Get the software. Tee-clc (can be installed with HomeBrew), which depends on; Java 6, 7, or 8 (see How to install Java 8 on Mac- as of this writing, Java 9 will not work.); Create a workspace using tee-clc ('tf') Tell tee-clc to remember your credentials (in OSX's Keychain) by adding this line to your.bashprofile.Then close and reopen your terminal or just paste the same command.
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Jupyter (formerly IPython Notebook) is an open-source project that lets you easily combine Markdown text and executable Python source code on one canvas called a notebook. Visual Studio Code supports working with Jupyter Notebooks natively, as well as through Python code files. This topic covers the native support available for Jupyter Notebooks and demonstrates how to:
- Create, open, and save Jupyter Notebooks
- Work with Jupyter code cells
- View, inspect, and filter variables using the Variable explorer and Data viewer
- Connect to a remote Jupyter server
- Debug a Jupyter notebook
The AWS Toolkit for Visual Studio is available via the Visual Studio Marketplace and supports Visual Studio 2017 and 2019. The AWS Toolkit for 2013 and 2015 is contained in the AWS SDK and Tools for.NET install package. At this time, the AWS Toolkit for Visual Studio does not support Visual Studio. Visual Studio 2017 for Mac version 7.8.1.4. Released February 22, 2019. We fixed an issue where Visual Studio for Mac becomes unresponsive when selecting two column view. Visual Studio 2017 for Mac version 7.8.2.1. Released February 28, 2019. We fixed an issue where Debugger features sometimes don't work as expected with Unity. Xamarin is a free and open source mobile app platform for building native and high-performance iOS, Android, tvOS, watchOS, macOS, and Windows apps in C# with.NET. This site uses cookies for analytics, personalized content and ads. # Node.js Tools for Visual Studio.ntvsanalysis.dat # Visual Studio 6 build log.plg # Visual Studio 6 workspace options file.opt # Visual Studio 6 auto-generated workspace file (contains which files were open etc.).vbw # Visual Studio LightSwitch build output. /.HTMLClient / GeneratedArtifacts. /.DesktopClient / GeneratedArtifacts.
Setting up your environment
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To work with Jupyter notebooks, you must activate an Anaconda environment in VS Code, or another Python environment in which you've installed the Jupyter package. To select an environment, use the Python: Select Interpreter command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).
Once the appropriate environment is activated, you can create and open a Jupyter Notebook, connect to a remote Jupyter server for running code cells, and export a Jupyter Notebook as a Python files.
Note: By default, the Visual Studio Code Python extension will open a Jupyter Notebook (.ipynb) in the Notebook Editor. If you want to disable this behavior you can turn it off in settings. (Python > Data Science: Use Notebook Editor).
Create or open a Jupyter Notebook
You can create a Jupyter Notebook by running the Python: Create Blank New Jupyter Notebook command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) or by creating a new .ipynb file in your workspace. When you select the file, the Notebook Editor is launched allowing you to edit and run code cells.
If you have an existing Jupyter Notebook, you can open it in the Notebook Editor by double clicking on the file and opening with Visual Studio Code, through the Visual Studio Code, or using the Command Palette Python: Open in Notebook Editor command.
Once you have a Notebook created, you can run a code cell using the green run icon next to the cell and the output will appear directly below the code cell.
Save your Jupyter Notebook
You can save your Jupyter Notebook using the keyboard combo Ctrl+S or through the save icon on the Notebook Editor toolbar.
Note: At present, you must use the methods discussed above to save your Notebook. The File>Save menu does not save your Notebook, just the toolbar icon or keyboard command.
Work with code cells in the Notebook Editor
The Notebook Editor makes it easy to create, edit, and run code cells within your Jupyter Notebook.
Create a code cell
By default, a blank Notebook will have an empty code cell for you to start with and an existing Notebook will place one at the bottom. Add your code to the empty code cell to get started.
Code cell modes
While working with code cells a cell can be in three states, unselected, command mode, and edit mode. The current state of a cell is indicated by a vertical bar to the left of a code cell. When no bar is visible, the cell is unselected.
An unselected cell isn't editable, but you can hover over it to reveal additional cell specific toolbar options. These additional toolbar options appear directly below and to the left of the cell. You'll also see when hovering over a cell that an empty vertical bar is present to the left.
When a cell is selected, it can be in two different modes. It can be in command mode or in edit mode. When the cell is in command mode, it can be operated on and accept keyboard commands. When the cell is in edit mode, the cell's contents (code or markdown) can be modified.
When a cell is in command mode, the vertical bar to the left of the cell will be solid to indicate it's selected.
When you're in edit mode, the vertical bar will have diagonal lines.
To move from edit mode to command mode, press the ESC key. To move from command mode to edit mode, press the Enter key. You can also use the mouse to change the mode by clicking into or out of the code/markdown region in the code cell.
Add additional code cells
Code cells can be added to a Notebook using the main toolbar, a code cell's vertical toolbar, the add code cell icon at the bottom of the Notebook, the add code cell icon at the top of the Notebook (visible with hover), and through keyboard commands.
Using the plus icon in the main toolbar will add a new cell directly below the currently selected cell. Using the add cell icons at the top and bottom of the Jupyter Notebook, will add a code cell at the top and bottom respectively. And using the add icon in the code cell's toolbar, will add a new code cell directly below it.
When a code cell is in command mode, the A key can be used to add a cell above and the B can be used to add a cell below the selected cell.
Select a code cell
The selected code cell can be changed using the mouse, the up/down arrow keys on the keyboard, and the J (down) and K (up) keys. To use the keyboard, the cell must be in command mode.
Run a single code cell
Once your code is added, you can run a cell using the green run arrow and the output will be displayed below the code cell.
You can also use key combos to run a selected code cell. Ctrl+Enter runs the currently selected cell, Shift+Enter runs the currently selected cell and inserts a new cell immediately below (focus moves to new cell), and Alt+Enter runs the currently selected cell and inserts a new cell immediately below (focus remains on current cell). These keyboard combos can be used in both command and edit modes.
Run multiple code cells
Running multiple code cells can be accomplished in a number of ways. You can use the double arrow in the toolbar of the Notebook Editor to run all cells within the Notebook or the hover toolbar arrows to run all cells above or below the current code cell.
Move a code cell
Moving code cells up or down within a Notebook can be accomplished using the vertical arrows beside each code cell. Hover over the code cell and then click the up arrow to move the cell up and the down arrow to move the cell down.
Delete a code cell
Deleting a code cell can be accomplished by hovering over a code cell and using the delete icon in the code cell toolbar or through the keyboard combo dd when the selected code cell is in command mode.
Switch between code and Markdown
The Notebook Editor allows you to easily change code cells between Markdown and code. By default a code cell is set for code, but just click the Markdown icon (or the code icon, if Markdown was previously set) in the code cell's toolbar to change it.
Once Markdown is set, you can enter Markdown formatted content to the code cell. Once you select another cell or toggle out of the content selection, the Markdown content is rendered in the Notebook Editor.
You can also use the keyboard to change the cell type. When a cell is selected and in command mode, the M key switches the cell type to Markdown and the Y key switches the cell type to code.
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Clear output or restart/interrupt the kernel
If you'd like to clear the code cell output or restart/interrupt the kernel, you can accomplish that using the main Notebook Editor toolbar.
Enable/Disable line numbers
You can enable or disable line numbering within a code cell using the L key.
IntelliSense support in the Jupyter Notebook Editor
The Python Jupyter Notebook Editor window has full IntelliSense – code completions, member lists, quick info for methods, and parameter hints. You can be just as productive typing in the Notebook Editor window as you are in the code editor.
Variable explorer and data viewer
Within the Python Notebook Editor, it's possible to view, inspect, and filter the variables within your current Jupyter session. By clicking the Variables icon in the top toolbar after running code and cells, you'll see a list of the current variables, which will automatically update as variables are used in code.
For additional information about your variables, you can also double-click on a row or use the Show variable in data viewer button next to the variable to see a more detailed view of a variable in the Data Viewer. Once open, you can filter the values by searching over the rows.
Note: Variable explorer is enabled by default, but can be turned off in settings (Python > Data Science: Show Jupyter Variable Explorer).
Plot viewer
The Plot Viewer gives you the ability to work more deeply with your plots. In the viewer you can pan, zoom, and navigate plots in the current session. You can also export plots to PDF, SVG, and PNG formats.
Within the Notebook Editor window, double-click any plot to open it in the viewer, or select the plot viewer button on the upper left corner of the plot (visible on hover).
Note: There is support for rendering plots created with matplotlib and Altair.
Debug a Jupyter Notebook
Currently, to debug a Jupyter Notebook you will need to first export it as a Python file. Once exported as a Python file, the Visual Studio Code debugger lets you step through your code, set breakpoints, examine state, and analyze problems. Using the debugger is a helpful way to find and correct issues in notebook code. To debug your Python file:
- In VS Code, if you haven't already, activate a Python environment in which Jupyter is installed.
- From your Jupyter Notebook (.ipynb) select the convert button in the main toolbar.Once exported, you'll have a .py file with your code that you can use for debugging.
- After saving the .py file, to start the debugger, use one of the following options:
- For the whole Notebook, open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) and run the Python: Debug Current File in Python Interactive Window command.
- For an individual cell, use the Debug Cell adornment that appears above the cell. The debugger specifically starts on the code in that cell. By default, Debug Cell just steps into user code. If you want to step into non-user code, you need to uncheck Data Science: Debug Just My Code in the Python extension settings (⌘, (Windows, Linux Ctrl+,)).
- To familiarize yourself with the general debugging features of VS Code, such as inspecting variables, setting breakpoints, and other activities, review VS Code debugging.
- As you find issues, stop the debugger, correct your code, save the file, and start the debugger again.
- When you're satisfied that all your code is correct, use the Python Interactive window to export the Python file as a Jupyter Notebook (.ipynb).
Connect to a remote Jupyter server
You can offload intensive computation in a Jupyter Notebook to other computers by connecting to a remote Jupyter server. Once connected, code cells run on the remote server rather than the local computer.
To connect to a remote Jupyter server:
- Run the Python: Specify local or remote Jupyter server for connections command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).
- When prompted to Pick how to connect to Jupyter, select Existing: Specify the URI of an existing server.
- When prompted to Enter the URI of a Jupyter server, provide the server's URI (hostname) with the authentication token included with a
?token=
URL parameter. (If you start the server in the VS Code terminal with an authentication token enabled, the URL with the token typically appears in the terminal output from where you can copy it.) Alternatively, you can specify a username and password after providing the URI.
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Visual Studio 2017 for Mac contains many new and exciting features and IDE productivity enhancements tosupport cross-platform desktop app development, cross-platform mobile development, Azure development, web and cloud development,and more. To try out Visual Studio 2017 for Mac, see the Downloads page.For more information about everything that's new in this release, see theVisual Studio 2017 for Mac release notes.
System Requirements
For information on the system requirements for installing and running the Visual Studio 2017 for Mac family of products, see the Visual Studio 2017 for Mac System Requirement page.
Platform Targeting
Visual Studio for Mac provides cutting-edge tools and technologies to create apps that take advantage of thelatest platform capabilities, for macOS, Android, iOS, tvOS, and watchOS, as well as web sites, services, and games.
Feature Summary
- Mobile app development
- Share code between Android and iOS with Xamarin
- Native iOS and Android UI designers
- Shared UI with Xamarin.Forms
- Protect Android code with Embedded Assemblies
- Visualize and debug apps with Xamarin Inspector *
- Profile your apps with Xamarin Profiler *
- Cross-platform 'desktop' development
- macOS app development
- .NET Core development
- Web application development
- ASP.NET Core development
- HTML, CSS, JSON web editor tooling
- Cloud development
- ASP.NET Core WebAPI development
- Publish ASP.NET Core projects to Azure directly from the IDE
- Game development
- Unity game development
* Requires Visual Studio for Mac Enterprise
Visual Studio for Mac does not support Windows client projects like Windows Forms, WPF, or UWP.
Visual Studio 2017 for Mac Support for Android Development
Visual Studio 2017 for Mac enables you to build native Android apps using Xamarin and C#. You can use Unity to build Android games.
You can use the Android SDK Manager to easily obtain the Android SDK and Android API levels.You can download additional API levels separately using the Android SDK Manager.
For more information, see Android development with Visual Studio for Mac.
Visual Studio 2017 for Mac Support for iOS Development
Visual Studio 2017 for Mac enables you to build native iOS apps using Xamarin and C#. You can use Unity to build iOS games.
For more information, see iOS development with Visual Studio for Mac.
Visual Studio 2017 for Mac Support for macOS/OS X Development
Visual Studio 2017 for Mac enables you to build console applications and Cocoa (desktop) applications for macOS.
For more information, see macOS development with Visual Studio for Mac.
Visual Studio 2017 for Mac Support for ASP.NET Core Development
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ASP.NET Core is an open-source and cross-platform framework for building modern cloud based internet connected applications, such as web apps and services, IoT apps, and mobile backends.
ASP.NET Core apps can be developed and debugged using Visual Studio 2017 for Mac, including the server-side code as well as client side HTML, CSS, and Javascript. They can be hosted on Windows, macOS, or Linux.
For more information, see .NET Core and to get started follow this hands-on lab.
Visual Studio 2017 for Mac Support for Unity Game Development
Visual Studio for Mac Tools for Unity is a free Visual Studio extension that turns Visual Studio for Mac into a powerful tool for developing cross-platform games and apps with the Unity platform.
For more information, see Visual Studio Tools for Unity and to get started follow this hands-on lab.
Other Platforms and Technologies
Visual Studio 2017 for Mac also supports the following platforms and technologies. For more information, seehttps://visualstudio.microsoft.com/vs/.
Microsoft Visual Studio
- .NET Core 1.1. For more information see https://dot.net/core
- F#
- Web Development HTML5/CSS3 and JavaScript
Feedback and Suggestions
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Use the Provide a Suggestion link on the welcome page in Visual Studio for Mac, or visit Visual Studio for Mac's UserVoice page directly. From here you can add new requests or vote on existing ideas. To report a problem, follow these instructions.