git-hooks.nix
dvc
git-hooks.nix | dvc | |
---|---|---|
6 | 110 | |
456 | 13,246 | |
2.6% | 1.0% | |
9.2 | 9.6 | |
11 days ago | 5 days ago | |
Nix | Python | |
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.
git-hooks.nix
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Fast, Declarative, Reproduble and Composable Developer Environments Using Nix
> Good luck getting answers on those questions other than "read the source code" and then followed by "no, not that source code, this branch here".
I experienced a similar situation last week with git-hooks.nix[1], a pre-commit integration for Nix.
I wanted to run biome[2] checks on my repository during pre-push so I wrote a custom hook because git-hooks.nix has pre-defined integrations with prettier and rome, but not biome.
Or that's what I thought. I eventually found out that the rome hook is actually referred as "rome" everywhere but calls biome instead[3]. This wasn't documented anywhere, so I opened an issue[4] suggesting to rename the hook to "biome" and keep the former for backwards compatibility reasons.
As of today, this has been acknowledged by one of the maintainers, whose sole feedback has been to "thumb down" the issue.
TL;DR: It's not just the documentation, but also the code not doing what you would expect. It also seems there's no means to improve the situation other than just forking the project since there's also clearly some kind of communication problem.
[1] https://github.com/cachix/git-hooks.nix
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Any good alternative to husky in rust to enforce and write conventional commits and for pre-commit source code linting??
Anyone who already uses Nix and Flakes can use this integration. Anyone who doesn't use Nix can just ignore me, because I'm not here to try converting unconvinced folks.
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Plugin devs: type check your lua plugins with lua-language-server and EmmyLua (GitHub action)
I don't think it does. I might look into implementimg it though, because I use pre-commit-hooks.nix in my own projects' CI.
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Pre-commit: framework for managing/maintaining multi-language pre-commit hooks
> My least favourite bug is that it doesn't always play nicely with NixOS [1], and the maintainer locked me out of the issue for pointing it out.
Oof. Does this solve the problem https://github.com/cachix/pre-commit-hooks.nix (using Nix to manage dependencies)?
I was looking at pre-commit the other day, and wanted to incorporate it into the Nix setup of my projects.
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y|sndr - Hooking up with Git - A nix managed solution to git hook management
Was it not possible to use something like this? https://github.com/cachix/pre-commit-hooks.nix
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Statix — Lints and Suggestions for the Nix programming language
Maybe consider adding this to https://github.com/cachix/pre-commit-hooks.nix once you feel it's mature enough.
dvc
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My Favorite DevTools to Build AI/ML Applications!
Collaboration and version control are crucial in AI/ML development projects due to the iterative nature of model development and the need for reproducibility. GitHub is the leading platform for source code management, allowing teams to collaborate on code, track issues, and manage project milestones. DVC (Data Version Control) complements Git by handling large data files, data sets, and machine learning models that Git can't manage effectively, enabling version control for the data and model files used in AI projects.
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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).
https://dvc.org/
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.
What are some alternatives?
pip-audit - Audits Python environments, requirements files and dependency trees for known security vulnerabilities, and can automatically fix them
MLflow - Open source platform for the machine learning lifecycle
husky - Git hooks made easy 🐶 woof!
lakeFS - lakeFS - Data version control for your data lake | Git for data
rnix-lsp - WIP Language Server for Nix! [maintainer=@aaronjanse]
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]
pre-commit - A framework for managing and maintaining multi-language pre-commit hooks.
delta - An open-source storage framework that enables building a Lakehouse architecture with compute engines including Spark, PrestoDB, Flink, Trino, and Hive and APIs
setup-dvc - DVC GitHub action
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
nixpkgs - Nix Packages collection & NixOS
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.