is that, right now, VS Code doesn’t know what kind of file it’s dealing with. The buffer is called Untitled-1, and if you look in the lower right corner of the window, you’ll see the words Plain Text.

To activate the Python extension, save the file (by selecting File, Save from the menu, File:Save File from the Command Palette, or just using Ctrl+S) as sieve.py. VS Code will see the .py extension and correctly interpret the file as Python code. Now your window should look like this:

That’s much better! VS Code automatically reformats the file as Python, which you can verify by inspecting the language mode in the lower left corner.

If you have multiple Python installations (like Python 2.7, Python 3.x, or Anaconda), you can change which Python interpreter VS Code uses by clicking the language mode indicator, or selecting Python: Select Interpreter from the Command Palette. VS Code supports formatting using pep8 by default, but you can select black or yapf if you wish.

Let’s add the rest of the Sieve code now. To see IntelliSense at work, type this code directly rather than cut and paste, and you should see something like this:

Here’s the full code for a basic Sieve of Eratosthenes:

As you type this code, VS Code automatically indents the lines under for and if statements for you properly, adds closing parentheses, and makes suggestions for you. That’s the power of IntelliSense working for you.

Running Python Code

Now that the code is complete, you can run it. There is no need to leave the editor to do this: Visual Studio Code can run this program directly in the editor. Save the file (using Ctrl+S), then right-click in the editor window and select Run Python File in Terminal:

You should see the Terminal pane appear at the bottom of the window, with your code output showing.

Python Linting Support

You may have seen a pop up appear while you were typing, stating that linting was not available. You can quickly install linting support from that pop up, which defaults to PyLint. VS Code also supports other linters. Here’s the complete list at the time of this writing:

• pylint
• flake8
• mypy
• pydocstyle
• pep8
• prospector
• pyllama
• bandit

The Python linting page has complete details on how to setup each linter.

Note: The choice of linter is a project workspace setting, and not a global user setting.

Editing an Existing Python Project

In the Sieve of Eratosthenes example, you created a single Python file. That’s great as an example, but many times, you’ll create larger projects and work on them over a longer period of time. A typical new project work flow might look like this:

• Create a folder to hold the project (which may include a new GitHub project)
• Change to the new folder
• Create the initial Python code using the command code filename.py

Using Visual Studio Code on a Python project (as opposed to a single Python file) opens up tons more functionality that lets VS Code truly shine. Let’s take a look at how it works with a larger project.

Late in the previous millennium, when I was a much younger programmer, I wrote a calculator program that parsed equations written in infix notation, using an adaptation of Edsger Dijkstra’s shunting yard algorithm.

To demonstrate the project-focused features of Visual Studio Code, I began recreating the shunting yard algorithm as an equation evaluation library in Python. To continue following along, feel free to clone the repo locally.

Once the folder is created locally, you can open the entire folder in VS Code quickly. My preferred method (as mentioned above) is modified as follows, since I already have the folder and basic files created:

VS Code understands, and will use, any virtualenv, pipenv, or conda environments it sees when opened this way. You don’t even need to start the virtual environment first! You can even open a folder from the UI, using File, Open Folder from the menu, Ctrl+K, Ctrl+O from the keyboard, or File:Open Folder from the Command Palette.

For my equation eval library project, here’s what I see:

When Visual Studio Code opens the folder, it also opens the files you last had opened. (This is configurable.) You can open, edit, run, and debug any file listed. The Explorer view in the Activity Bar on the left gives you a view of all the files in the folder and shows how many unsaved files exist in the current set of tabs.

Testing Support

VS Code can automatically recognize existing Python tests written in the unittest framework, or the pytest or Nose frameworks if those frameworks are installed in the current environment. I have a unit test written in unittest for the equation eval library, which you can use for this example.

To run your existing unit tests, from any Python file in the project, right-click and select Run Current Unit Test File. You’ll be prompted to specify the test framework, where in the project to search for tests, and the filename pattern your tests utilize.

Get Started Tutorial For Python In Visual Studio Code

All of these are saved as workspace settings in your local .vscode/settings.json file and can be modified there. For this equation project, you select unittest, the current folder, and the pattern *_test.py.

Once the test framework is set up and the tests have been discovered, you can run all your tests by clicking Run Tests on the Status Bar and selecting an option from the Command Palette:

You can even run individual tests by opening the test file in VS Code, clicking Run Tests on the Status Bar, and selecting the Run Unit Test Method… and the specific test to run. This makes it trivial to address individual test failures and re-run only failed tests, which is a huge time-saver! Test results are shown in the Output pane under Python Test Log.

Debugging Support

Even though VS Code is a code editor, debugging Python directly within VS Code is possible. VS Code offers many of the features you would expect from a good code debugger, including:

• Automatic variable tracking
• Watch expressions
• Breakpoints
• Call stack inspection

You can see them all as part of the Debug view on the Activity Bar:

The debugger can control Python apps running in the built-in terminal or an external terminal instance. It can attach to an already running Python instances, and can even debug Django and Flask apps.

Debugging code in a single Python file is as simple as starting the debugger using F5. You use F10 and F11 to step over and into functions respectively, and Shift+F5 to exit the debugger. Breakpoints are set using F9, or using the mouse by clicking in the left margin in the editor window.

Before you start debugging more complicated projects, including Django or Flask applications, you need to setup and then select a debug configuration. Setting up the debug configuration is relatively straightforward. From the Debug view, select the Configuration drop-down, then Add Configuration, and select Python:

Visual Studio Code will create a debug configuration file under the current folder called .vscode/launch.json, which allows you to setup specific Python configurations as well as settings for debugging specific apps, like Django and Flask.

You can even perform remote debugging, and debug Jinja and Django templates. Close the launch.json file in the editor and select the proper configuration for your application from the Configuration drop-down.

Git Integration

VS Code has built-in support for source control management, and ships with support for Git and GitHub right out of the box. You can install support for other SCM’s in VS Code, and use them side by side. Source control is accessible from the Source Control view:

If your project folder contains a .git folder, VS Code automatically turns on the full range of Git/GitHub functionality. Here are some of the many tasks you can perform:

• Commit files to Git
• Push changes to, and pull changes from, remote repos
• Check-out existing or create new branches and tags
• View and resolve merge conflicts

All of this functionality is available directly from the VS Code UI:

VS Code will also recognize changes made outside the editor and behave appropriately.

Committing your recent changes within VS Code is a fairly straightforward process. Modified files are shown in the Source Control view with an M marker, while new untracked files are marked with a U. Stage your changes by hovering over the file and then clicking the plus sign (+). Add a commit message at the top of the view, and then click the check mark to commit the changes:

You can push local commits to GitHub from within VS Code as well. Select Sync from the Source Control view menu, or click Synchronize Changes on the status bar next to the branch indicator.

Conclusion

Visual Studio Code is one of the coolest general purpose editors and a great candidate for Python development. In this article, you learned:

• How to install VS Code on any platform
• How to find and install extensions to enable Python-specific features
• How VS Code makes writing a simple Python application easier
• How to run and debug existing Python programs within VS Code
• How to work with Git and GitHub repositories from VS Code

Visual Studio Code has become my default editor for Python and other tasks, and I hope you give it a chance to become yours as well.

If you have questions or comments, please reach out in the comments below. There is also a lot more information at the Visual Studio Code website than we could cover here.

The author sends thanks to Dan Taylor from the Visual Studio Code team at Microsoft for his time and invaluable input in this article.

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Make without limit! Device Simulator Express, a Microsoft Garage project, allows you to code microcontrollers without the hardware on hand! You can program your Adafruit Circuit Playground Express (CPX), your BBC micro:bit or the Adafruit CLUE! Test and debug your code on the device simulator and see the sameresult when you plug in your actual microcontroller. Curious about the output of the device, the serialmonitor allows you to observe the device output.

Table of Contents

• Adafruit Circuit Playground Express (CPX) Simulator
• BBC micro:bit Simulator
• Adafruit CLUE Simulator
• How to use

Devices we support

Prerequisites

The following dependencies are required to install before launching Device Simulator Express.
You will be prompted to install the Python dependencies during the first use.

• Python 3.7+: Make sure you've added Python and pip to your PATH in your environment variables. (1)
• Python VS Code extension: This will be installed automatically from the marketplace when you install Device Simulator Express.

Adafruit Circuit Playground Express (CPX) Simulator

Features

• IntelliSense and syntax highlighting for CircuitPython code for the CPX library
• Template file generation
• Integrated Python Debugging for the Simulator
• Serial monitor (available on Windows and Mac only)
• Output panel for the simulator
• Deploy CircuitPython code to the physical device.
• Simulation of the CPX device, including:
  • Green LED
  • Red LED
  • Push Buttons A and B
  • Slider Switch
  • Speaker: Play .wav file
  • 10 NeoPixels
  • Light sensor
  • Motion sensors
  • Acceleration detection
  • Device shake detection
  • Temperature sensor
  • 7 Capacitive Touch sensors

The simulator supports most of the sensors on CPX except IR transmitter & Receiver, Sound Sensor (microphone), Speaker (Play Tone) and the 'tap' on Motion Sensor.The code related to these sensors can still run on the actual CPX board and be deployed using Device Simulator Express.
As we only support CPX library now, other libraries (i.e. simpleio) can’t run on the simulator. But they will work on the actual device!

Useful Links

• Tutorials and Example Code for Adafruit CPX:
• Format Adafruit CPX device:

Keyboard Shortcuts

In Device Simulator Express, you can use keyboard to interact with the device:

• Push Button: A for Button A, B for Button B, C for Buttons A & B
• Capacitive Touch Sensor: Shift + 1 ~ 7 for GPIO pins A1 - A7
• Slider Switch: Shift + S
• Refresh the simulator: Shift + R
• Run the simulator: Shift + F

BBC micro:bit Simulator

Features

• IntelliSense and syntax highlighting for MicroPython code for the micro:bit library
• Template file generation
• Integrated Python Debugging for the Simulator
• Deploy MicroPython code to the physical device
• Serial monitor (available on Windows and Mac only)
• Simulation of the micro:bit device, including:
  • 25 LEDs
  • Push Buttons A and B
  • Light sensor
  • Motion sensors
  • Acceleration detection including gesture detection
  • Temperature sensor

Useful Links

• Tutorials and Example Code for BBC micro:bit:

Keyboard Shortcuts

• Push Button: A for Button A, B for Button B, C for Buttons A & B
• Refresh the simulator: Shift + R
• Run the simulator: Shift + F

Adafruit CLUE Simulator

Features

• IntelliSense and syntax highlighting for CircuitPython code for the following drivers and libraries:
  • adafruit_clue
  • adafruit_slideshow
  • adafruit_display_shapes
  • adafruit_display_text
  • adafruit_bitmap_font
  • adafruit_fancyled
  • neopixel
  • displayio
• Template file generation
• Integrated Python Debugging for the Simulator
• Deploy CircuitPython code to the physical device
• Serial monitor (available on Windows and Mac only)
• Simulation of the CLUE device, including:
  • 240x240 color screen
  • Push Buttons A and B
  • Sensors for:
    • Temperature
    • Light
    • Color
    • Acceleration
    • Humidity
    • Pressure
    • Proximity
    • Gestures
    • Gyro
    • Magnetic Field

Useful Links

• Tutorials and Example Code for Adafruit CLUE:

Keyboard Shortcuts

• Push Button: A for Button A, B for Button B, C for Buttons A & B
• Refresh the simulator: Shift + R
• Run the simulator: Shift + F

How to use

To use Device Simulator Express, install the extension from the marketplace and reload VS Code.

To access many of the commands, you need to open the command palette. This can be done with Ctrl + Shift + P for Windows and Linux / Cmd + Shift + P for Mac. It can also be accessed from the toolbar by going to View -> Command Palette.

I. Take a look at the 'Device Simulator Express: Getting Started' Command.

1. Type in 'Device Simulator Express: Getting Started' in the command palette (Ctrl + Shift + P / Cmd + Shift + P to open the command palette).
2. Choose the the device you want to play with from the dropdown.
3. Read, copy and learn some of the things you can do with the simulator!

II. Start with the 'Device Simulator Express: New File' Command.

1. Type in 'Device Simulator Express: New File' in the command palette (Ctrl + Shift + P / Cmd + Shift + P to open the command palette).
2. Select the device you want to use.
3. Name and save your file somewhere, and we’re good to go!
4. Start with some examples: you can find examples files and tutorials inside the comments at the top of the file.

III. Start from an existing Python file.

1. Open the folder or your .py file in Visual Studio Code.
2. Run Device Simulator Express: Open Simulator from the command palette or icon in the editor toolbar.
3. Select the device you want to use.

IV. Run your code on the simulator.

1. Run Run Simulator from the command palette or use the Play button on the simulator webview.

V. Deploy your code to the physical device

Before deploying the Python code to your CPX device, you need to format your device by following these tutorials:

• For the CPX:

  • Download the firmware with the .uf2 file (link: https://learn.adafruit.com/adafruit-circuit-playground-express/circuitpython-quickstart).
  • Download the lastest versions of the cpx libraries (link: https://learn.adafruit.com/welcome-to-circuitpython/circuitpython-libraries).

• For the micro:bit:

  • Download the firmware with the .hex file (link: https://microbit.org/get-started/user-guide/firmware/).

• For the CLUE:

  • Download the latest versions of the cpx libraries and follow the instructions here (link:https://learn.adafruit.com/adafruit-clue/circuitpython).

1. Plug in your device (make sure it’s formatted properly already).
2. Run the command 'Device Simulator Express: Deploy to Device'.

VI. Use the Serial Monitor for your device (available on Windows and Mac only)

1. Plug in your device (make sure it’s formatted properly already).
2. Run the command 'Device Simulator Express: Open Serial Monitor'.
3. Select your baud rate for the serial port.
4. The print() statements in your code will show in the output console.

VII. Debug your project on the simulator

1. Add breakpoints in your code
2. Press F5 to enter the debugging mode, and you can start debugging line by line!

Commands

Device Simulator Express provides several commands in the Command Palette (F1 or Ctrl + Shift + P / Cmd + Shift + P for Mac OS) for working with *.py files:

• Device Simulator Express: Getting Started: Opens a page in VS Code that helps users get started with the extension. Here, users can browse through code that they can use to play with the simulators.
• Device Simulator Express: Run Simulator: Runs Python code on the simulator.
• Device Simulator Express: New File: Opens an unsaved .py file with template code, also opens the simulator for the selected device.
• Device Simulator Express: Open Simulator: Opens the simulator in the simulator window for the selected device
• Device Simulator Express: Deploy to Device: Copies the current file to the selected device.
• Device Simulator Express: Open Serial Monitor: Opens the serial monitor in the integrated output window.
• Device Simulator Express: Close Serial Monitor: Stops the serial monitor and releases the serial port.
• Device Simulator Express: Change Baud Rate: Changes the baud rate of the selected serial port. For Adafruit CPX, the default baud rate is 115200.
• Device Simulator Express: Select Serial Port: Changes the current serial port.

Contribute

Provide feedback

To add a review for our extension, please do so on the Visual Studio Marketplace

To report issues, provide feedback or requests, please use this link: Provide Feedback.
We would love to hear from you about your experience to keep improving our project.

Privacy and Telemetry Notice

Data Collection

Cached

The software may collect information about you and your use of the software and send it to Microsoft. Microsoft may use this information to provide services and improve our products and services. You may turn off the telemetry as described in the repository. There are also some features in the software that may enable you and Microsoft to collect data from users of your applications. If you use these features, you must comply with applicable law, including providing appropriate notices to users of your applications together with a copy of Microsoft's privacy statement. Our privacy statement is located at https://go.microsoft.com/fwlink/?LinkID=824704. You can learn more about data collection and use in the help documentation and our privacy statement. Your use of the software operates as your consent to these practices.

Disable Telemetry

The Microsoft Device Simulator Express Extension for Visual Studio Code collects usagedata and sends it to Microsoft to help improve our products andservices. Read ourprivacy statement tolearn more. This extension respects the telemetry.enableTelemetrysetting which you can learn more about athttps://code.visualstudio.com/docs/supporting/faq#_how-to-disable-telemetry-reporting.

To disable telemetry, follow these steps:

1. Open File (Open Code on macOS)
2. Select Preferences
3. Select Settings
4. Search for telemetry
5. Uncheck the Telemetry: Enable Telemetry setting

Third Party Notice

A ThirdPartyNotices.txt file is provided in the extension's source code listing the appropriate third-party notices.

Troubleshooting Tips

• The first time you install the extension, you'll need to execute the run command at least once in order to access auto-completion.
• While running a code file, if you get an error saying it can't find the file, make sure you've clicked on a valid Python code file before running it.
• To open the output panel again after closing it go to VS Code menu: View -> Output.
• If you try to deploy to the CPX while it's plugged in but you still get an error saying it cannot find the board, make sure your device is formatted correctly and that its name matches CIRCUITPY.
• If you can't get the Simulator communication working while debugging, try to open your Settings and check the port used under 'Device Simulator Express: Debugger Server Port'. You can either change it (usually ports above 5000 should work) or try to free it, then start debugging again.
• When you are using the serial monitor, if you get some unusual error messages, unplug the device and reload the VS Code windows.
• If you're using Ubuntu and having some problems with setting up the environment, try reviewing this article's 'Step 1' section on how to set up Python 3 on Ubuntu 16.04. Then, ensure that you've run sudo apt-get install -y python3-venv to allow for virtual environment creation.

License

Notes

Mac Os Visual Studio Code Python 3

1. Make sure that when you type python in a terminal, the command is recognized and you have the correct version. The easiest way to do it is to select the 'Add to PATH' option directly when you install Python. Otherwise you can search how to insert it manually.
2. You can choose to see the prompt or not by changing the extension configurations.