vscode-dvc
features
| vscode-dvc | features | |
|---|---|---|
| 6 | 2 | |
| 177 | 6 | |
| 0.6% | - | |
| 9.9 | 1.6 | |
| 1 day ago | 3 days ago | |
| TypeScript | Shell | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
vscode-dvc
- Machine learning experiment tracking and data versioning with for VS Code
- DVC Extension for Visual Studio Code
- ML experiment tracking with DVC extension for VS Code
- ML experiment tracking and data versioning in VS Code
- vscode-dvc: Machine learning experiment tracking and data versioning with DVC extension for VS Code
- Reproducible ML experiments extension for VS Code
features
-
Microsoft Docker Development Container Templates
* "Features" (https://containers.dev/implementors/features/ ) which allow you to quickly add functionality to your dev containers. For example, when I want to add the terraform CLI, I add the corresponding feature to the devcontainer.json.
-
Development Containers
The way I see it - it's a really nice way to make modules out of your Docker files (e.g. we need to install a tool and we need to run apt-get + some config, etc). And a simpler, JSON syntax to apply those modules on top of a base image.
I love the experience so far, we've done a few features (modules) - e.g. this one to install `nvtop` to see GPU utilization https://github.com/iterative/features/blob/main/src/nvtop/in...
The whole CUDA + nvtop + (some other tools) for an example project to be run on a remote machine via VS Code becomes like this:
https://github.com/shcheklein/hackathon/blob/main/.devcontai...
And that's enough to run ML training on GH Codespaces with GPU support. Super cool experience.
What are some alternatives?
Mage - 🧙 The modern replacement for Airflow. Mage is an open-source data pipeline tool for transforming and integrating data. https://github.com/mage-ai/mage-ai
templates - Repository for Dev Container Templates that are managed by Dev Container spec maintainers. See https://github.com/devcontainers/template-starter to create your own!
vscode-go - Go extension for Visual Studio Code
spec - Development Containers: Use a container as a full-featured development environment.
vscode-git-graph - View a Git Graph of your repository in Visual Studio Code, and easily perform Git actions from the graph.
client - DagsHub client libraries
marimo - A reactive notebook for Python — run reproducible experiments, execute as a script, deploy as an app, and version with git.
flask-surveys-container-app - An example Flask app for public surveys (no user auth) designed to be run inside Docker and deployed to Azure Container Apps with the Azure Developer CLI.
vscode-intelephense - PHP intellisense for Visual Studio Code
gitpod - The developer platform for on-demand cloud development environments to create software faster and more securely.
layerx-community - LayerX-AI is a comprehensive platform to annotate and manage your machine learning data.
docked - Running Rails from Docker for easy start to development