A Swift library for easy asynchronous downloading, caching, and display of remote images in iOS, tvOS, and macOS apps.
Imaginary is a Swift library designed to simplify the handling of remote images in iOS, tvOS, and macOS applications. It provides asynchronous downloading, caching, and display capabilities, solving the common hassle of managing network-sourced images efficiently. The library includes features like memory and disk caching, image pre-processing, and support for various view types.
iOS, tvOS, and macOS developers who need to integrate remote images into their apps with minimal boilerplate and robust caching.
Developers choose Imaginary for its narrow yet flexible API, built-in caching with expiry management, and extensibility through custom processors and displayers, making remote image handling straightforward and highly customizable.
:unicorn: Remote images, as easy as one, two, three.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Efficiently fetches images in the background without blocking the UI, as demonstrated in the basic setImage(url:) examples for smooth user experiences.
Uses memory and disk caching via the Cache library for fast retrieval and automatic expiry management, reducing network calls and improving performance.
Works with any view type through customizable ImageDisplayer protocols, allowing integration with UIImageView, UIButton, and beyond, per the advanced usage section.
Supports custom ImageProcessor implementations for tasks like tinting, enabling image modifications before display without boilerplate code.
The README marks pre-processors like ResizeImageProcessor and RoundImageProcessor as incomplete, forcing developers to write custom code for common transformations.
Relies on the Cache library for storage, adding an extra dependency that can complicate projects aiming for minimal third-party code or lightweight setups.
Lacks support for progressive loading, animated formats like GIFs, or advanced image decoding, which are standard in more comprehensive libraries.