Kedro
Docusaurus
Kedro | Docusaurus | |
---|---|---|
29 | 282 | |
9,362 | 52,968 | |
0.7% | 1.3% | |
9.7 | 9.5 | |
10 days ago | 5 days ago | |
Python | TypeScript | |
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.
Kedro
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Nextflow: Data-Driven Computational Pipelines
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
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A Polars exploration into Kedro
# pyproject.toml [project] dependencies = [ "kedro @ git+https://github.com/kedro-org/kedro@3ea7231", "kedro-datasets[pandas.CSVDataSet,polars.CSVDataSet] @ git+https://github.com/kedro-org/kedro-plugins@3b42fae#subdirectory=kedro-datasets", ]
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What are some open-source ML pipeline managers that are easy to use?
So there's 2 sides to pipeline management: the actual definition of the pipelines (in code) and how/when/where you run them. Some tools like prefect or airflow do both of them at once, but for the actual pipeline definition I'm a fan of https://kedro.org. You can then use most available orchestrators to run those pipelines on whatever schedule and architecture you want.
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How do data scientists combine Kedro and Databricks?
We have set up a milestone on GitHub so you can check in on our progress and contribute if you want to. To suggest features to us, report bugs, or just see what we're working on right now, visit the Kedro projects on GitHub.
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How do you organize yourself during projects?
you could use a project framework like kedro to force you to be more disciplined about how you structure your projects. I'd also recommend checking out this book: Edna Ridge - Guerrilla Analytics: A Practical Approach to Working with Data
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Futuristic documentation systems in Python, part 1: aiming for more
Recently I started a position as Developer Advocate for Kedro, an opinionated data science framework, and one of the things we're doing is exploring what are the best open source tools we can use to create our documentation.
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Python projects with best practices on Github?
You can also check out Kedro, it’s like the Flask for data science projects and helps apply clean code principles to data science code.
- Data Science/ Analyst Zertifikate für den Job Markt?
- What are examples of well-organized data science project that I can see on Github?
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Dabbling with Dagster vs. Airflow
An often overlooked framework used by NASA among others is Kedro https://github.com/kedro-org/kedro. Kedro is probably the simplest set of abstractions for building pipelines but it doesn't attempt to kill Airflow. It even has an Airflow plugin that allows it to be used as a DSL for building Airflow pipelines or plug into whichever production orchestration system is needed.
Docusaurus
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Alternatives to Docusaurus for product documentation
Docusaurus is a popular open-source documentation tool primarily designed for product documentation and other technical documentation needs. It was first released in 2017 by Facebook Open Source (now Meta Open Source). Just recently, Docsaurus version 3.0 was released.
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Docusaurus doesn't recognize brackets {} on the markdown files
// @ts-check // `@type` JSDoc annotations allow editor autocompletion and type checking // (when paired with `@ts-check`). // There are various equivalent ways to declare your Docusaurus config. // See: https://docusaurus.io/docs/api/docusaurus-config import { themes as prismThemes } from "prism-react-renderer"; /** @type {import('@docusaurus/types').Config} */ const config = { title: "My Site", tagline: "Dinosaurs are cool", url: "https://your-docusaurus-test-site.com", baseUrl: "/", onBrokenLinks: "throw", onBrokenMarkdownLinks: "warn", favicon: "img/favicon.ico", organizationName: "facebook", // Usually your GitHub org/user name. projectName: "docusaurus", // Usually your repo name. presets: [ [ "docusaurus-preset-openapi", /** @type {import('docusaurus-preset-openapi').Options} */ ({ docs: { sidebarPath: require.resolve("./sidebars.js"), // Please change this to your repo. editUrl: "https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/", }, blog: { showReadingTime: true, // Please change this to your repo. editUrl: "https://github.com/facebook/docusaurus/tree/main/packages/create-docusaurus/templates/shared/", }, theme: { customCss: require.resolve("./src/css/custom.css"), }, }), ], ], themeConfig: /** @type {import('docusaurus-preset-openapi').ThemeConfig} */ ({ navbar: { title: "My Site", logo: { alt: "My Site Logo", src: "img/logo.svg", }, items: [ { type: "doc", docId: "intro", position: "left", label: "Tutorial", }, { to: "/api", label: "API", position: "left" }, { to: "/blog", label: "Blog", position: "left" }, { href: "https://github.com/facebook/docusaurus", label: "GitHub", position: "right", }, ], }, footer: { style: "dark", links: [ { title: "Docs", items: [ { label: "Tutorial", to: "/docs/intro", }, ], }, { title: "Community", items: [ { label: "Stack Overflow", href: "https://stackoverflow.com/questions/tagged/docusaurus", }, { label: "Discord", href: "https://discordapp.com/invite/docusaurus", }, { label: "Twitter", href: "https://twitter.com/docusaurus", }, ], }, { title: "More", items: [ { label: "Blog", to: "/blog", }, { label: "GitHub", href: "https://github.com/facebook/docusaurus", }, ], }, ], copyright: `Copyright © ${new Date().getFullYear()} My Project, Inc. Built with Docusaurus.`, }, prism: { theme: prismThemes.github, darkTheme: prismThemes.dracula, }, }), }; export default config;
- Looking for open source documentation generator
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Show HN: A Python-based static site generator using Jinja templates
Facebook's React/Markdown SSG docusaurus does those things: https://docusaurus.io/
Though you may have to use a plugin for responsive images: https://docusaurus.io/docs/api/plugins/@docusaurus/plugin-id...
- Craft Your GitHub Profile Page in 60 Seconds with Zero Code, Absolutely Free
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Top 5 Open-Source Documentation Development Platforms of 2024
Docusaurus is an open-source static site generator built on React and has emerged as a popular tool for developing and maintaining product documentation. Its ease of use, extensive features, and robust community support make it a compelling choice for many organizations.
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No CMS? Writing Our Blog in React
Wondering why Docusaurus (https://docusaurus.io) did not match their needs. Works perfectly fine as a blogging engine for our tech blog.
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Best Software Documentation Tools
This is developed by Meta. You can create really nice-looking documentation websites super fast.
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Can Git or any other VCS be used as a database instead of SQL/NoSQL ones? Have you ever seen such a thing?
Docusaurus, a documentation tool by Facebook, hosts a showcase of other websites that use Docusaurus on their Homepage. The list of websites of this showcase is a typescript files that is maintained by Docusaurus devs, and that you can add your website to through PR: https://github.com/facebook/docusaurus/blob/main/website/src/data/users.tsx
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Community project: PreventRansomware.io
Fix "Edit this page" links at the bottom of each doc (Problem with the Docusaurus build I guess)
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
nextra - Simple, powerful and flexible site generation framework with everything you love from Next.js.
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
storybook - Storybook is a frontend workshop for building UI components and pages in isolation. Made for UI development, testing, and documentation.
Dask - Parallel computing with task scheduling
oauth2-proxy - A reverse proxy that provides authentication with Google, Azure, OpenID Connect and many more identity providers.
cookiecutter-pytorch - A Cookiecutter template for PyTorch Deep Learning projects.
JSDoc - An API documentation generator for JavaScript.
ploomber - The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
VuePress - 📝 Minimalistic Vue-powered static site generator
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
MkDocs - Project documentation with Markdown.