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RxSwift: Deep Cuts

There are two properties of the RxSwift API that make it painfully easy to create memory management related bugs.

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Even though the MVVM is straightforward, writing unit tests for various use cases is still tricky. So let’s learn how to write tests properly…

The one concept Nietzsche, Thoreau and Hesse most probably tried to elude through their lives: Dependency. Even if one does not agree or embrace their philosophies, a programmer should — or must? — apply their way of thinking while programming.
The journey through the RxSwift universe is something vast that begins with a much broader concern, the reactive way of thinking, which is a shift in our programming mindset. Reactive programming is a topic that requires understanding for proper use, so the road for this kind of knowledge needs to start with core concepts as well as the motivation behind this different approach to programming. This post is a sort of entrance ticket for this reactive club, but the swift and iOS session of the party.
Apple started using deep learning for face detection in iOS 10. With the release of the Vision framework, developers can now use this technology and many other computer vision algorithms in their apps. We faced significant challenges in developing the framework so that we could preserve user privacy and run efficiently on-device. This article discusses these challenges and describes the face detection algorithm. 
Framework for mock generation. Adds a set of handy methods, simplifying testing.

TransitionableTab makes it easy to animate when switching between tab.

A tool for defining design systems and using them to generate cross-platform UI code, Sketch files, images, and other artifacts.

AwLargest list of models for Core ML (for iOS 11+).

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