Visual Studio Code 2022 Online
Chrystal Dueno
GitLens+ users now can access the Visual File History view, which allows you to quickly see the evolution of a file, including when changes were made, how large, and by whom. You can access this view from the panel below the editor area or via the Command Palette.
Authors who have contributed changes to the file are shown on the y-axis on the left hand side, creating a lane of their commits over time along the x-axis. Commits are plotted as color-coded bubbles, distinguishing authors by color. The size of the bubble represents the relative magnitude of the change.
Furthermore, the additions and deletions of each commit are visualized as color-coded, stacked vertical bars. The height of these bars represents the number of affected lines, shown on the y-axis on the right hand side. Added lines are shown in green, and deleted lines are shown in red.
The ability to checkout multiple branches at the same time in a single repository makes it easier for people to develop on, or test multiple branches, minimizing the overhead of switching between branches. This GitLens feature makes creating and managing worktrees easier because they are visualized in the source control panel in VS Code.
GitLens+ Pro is perfect for users who need access to all GitLens+ features for private repositories and escalated professional support.
GitLens+ Enterprise offers all the benefits of GitLens+ Pro, but is designed for larger teams who need professional onboarding and training opportunities. Plus, more advanced features for large teams, like SSO support, are coming soon.
It can be hard to keep track of which commits are tied to particular issues, or which pull requests merged the code changes. Now, when comparing a range of commits using the Search & Compare feature of GitLens, you can see any GitHub issues and pull requests that were associated with those changes. For example: you can now easily see all the issues fixed in a release from a single view.
There are a lot of powerful features and ways you can configure GitLens. To guide new and existing users through the configuration process, we have added a new Get Started with GitLens walkthrough. The experience is designed to guide you every step of the way, from initial setup to using GitLens+ features like an expert in no time.
The walkthrough quickly covers setting up and customizing GitLens, and how to use the various features like the current line blame and Git authorship CodeLens. It also shows you how to leverage the Git Command Palette, use the visual interactive rebase, and more.
This is just the beginning of how GitLens will continue to be enhanced. Many additional GitLens+ features are coming soon, including a visual commit graph and richer integrations. Sign up now to get access to these incredible GitLens+ features and to stay connected with the team working to bring you even more functionality!
I have been using visual studio code for the last 3 - 4 years and even though I don't like how resource-intensive it is but when it comes to features and customization it never disappoints me. I'm really loving the setup I have now so I thought I should write about my current vs code setup.
I'm a full-stack web developer, I primarily work in Typescript. Our frontend is uses React, Apollo Client, and Next.js (when server rendering is needed). In Backend, we use Nodejs, Express, GraphQL, and Prisma and for deployments, serverless with Github CI/CD.
In this article, you learn how to launch Visual Studio Code remotely connected to an Azure Machine Learning compute instance. Use VS Code as your integrated development environment (IDE) with the power of Azure Machine Learning resources. Use VS Code in the browser with VS Code for the Web, or use the VS Code desktop application.
This feature is currently in public preview. This preview version is provided without a service-level agreement, and we don't recommend it for production workloads. Certain features might not be supported or might have constrained capabilities.
Use VS Code as your workspace's integrated development environment (IDE). This option provides you with a full-featured development environment for building your machine learning projects.
VS Code for the Web provides you with a full-featured development environment for building your machine learning projects, all from the browser and without required installations or dependencies. And by connecting your Azure Machine Learning compute instance, you get the rich and integrated development experience VS Code offers, enhanced by the power of Azure Machine Learning.
On the initial connection, you may be prompted to install the Azure Machine Learning Visual Studio Code extension if you don't already have it. For more information, see the Azure Machine Learning Visual Studio Code Extension setup guide.
In order to connect to your remote compute instance from Visual Studio Code, make sure that the account you're logged into in Azure Machine Learning studio is the same one you use in Visual Studio Code.
This option connects your current VS Code session to a remote compute instance. In order to connect to your compute instance from VS Code, you need to install the Azure Machine Learning Visual Studio Code extension. For more information, see the Azure Machine Learning Visual Studio Code Extension setup guide.
If you pick one of the click-out experiences, a new VS Code window is opened, and a connection attempt made to the remote compute instance. When attempting to make this connection, the following steps are taking place:
This option allows you to use a compute instance as a remote Jupyter Notebook server from Visual Studio Code (Desktop). This option connects only to the compute instance, not the rest of the workspace. You won't see your workspace files in VS Code when using this option.
Now that you've launched Visual Studio Code remotely connected to a compute instance, you can prep your data, edit and debug your code, and submit training jobs with the Azure Machine Learning extension.
The world of online IDEs and cloud-based tools is currently very vibrant and active. Three of the most prominent IDE projects of recent years are for sure VS Code, Eclipse Che and Eclipse Theia. VS Code itself is a desktop IDE only, but it uses Electron and is hence based on web technologies. However, Microsoft previously announced VS Code Online, recently renamed to VS Code Codespaces, which includes a browser-based IDE based on VS Code. So the better question is actually: how does VS Code Codespaces compare to Eclipse Che?
First, we will have to look at both projects in more detail to find comparable parts. Both, like most cloud-based development tools, conceptually consist of two pieces: An IDE and a workspace server. The IDE is the UI that the developers use for their development tasks including code editing, interacting with version control, triggering builds or debugging. The workspace server hosts the actual developer runtime including the source code, and all the tools for building, debugging, or analyzing the source code. These tools are triggered by the browser-based UI but run on a backend.
In this section, we compare the IDE options of VS Code Codespaces to Eclipse Che. We will have a look at the default IDEs and their extensibility. We then describe options to use other, potentially customized IDEs, and finally the available deployment options.
Any VS Code related offering obviously uses VS Code as an IDE. There are actually two versions, the classic VS Code for the desktop and VS Code Online. We will discuss the available deployment options later.
There is one difference between Che Theia plugins and VS Code. Che plugins do not only extend the IDE (Theia) but also consist of a sidecar that is added to the underlying workspace container. That is useful, if the plugin requires anything to be installed on the underlying container, e.g. a JVM. In VS Code you have to manually maintain these dependencies.
Besides VS Code extensions, Eclipse Theia provides a second, more powerful extension mechanism, called Theia extensions. More powerful means that Theia extensions are not restricted to a dedicated plugin API that has been built for external extenders (like in VS Code), but extensions can access any API within Theia. In fact, Theia itself consists of extensions, so whatever can be done by the Theia core extensions, can also be adapted or extended by your custom extension. This includes removing features, adding custom editors, changing the default behavior and even creating a completely white-labelled fully customized product. Please see this article for a detailed comparison between Theia plugins and extensions. Taking Theia extensions into account, the Che default IDE is actually much more flexible and adaptable compared to VS Code. However, Theia extensions do not provide extensibility at runtime, you have to configure and deploy a product containing all extensions you want to use, including existing ones and custom ones you developed yourself. That essentially means that you need to replace the default Che Theia version with your own custom version of Theia. Luckily, this is easily possible in Che, as discussed in the next section.
When using VS Code, VS Code Online or VS Code Codespaces, the IDE of your choice will be, no surprise, VS Code. While you can customize it using VS Code extensions, as discussed in the previous section, you cannot really use anything else than VS Code.
Last but definitely not least, you can add your own editor to this list by simply extending the Che editor registry. This allows you to add any editor of your choice. This option is especially interesting when being combined with the extensibility and adaptability of Eclipse Theia. You can deploy your custom and potentially white labeled Theia version to the Che editor registry and thereby have a cloud-based tool that is completely customized for your specific domain or use case.
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