This is going to be another one of those posts where I did something ridiculous and then show you how I got there, so let's just get right to it. Yep, that's Rust code with embedded Objective-C syntax, and it works. Why would you do such a thing? Maybe you want tighter interop between the Rust and Objective-C parts of your iOS app. Maybe you want to write your iOS app entirely in Rust.

Object-oriented programming (OOP) is the foundation of modern programming languages, including C, Java, C#, Visual Basic .NET, Ruby, and Objective-C.

Swift is Apple's new, native, fast, and easy to learn programming language for iOS and OS X app development. If you are an iOS developer or planning to become one, learning Swift is your #1 priority, and Learn Swift on the Mac tells you everything you need to get up to speed, well, swiftly. You'll start with the Swift Playground and an introduction to object-oriented programming so you can immediately see Swift in action. You then learn about all of the key language features like functions and closures, classes, methods, extensions, and how Swift works just as well as Objective-C when it comes to easy memory management with ARC. Finally you'll learn how to use Swift alongside Objective-C as well as with Core Data, and you'll learn how to put all of the pieces together with a health app using Apple's new HealthKit framework.

Determining the programming language of a source code file has been considered in the research community; it has been shown that Machine Learning (ML) and Natural Language Processing (NLP) algorithms can be effective in identifying the programming language of source code files. However, determining the programming language of a code snippet or a few lines of source code is still a challenging task. Online forums such as Stack Overflow and code repositories such as GitHub contain a large number of code snippets. In this paper, we describe Source Code Classification (SCC), a classifier that can identify the programming language of code snippets written in 21 different programming languages. A Multinomial Naive Bayes (MNB) classifier is employed which is trained using Stack Overflow posts. It is shown to achieve an accuracy of 75% which is higher than that with Programming Languages Identification (PLI a proprietary online classifier of snippets) whose accuracy is only 55.5%. The average score for precision, recall and the F1 score with the proposed tool are 0.76, 0.75 and 0.75, respectively. In addition, it can distinguish between code snippets from a family of programming languages such as C, C++ and C#, and can also identify the programming language version such as C# 3.0, C# 4.0 and C# 5.0.

Taking the opportunity provided by our recent Spring release, BigML is pleased to announce our new SDK for Objective-C, bigml-objc, which provides a modern, block-based Objective-C API, and a new more maintainable and coherent design. Additionally, bigml-objc includes support for our exciting new DSL for the automation of ML workflows, WhizzML. Its main aim is allowing iOS, OS X, watchOS, and tvOS developers to easily integrate BigML services into their apps while also benefitting from modern Objective-C features, first and foremost Objective-C blocks, which allow for a simple handling of asynchronous operations. Remote resource processing: BigML SDK exposes BigML's REST API through a higher-level Objective-C API that will make is easier for you to create, retrieve, update, and delete remote resources. Local resource processing: BigML SDK allows you to mix local and remote distributed processing in a seamless and transparent way.

Taking the opportunity provided by our recent Spring release, BigML is pleased to announce our new SDK for Objective-C, bigml-objc, which provides a modern, block-based Objective-C API, and a new more maintainable and coherent design. Additionally, bigml-objc includes support for our exciting new DSL for the automation of ML workflows, WhizzML.