Ssh vault for visual studio code

Remote-SSH Kaggle using Visual Studio Code This repository provides a convenient way to remotely connect to Kaggle using Visual Studio Code, enabling you to maximize the benefits of Kaggle's utilities. With this setup, you can maintain a continuous 12-hour session without interruptions. Additionally, you can extend the GPU usage from the default 30 hours per week to 42 hours by following a simple procedure (closing the notebook session at the end of the 29th hour, SSH back in, and maintain it for an additional 12 hours :v). This setup allows for easier usage of the terminal and debugging capabilities compared to the notebook interface provided by Kaggle. Furthermore, you can utilize and manage .py files effortlessly. And there are many more exciting features for you to explore! Getting Started 1. Install Visual Studio Code and create account NgrokDownload and install Visual Studio Code: account Ngrok: Generate SSH-keyNote: Windows & Linux similar.2.1 Open Terminal / Command Prompt.2.2 Paste the text below:2.3 Push SSH public key to GitHub3. Environment settings3.1 Go to Kaggle notebook: Notebook Example3.2 Choose Copy & Edit:3.3 In the right-hand bar, choose 1 of these 2 GPUs. TPU is not supported:3.4 At persistence, select Files only to save files every time you Stop Session:3.5 Go to the GitHub repo to save the SSH public key that you uploaded in step 2.3 -> Select raw:3.6 And coppy the above link:3.7 For public_key_path, paste the link copied from step 3.6:3.8 Go to Ngrok -> Your Authtoken -> press copy:3.9 Run the notebook cells from top to cell as shown in the picture, paste the Ngrok token saved from step 3.8 where the arrow points:3.10 In this cell you have to run twice, press stop and run again:3.11 Then re-run again, output like the following image is ok:3.12 In the last cell, notice the red square, which is HostName: 0.tcp.ap.ngrok.io and Port: 17520. Make a note to use for step 4.6.4. Install SSH configuration on Visual Studio Code4.1 Press Ctrl Shift X, search SSH and install the following 2 extentions:4.2 Note: How to SSH in detail see here ( Press Ctrl Shift

P -> Remote-SSH: Connect to Host…4.4 Press Configure SSH Host…4.5 Select ~/.ssh/config, usually the first file.4.6 Add the following information to the config file:Host: SSH's name, whatever you wantHostName: Server's IP address (in step 3.12)Port: red number (in step 3.12)User: root (keep the same)IdentityFile: Path to private key (in step 2.2)s4.7 Press Ctrl S and Ctrl Shift P -> Remote-SSH: Connect to Host…4.8 Press Kaggle that you named Host: Kaggle4.9 Press continue (Note: If a list appears to select the operating system, please select linux):4.10 At the bottom left corner shows as shown in the picture that ssh was successful:5. Using5.1 Press Ctrl K O -> Enter the path /kaggle -> Press ok.5.2 Open terminal press Ctrl J -> enter conda init -> press kill as shown in the picture.5.3 Activate cuda: Run the following scripts in terminal to activate cuda (Ctrl J to open terminal):sudo apt install nvidia-utils-515 -y5.4 Check GPU nvidia-smi:5.6 After each time stopping a session and running a new session notebook on Kaggle, you only need to perform the following operations in order to continue using: 3.10 -> 3.11 -> 3.12 -> 4.3 -> 4.4 -> 4.5 -> 4.6 -> 4.7 -> 4.8 -> 4.9 -> 5.1 -> 5.2 -> 5.3 -> 5.4. Tips and Tricks Here are some tips and tricks to make the most out of your remote-SSH Kaggle setup:To maintain a continuous session, remember to close the notebook session and SSH back in before reaching the 30-hour GPU usage limit. By doing so, you can extend your GPU usage to a maximum of 42 hours per week.Use the terminal in Visual Studio Code for easier command-line interactions and workflows.Take advantage of the debugging capabilities in Visual Studio Code to streamline your Kaggle projects.Easily manage and work with .py files by organizing your code in a familiar file-based structure.On the right bar of the Data section you will see 2 sections Input and Output:With Input as the place to receive data from kaggle and you do not have the right to edit on visual studio code, the corresponding dir is /kaggle/input/... The maximum storage

If the Distributed Vault upgrade fails, review the logs to determine the error. Prerequisite verification and installation errors Microsoft Visual C++ Redistributable for Visual Studio installation failed Error The following message indicates that the installation of Microsoft Visual C++ Redistributable for Visual Studio 2015-2022 32-bit and 64-bit versions failed: This error may occur because of one of the following scenarios: Scenario 1: One or more installation services are not running on the Vault server. Scenario 2: Your machine may be running an unsupported version of Microsoft Visual C++ Redistributable for Visual Studio 2015-2022. Scenario 1 solution If one or more installation services are not running on the Vault server, perform the following steps: In the installation package, in the WSUS directory, run the OpeningServices.ps1 script. Reboot the Vault server and try reinstalling Microsoft Visual C++ Redistributable for Visual Studio 2015-2022 32-bit and 64-bit versions. Scenario 2 solution If your machine may be running an unsupported version of Microsoft Visual C++ Redistributable for Visual Studio 2015-2022, perform the following steps: In the installation package, in the WSUS directory, run the OpeningServices.ps1 script. Reboot the Vault server for the change to take effect. Stop all CyberArk services on the server. Uninstall the current version of Microsoft Visual C++ Redistributable for Visual Studio. Install the latest version of Microsoft Visual C++ Redistributable for Visual Studio 2015-2022 32-bit and 64- versions. Restart the Vault server before continuing with the upgrade. Re-harden the Vault by running the ClosingServices.ps1 script file in the WSUS folder of

After merging a pull request. See our August Milestone plan for more details.Remote Development (Preview)Work has continued on the Remote Development extensions, which allow you to use a container, remote machine, or the Windows Subsystem for Linux (WSL) as a full-featured development environment.To help get you started with the Remote Development extensions, there are three introductory tutorials:Dev Containers - Run Visual Studio Code in a Docker Container.Remote via SSH - Connect to remote and virtual machines with Visual Studio Code via SSH.Working in WSL - Run Visual Studio Code in Windows Subsystem for Linux.You can also read a recent blog post describing Tips and Tricks for Linux development with WSL and Visual Studio Code.Feature highlights in 1.38 include:VS Code Stable preview support for Alpine Linux Containers, Alpine WSL distributions, and ARMv7l / AArch32 SSH hosts.VS Code Insiders experimental support for ARMv8l / AArch64 SSH hosts.Improvements to Dev Containers including a new container explorer!You can learn about new extension features and bug fixes in the Remote Development release notes.VS Code icon repositoryWe've published a repository of all of the VS Code icons for use by extension authors. There are dark/light versions of each icon, and we also linked to our Figma design file.Webview.asWebviewUri and Webview.cspSourceThere are two new properties on webviews:Webview.asWebviewUri - Convert a URI for the local file system to one that can be used inside webviews.For desktop VS Code, this will convert file: URIs into vscode-resource: URIs.Webview.cspSource - The content security policy source for webview resources.For desktop VS Code, this would be the string vscode-resource:.const panel = vscode.window.createWebviewPanel( CatCodingPanel.viewType, 'Cat Coding', vscode.ViewColumn.One, { // Restrict the webview to only loading local content from our extension's `media` directory. localResourceRoots: [vscode.Uri.file(path.join(extensionPath, 'media'))] });const imagePath = vscode.Uri.file(path.join(extensionPath, 'media'));panel.html = ` ${ panel.webview.cspSource } https:;"> Cat Coding ${panel.webview.asWebviewUri(imagePath)}/cat.gif" width="300" />`;Warning when creating webview without a Content Security PolicyWhile developing an extension that uses the Webview API, we now log a warning when you create a webview that does not set a Content Security Policy.All webviews (even very simple ones) should set a content security policy. This helps limit the potential impact of content injections and is generally a good measure for defense in depth. We've documented how to add a content security policy to VS Code webviews in the Webview extension guide.Machine-specific overridable settingsYou can now define a machine specific setting that can be overridable at workspace and folder level using the scope machine-overridable."configuration": { "title": "My Extension Settings", "properties": { "myextension.libPath": { "type": [ "string", "null" ], "markdownDescription": "Specify the path to the library.", "default": null, "scope": "machine-overridable" } }}Multi-select in custom tree viewTrees contributed through createTreeView can now add the canSelectMany option to the TreeViewOptions. This enables multi-select in the contributed tree view and causes commands that are run on tree elements to receive all the selected tree elements as an array in the second command argument.markdown.api.renderThe new markdown.api.render command from VS Code's built-in Markdown extension takes a string of Markdown or a vscode.TextDocument and returns the rendered Markdown as HTML:import