import{s as q,n as z,o as F}from"../chunks/scheduler.d6170356.js";import{S as j,i as B,g as f,s as h,r as T,A as N,h as m,f as a,c as u,j as A,u as C,x as w,k as O,y as R,a as s,v as E,d as M,t as S,w as I}from"../chunks/index.fcd4cc08.js";import{H as W,E as G}from"../chunks/EditOnGithub.da2b595c.js";function Q(D){let r,b,p,g,d,y,i,k=`The Datasets Hub has support for several libraries in the Open Source ecosystem.
Thanks to the <a href="/docs/huggingface_hub">huggingface_hub Python library</a>, it’s easy to enable sharing your datasets on the Hub.
We’re happy to welcome to the Hub a set of Open Source libraries that are pushing Machine Learning forward.`,_,n,x="The table below summarizes the supported libraries and their level of integration.",P,o,H='<thead><tr><th>Library</th> <th>Description</th> <th>Download from Hub</th> <th>Push to Hub</th></tr></thead> <tbody><tr><td><a href="./datasets-argilla">Argilla</a></td> <td>Collaboration tool for AI engineers and domain experts that value high quality data.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-dask">Dask</a></td> <td>Parallel and distributed computing library that scales the existing Python and PyData ecosystem.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-usage">Datasets</a></td> <td>🤗 Datasets is a library for accessing and sharing datasets for Audio, Computer Vision, and Natural Language Processing (NLP).</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-distilabel">Distilabel</a></td> <td>The framework for synthetic data generation and AI feedback.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-duckdb">DuckDB</a></td> <td>In-process SQL OLAP database management system.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-fiftyone">FiftyOne</a></td> <td>FiftyOne is a library for curation and visualization of image, video, and 3D data.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-pandas">Pandas</a></td> <td>Python data analysis toolkit.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-polars">Polars</a></td> <td>A DataFrame library on top of an OLAP query engine.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-spark">Spark</a></td> <td>Real-time, large-scale data processing tool in a distributed environment.</td> <td>✅</td> <td>✅</td></tr> <tr><td><a href="./datasets-webdataset">WebDataset</a></td> <td>Library to write I/O pipelines for large datasets.</td> <td>✅</td> <td>❌</td></tr></tbody>',$,l,v,c,L;return d=new W({props:{title:"Libraries",local:"libraries",headingTag:"h1"}}),l=new G({props:{source:"https://github.com/huggingface/hub-docs/blob/main/docs/hub/datasets-libraries.md"}}),{c(){r=f("meta"),b=h(),p=f("p"),g=h(),T(d.$$.fragment),y=h(),i=f("p"),i.innerHTML=k,_=h(),n=f("p"),n.textContent=x,P=h(),o=f("table"),o.innerHTML=H,$=h(),T(l.$$.fragment),v=h(),c=f("p"),this.h()},l(t){const e=N("svelte-u9bgzb",document.head);r=m(e,"META",{name:!0,content:!0}),e.forEach(a),b=u(t),p=m(t,"P",{}),A(p).forEach(a),g=u(t),C(d.$$.fragment,t),y=u(t),i=m(t,"P",{"data-svelte-h":!0}),w(i)!=="svelte-19pvdk"&&(i.innerHTML=k),_=u(t),n=m(t,"P",{"data-svelte-h":!0}),w(n)!=="svelte-ff3ufa"&&(n.textContent=x),P=u(t),o=m(t,"TABLE",{"data-svelte-h":!0}),w(o)!=="svelte-1hcj4t5"&&(o.innerHTML=H),$=u(t),C(l.$$.fragment,t),v=u(t),c=m(t,"P",{}),A(c).forEach(a),this.h()},h(){O(r,"name","hf:doc:metadata"),O(r,"content",U)},m(t,e){R(document.head,r),s(t,b,e),s(t,p,e),s(t,g,e),E(d,t,e),s(t,y,e),s(t,i,e),s(t,_,e),s(t,n,e),s(t,P,e),s(t,o,e),s(t,$,e),E(l,t,e),s(t,v,e),s(t,c,e),L=!0},p:z,i(t){L||(M(d.$$.fragment,t),M(l.$$.fragment,t),L=!0)},o(t){S(d.$$.fragment,t),S(l.$$.fragment,t),L=!1},d(t){t&&(a(b),a(p),a(g),a(y),a(i),a(_),a(n),a(P),a(o),a($),a(v),a(c)),a(r),I(d,t),I(l,t)}}}const U='{"title":"Libraries","local":"libraries","sections":[],"depth":1}';function V(D){return F(()=>{new URLSearchParams(window.location.search).get("fw")}),[]}class Y extends j{constructor(r){super(),B(this,r,V,Q,q,{})}}export{Y as component};
