An iOS search bar component with auto-completion suggestions, supporting both simple strings and custom objects with images.
ModernSearchBar is an open-source iOS library that implements a search bar with auto-completion features. It provides a dropdown suggestions view that updates as users type, supporting both plain text and custom objects with remote images. It solves the need for a ready-to-use, customizable search component that mimics iOS's native search behavior without extensive custom development.
iOS developers building apps that require search functionality with suggestions, such as product catalogs, contact lists, or content discovery interfaces. It's suitable for those using Swift and UIKit who want a drop-in replacement for UISearchBar with enhanced features.
Developers choose ModernSearchBar for its ease of integration, dual data source support, and high customizability. It saves time compared to building auto-completion from scratch and offers a native-like experience with additional flexibility for advanced use cases like image-loaded suggestions.
The famous iOS search bar with auto completion feature implemented.
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Can be integrated via Interface Builder by setting a custom class, simplifying setup for developers using storyboards, as shown in the usage section.
Supports both simple string arrays and custom objects with image URLs (ModernSearchBarModel), allowing for basic or enriched suggestions, demonstrated in the dual demos.
Offers numerous properties to tweak UI elements like shadows, icons, labels, and layout, enabling deep styling to match app design, detailed in the CUSTOMIZING code snippets.
Inherits from UISearchBarDelegate and adds methods for suggestion selection, making it easy to handle interactions without custom table view implementations.
Last updated in 2017 with version 1.5, which may not support newer iOS versions, Swift language features, or have recent bug fixes and security updates.
Only accepts pre-loaded arrays for suggestions, lacking built-in support for asynchronous fetching, pagination, or performance optimizations for large datasets.
Tied to UIKit, making it incompatible with SwiftUI projects without additional bridging code, which adds complexity for modern iOS development.