.NET Interactive takes the power of .NET and embeds it into your interactive experiences. Share code, explore data, write, and learn across your apps in ways you couldn't before.
- Notebooks: Jupyter, nteract, and Visual Studio Code
- Code bots
- Devices like Raspberry Pi
- Embeddable script engines
- REPLs
.NET Interactive IS .NET UNLEASHED
We recently introduced the .NET Interactive Notebooks extension for Visual Studio Code, which adds support for .NET Interactive using the new Visual Studio Code native notebook feature. We encourage you to try it out. If you'd like to contribute, you can start here.
Project Jupyter is a popular platform for creating interactive notebooks that can be used for data science, documentation, DevOps, and much more.
There are several ways to get started using .NET with Jupyter, including Jupyter Notebook, JupyterLab, and nteract.
- Try sample .NET notebooks online using Binder. This also allows you try out our daily builds, which include preview features of F# 5.
- Install .NET Interactive to create and run .NET notebooks on your machine.
- Share your own .NET notebooks with others online using Binder.
- Use .NET Interactive with nteract
- Use .NET Interactive on Raspberry Pi and pi-top
You can find additional documentation here.
Open the VS Code extension test script in VS Code - Insiders
vscode-insiders://ms-dotnettools.dotnet-interactive-vscode/openNotebook?url=https%3A%2F%2Fraw.githubusercontent.com%2Fdotnet%2Finteractive%2Fmain%2FNotebookTestScript.dib
We provide a number of packages that can be used to write custom extensions for .NET Interactive or to build your own interactive experiences.
You can contribute to .NET Interactive with issues and pull requests. Simply filing issues for problems you encounter is a great way to contribute. Contributing code improvements is greatly appreciated. You can read more about our contribution guidelines here.
Azure Synapse Analytics | Azure HDInsight (HDI) |
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Azure Synapse Analytics uses the .NET kernel to write and run quick ad-hoc queries in addition to developing complete, end-to-end big data scenarios, such as reading in data, transforming it, and visualizing it | You can launch Jupyter notebooks from your HDInsight cluster to run big data queries against the compute resources in that cluster. |