dvc
VFSForGit
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dvc | VFSForGit | |
---|---|---|
108 | 24 | |
13,093 | 5,935 | |
1.3% | 0.5% | |
9.7 | 4.7 | |
2 days ago | about 1 month ago | |
Python | C# | |
Apache License 2.0 | MIT License |
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.
dvc
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Why bad scientific code beats code following "best practices"
What you’re describing sounds like DVC (at a higher-ish—80%-solution level).
See pachyderm too.
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First 15 Open Source Advent projects
10. DVC by Iterative | Github | tutorial
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Platforms such as MLflow monitor the development stages of machine learning models. In parallel, Data Version Control (DVC) brings version control system-like functions to the realm of data sets and models.
- ML Experiments Management with Git
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Git Version Controlled Datasets in S3
I was using DVC (https://dvc.org/) for some time to help solve this but it was getting hard to manage the storage connections and I would run into cache issues a lot, but this solves it using git-lfs itself.
- Ask HN: How do your ML teams version datasets and models?
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Exploring MLOps Tools and Frameworks: Enhancing Machine Learning Operations
DVC (Data Version Control):
- Evaluate and Track Your LLM Experiments: Introducing TruLens for LLMs
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[D] Is there a tool to keep track of my ML experiments?
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
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Where do I best store my test data when using github for code?
I use DVC, which works decently well and can be hooked into Git.
VFSForGit
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Debian Git Monorepo
It's not only Windows that uses Git at Microsoft, but Sharepoint and Office (which includes the on-prem version of SharePoint). In terms of repo size Windows and Office are similar. I was part of the team that migrated Sharepoint from a Perforce clone to Git and helped build the tooling to allow Office to move as well. VFS for Git [1] and Scalar [2] are really good pieces of software.
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Serving a Website from a Git Repo Without Cloning It
Congratulations! That means you basically figured out how the clone procedure works and found a way to do so just in a partial way (also in an unsafe way). But it is a cool idea, nonetheless.
Also check out the Scalar [1] project and its predecessor, GVFS [2], both from Microsoft to manage their monorepo via a VFS layer.
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We Put Half a Million Files in One Git Repository, Here's What We Learned (2022)
VFS for Git is still Open Source: https://github.com/microsoft/VFSForGit
Microsoft's blog posts have indicated a move to use something as close to off-the-shelf git as possible, though. They say they've stopped using VFS much and are instead more often relying on sparse checkouts. They've upstreamed a lot of patches into git itself, and maintain their own git fork but the fork distance is generally shrinking as those patches upstream.
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Why SQLite Does Not Use Git
https://github.com/microsoft/VFSForGit
better than it used to, with the caveat that git in particular is not and has never claimed to be good at versioning blobs.
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🐂 🌾 Oxen.ai - Blazing Fast Unstructured Data Version Control, built in Rust
Oh dear you're not going to like this.
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He is very conservative...
It’s virtualised file system: https://github.com/microsoft/VFSForGit, only downloads what you actually use. Same thing in every large company, but different implementations.
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FYI: LLVM-project repo has exceeded GitHub upload size limit
This is where something like VFSForGit[0] helps out. Instead of cloning the entire repo, it creates a virtual file system and fetches objects on demand. MSFT uses it internally for the Windows source tree (which now exceeds 300GB).
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Created a Small Program To Display Upcoming Assignments On My Desktop
There's also a performance consideration. Not excluding /bin/ or /obj/ folders means dependencies are being tracked as well, and sometimes dependencies themselves are bigger than the program's source code itself. This is commonly the case with node projects, as the node_modules folder can balloon to hundreds of megabytes. They should never be tracked in git due to the nature of how git's internal database works. For e.g. if you delete a dependency because it's no longer needed, you can never fully reclaim that disk space (at least for the master branch) as git will need to keep the binary data stored in its internal tracking database because a previous commit in the master branch has captured the data. As you make more branches, git needs to store the data required to reconstruct your repo to a different state when you switch branches. When a branch has changes measured in the kilobytes, check out is very manageable, but when the differences balloon to many MBs due to the presence of heavy binary files, then checkout between different branches/commits can get very slow. Though, this happens anyway when source code data eventually reaches a certain threshold, beyond the hundreds of megabytes, it's made unnecessarily worse by including any binary files. It's one of the reasons Microsoft created VFS for git: https://github.com/microsoft/VFSForGit.
- Meta releases Sapling, a new way of using source control
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Software for managing config files
You mean like VFSforGit? Or the successor for that called Scalar? This has been a solved problem. Microsoft moved their entire Windows codebase to git. There have been a ton of huge improvements to performance as a result of that. And the above two plugins are easily better ways to deal with what you're referring to without resulting to dead tech.
What are some alternatives?
MLflow - Open source platform for the machine learning lifecycle
scalar - Scalar: A set of tools and extensions for Git to allow very large monorepos to run on Git without a virtualization layer
lakeFS - lakeFS - Data version control for your data lake | Git for data
EdenSCM - A Scalable, User-Friendly Source Control System. [Moved to: https://github.com/facebook/sapling]
Activeloop Hub - Data Lake for Deep Learning. Build, manage, query, version, & visualize datasets. Stream data real-time to PyTorch/TensorFlow. https://activeloop.ai [Moved to: https://github.com/activeloopai/deeplake]
juicefs - JuiceFS is a distributed POSIX file system built on top of Redis and S3.
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
git - A fork of Git containing Microsoft-specific patches.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
mvfs - ClearCase file system
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
sturdy - 🐥 Sturdy is an open-source, real-time, version control platform for startups (https://getsturdy.com)