# yangshun/awesome-spinners

💫 A curated collection of dazzling web spinners

Repository: https://github.com/yangshun/awesome-spinners
Canonical: https://ross.abutalabs.com/products/awesome-spinners
Language: JavaScript
License Family: other
Topics: awesome-list, awesome, spinners, css-spinners, css
Last push: 2022-02-07T09:49:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3880, "days_push": 1668, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1415, forks 81 (observed 2026-08-28T04:04:39.832380+00:00)

## What it is
A curated awesome-list of web loading spinners and loaders, covering CSS-only, SVG, JS+CSS, and Canvas implementations. It links to libraries, demos, and resources for building your own spinners.

## Use cases
- find css loading spinners for my website
- curated list of web loader animations
- best spinner libraries for frontend
- loading indicator examples with demos
- how to build my own css spinner
- svg and canvas spinner resources

## When to choose
- you want to browse and compare spinner/loader options before picking one
- you need inspiration or reference implementations for loading animations
- you want links to CSS-only, SVG, or Canvas spinner libraries with demos

## When to avoid
- you need a single ready-to-use spinner library rather than a list of links
- you need a maintained tool with guaranteed updates or support
- you need spinners for non-web platforms like mobile native or desktop

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: animation, ui-components
- domain: web-development, frontend, web-design
- platform: browser
- tags: awesome-list, css-spinners, loaders, curated-list, css, web-server

## Member repositories
- yangshun/awesome-spinners (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:39.832380+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:38:10.799248+00:00, confidence not recorded.
  - readme: https://github.com/yangshun/awesome-spinners (fetched 2026-08-28T04:04:39.832380+00:00, sha e0a8cf7dea3d)
- Data as of 2026-08-30T08:39:29.467469+00:00.