# NghiaTranUIT/FeSpinner

Rocket Loader Collection for iOS app

Repository: https://github.com/NghiaTranUIT/FeSpinner
Canonical: https://ross.abutalabs.com/products/fespinner
Language: Objective-C
License Family: other
Last push: 2020-03-16T15:57:22+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4669, "days_push": 2361, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1463, forks 268 (observed 2026-08-28T04:04:47.775515+00:00)

## What it is
FeSpinner is a collection of customizable loading spinner/HUD components for iOS apps, written in Objective-C. It offers multiple animated loader styles (handwriting, rolling, equalizer, hourglass, etc.) with an MBProgressHUD-like API for showing loaders while executing blocks or selectors.

## Use cases
- show a loading spinner while a task runs in an iOS app
- add custom animated HUD overlays to iOS views
- find creative loading indicator designs for mobile apps
- replace MBProgressHUD with a different loader collection
- display a blur-background loading overlay during network requests

## When to choose
- you build an iOS app in Objective-C and want a variety of stylish loading spinners
- you want simple copy-in loader files with no dependency manager required
- you need MBProgressHUD-style show/dismiss and block-execution APIs

## When to avoid
- you need a Swift-native or actively maintained spinner library
- you require a package manager integration like CocoaPods or SPM
- you need loaders for Android or cross-platform frameworks

## Facets
- artifact type: library
- maturity: maintenance
- function: ui-components, animation
- domain: mobile-development, frontend
- platform: -
- tags: loading-indicators, objective-c, hud, spinners, uikit, ios, mobile

## Member repositories
- NghiaTranUIT/FeSpinner (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:47.775515+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 2026-08-30T04:35:11.376395+00:00, confidence not recorded.
  - readme: https://github.com/NghiaTranUIT/FeSpinner (fetched 2026-08-28T04:04:47.775515+00:00, sha 144cf7a8c5d4)
- Data as of 2026-08-30T08:39:29.467469+00:00.