Search Results for "wechat"

Tinker is a hot-fix solution library for Android, and the official one for WeChat. It supports dex, So library, and resources, allowing application updates without needing reinstallation. Tinker consists mainly of 3 parts: a gradle compile plugin, a core SDK library, and a command-line version of non-gradle compiled users. There are many other hot-fix solutions just like Tinker, but Tinker overcomes many of the problems that other solutions have.

MMKV for Android is an efficient, small mobile key-value storage framework developed by WeChat. Works on Android, iOS, macOS, Windows, and POSIX. Efficient. MMKV uses mmap to keep memory synced with file, and protobuf to encode/decode values, making the most of Android to achieve best performance. MMKV supports concurrent read-read and read-write access between processes. Easy-to-use. You can use MMKV as you go. All changes are saved immediately, no sync, no apply calls needed. ...

BGASwipeBackLayout-Android is an Android library that adds swipe-back navigation behavior to Activity screens. It implements the interaction by adapting SlidingPaneLayout behavior from the support library. The project supports normal swipe-back behavior, WeChat-style swipe-back behavior, and use with non-transparent Activity themes. Developers can dynamically enable or disable swipe-back, choose whether tracking starts only from the left edge, and control whether the WeChat-style interaction is active. It also provides options for shadows, shadow fading, swipe thresholds, and navigation bar overlap behavior. ...

This solution was built When I was working in WeChat, what is used for resolving the layout conflict when you switch between the keyboard and the emoji-panel/function-panel. JKeyboardPanelSwitch can help you handle the keyboard and panel layout conflict in Android. If you want to import a snapshot version, we have already published the snapshot version to the sonatype so you can import the snapshot version.

...Although there are already a lot of writings on the internet on the topic, a great number of possible scenarios still have to be thought of, like unsuccessful compressions, too small pictures (eg. for profile pictures) or too bad image quality. Naturally, the first idea was to see how WeChat, the app giant manages this task in action. To gather data, 100 images with different resolutions were sent through WeChat Moments, then the compressed images were compared with the original ones. Luban's foundation is the result of this analysis on WeChat's compression method. Because the process was analyzed backward, Luban's efficacy is not yet exactly the same as that of WeChat, but the results are already very close to what WeChat Moments' image compression produces.