Pikapika is a cross-platform comic reader and downloader built with Flutter and Go, providing an ad-free experience for reading manga and comics. The application supports Windows, macOS, Linux, Android, and iOS, offering features such as browsing comics by category, searching, reading online or offline, managing downloads, favoriting content, viewing and posting comments, and downloading games. It includes a pro tier that unlocks advanced features like batch operations and extended export capabilities. The architecture separates the Flutter-based UI from a Go-based core backend, communicating via MethodChannels on mobile and go-flutter plugins on desktop. Local data storage for settings, favorites, and download history is managed through a central Method service. The UI is composed of reusable widgets organized in a component library, including specialized widgets for displaying comics, handling asynchronous states, and managing user interactions. Settings are implemented as individual classes that persist user preferences and broadcast changes via an event bus. Key entry points include platform-specific native code (MainActivity for Android, AppDelegate for iOS, etc.) and Flutter's main.dart/main_desktop.dart. Data flows involve user interactions triggering API requests through the Method service, which communicates with the Go backend to fetch or process data, then updates the UI accordingly. The application relies on various Flutter plugins for permissions, file handling, networking, and UI enhancements, while the Go core handles core logic and API interactions. We note that the project is actively maintained with recent commits and a low level of technical drift, indicating ongoing compatibility with current dependencies and platform SDKs.
TruyenDrive is a userscript that injects a full-featured comic/manga reader UI into Google Drive and OneDrive folder pages. Built with Vite, React 19, and TypeScript, it runs as a Tampermonkey script that mounts a shadow DOM reader overlay on top of the cloud storage page. The system automatically scans folder structures to detect chapters (sub-folders) or flat image lists, supports left-to-right, right-to-left, and top-to-bottom reading directions, spread layouts, zoom, page preloading, and browser history integration. It also implements a custom image encryption/decryption system using XOR and scanline methods, with Web Worker support for performance. The architecture is cleanly separated into provider abstractions (Google Drive, OneDrive), a state machine for folder classification, and a rich settings system with theme presets and persistence. The codebase demonstrates strong engineering practices including TypeScript strict mode, proper error boundaries, and reusable utility modules.