Canley Notifications Lite is a zero-dependency, native iOS wrapper. It simplifies scheduling & management into a clean, thread-safe, and Editor-friendly interface, saving time on complex integrations.This asset is for backend management of iOS Notifications and does not require rendering. (Aside from the simple demo scene.)The Canley Notifications Lite Service is a universal, platform-native wrapper for iOS local notifications. By turning the complex iOS notification process into a simple, thread-safe system, this package makes it incredibly easy for developers to implement reminders, re-engagement triggers, or scheduled alerts.The code is fully customisable via a clean, unified API, allowing you to tailor notification logic to your project's needs without the bloat of third-party dependencies.Zero-Dependency Core: Built using pure C# that interfaces natively with the iOS Notification Center, requiring no external plugins or proprietary frameworks.Editor-Friendly Simulation: Provides non-intrusive, console-based feedback when developing in the Unity Editor, allowing you to debug your logic without needing to push a build to a device for every tweak.Robust CRUD Architecture: Treats notifications as persistent records, enabling you to Create, Read, Update, and Delete specific alerts using unique GUIDs to prevent duplicate notification conflicts.Flexible Trigger System: Supports both relative time-based alerts and precise calendar-based scheduling, with an easy-to-use utility to calculate time intervals in seconds.Timezone-Aware Logic: Includes a configurable UseUtc flag, allowing you to toggle between local "wall-clock" time and absolute UTC time to suit your specific scheduling requirements.Streamlined Implementation: Requests native iOS permissions with a single method call and includes a unified API that simplifies the complex native iOS notification lifecycle.Gemini AI was used as a coding assistant to help architect the C# logic. All AI-generated suggestions were manually reviewed, tested, and integrated by the developer to ensure they meet Unity’s performance and safety standards. No third-party datasets were used to train a model for this package; it is a standard tool built with AI assistance.
