Rust Language Server provides live information such as code completion and documentation through a Microsoft co-developed protocol Developers of Mozilla’s Rust language, devised for fast and safe system-level programming, have unveiled the first release of the Rust Language Service (RLS), a project that provides IDEs and editors with live, contextual information about Rust code. RLS is one of the first implementations of the Language Server Protocol, co-developed by Microsoft, Codenvy, and Red Hat to standardized communications between IDEs and language runtimes. It’s another sign of Rust’s effort to be an A-list language across the board — not only by providing better solutions to common programming problems, but also cultivating first-class, cutting-edge tooling support from beyond its ecosystem. At this stage, RLS provides a few basic but broadly useful functions. It can flag errors as you type, locate all references for a particular symbol within a codebase, rename symbols, and provide documentation for objects found in the standard library. The first release of RLS is “pre-alpha” — at this stage it’s best thought of as a proof of concept rather than a working product. It uses the Rust compiler to supply much of the data, but in its current state, the compiler can’t always provide the data fast enough, especially when dealing with functions in larger Rust “crates,” or packages. One of the features planned for the Rust compiler, incremental compilation, should provide a performance boost to RLS as a by-product. The feature is still under wraps. Instead, RLS also makes use of an existing Rust crate, Racer, which provides code-completion data. RLS isn’t of much use by itself; it needs an IDE that supports the Language Server Protocol as a front end. Two such IDEs already exist: Eclipse and Microsoft’s Visual Studio Code. One of RLS’s chief developers, Jonathan Turner, has produced a sample RLS client for Visual Studio Code, so Rust developers who use that editor can start experimenting with it immediately. Be warned: This is still extremely rough software, so functions like refactoring code could be destructive. As the documentation says, “[RLS] is not ready for real use. It will probably eat your laundry.” Or at least leave it with rust stains. Related content news ActiveState's Python taps Intel MKL to speed data science and machine learning The MKL libraries for accelerating math operations debuted in Intel's own Python distribution, but now other Pythons are following suit By Serdar Yegulalp May 18, 2017 3 mins Data Science Machine Learning Open Source news CrateDB 2.0 Enterprise stresses security and monitoring—and open source The open source database for processing high-speed freeform data with SQL queries now has enterprise features, available as open source for faster developer uptake By Serdar Yegulalp May 16, 2017 3 mins NoSQL Databases Technology Industry Databases news analysis Waah! WannaCry shifts the blame game into high gear Every security crisis presents the opportunity to point fingers, but that's just wasted energy. The criminals are at fault—and we need to work together to stop them By Fahmida Rashid May 16, 2017 7 mins Small and Medium Business Technology Industry Malware news Faster machine learning is coming to the Linux kernel The addition of heterogenous memory management to the Linux kernel will unlock new ways to speed up GPUs, and potentially other kinds of machine learning hardware By Serdar Yegulalp May 15, 2017 3 mins Technology Industry Machine Learning Open Source Resources Videos