You should then see the output of running the code with the debug configuration. It may take a few seconds for the initial run to begin. The red dot will not show up until after you have selected the area next to a line number.Īfter you have a breakpoint added (or any other type of debug configuration), select the Run and Debug button on the left. Next, you can add a breakpoint by clicking to the left of the line number: Then, select the Debug view on the Activity bar (as shown below): You can start debugging by opening the Julia file that you would like to debug. To learn more about these options, head to Julia in VS Code - Running Code. You can run a Julia file (via ⌃F5 (Windows, Linux Ctrl+F5), which will run whatever Julia file you have open and active), execute Julia commands via the REPL, or even execute a specific block of code from a file you have open.
There are several ways to run Julia code within VS Code.
INTELLISENSE NOT WORKING WITH VISUAL STUDIO CODE UNITY INSTALL
If you run into any issues installing the Julia VS Code extension, check out install an extension, which should help clarify any issues.
In the Extensions view, search for the term "julia" in the Marketplace search box, then select the Julia extension (julialang.language-julia) and select the Install button. Inside VS Code, go to the Extensions view by clicking View on the top menu bar and then selecting Extensions. Open the Julia extension on the VS Code Marketplace and press Install or manually install by doing the following steps:. For a more in-depth guide on how these features work and can be configured, see the Julia in VS Code documentation. This page summarizes the Julia features included in the Julia VS Code extension. Most of these features work out of the box, while some may require basic configuration to get the best experience. The Julia extension for Visual Studio Code includes built-in dynamic autocompletion, inline results, plot pane, integrated REPL, variable view, code navigation, and many other advanced language features. Julia is commonly used in areas such as data science, machine learning, scientific computing, but is still a general purpose language that can handle most programming use cases. The Julia programming language is a high level and dynamic language built for speed and simplicity. Configure IntelliSense for cross-compiling.
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