Subscribe Free

Join 2670+ others. No spamming.
I promise!

We are currently under high development. Follow us at github.

Looking for Python Tutorials?
Check these awesome tutorials



jonathandturner / rls


Repository for the Rust Language Service (aka RLS)


Build Status Build status

Rust Language Server (RLS)

This project is in the early stages of development, it is not yet ready for real use. It will probably eat your laundry.

The RLS provides a server that runs in the background, providing IDEs, editors, and other tools with information about Rust programs. It supports functionality such as 'goto definition', symbol search, reformatting, and code completion, and enables renaming and refactorings.

The RLS gets its source data from the compiler and from Racer. Where possible it uses data from the compiler which is precise and complete. Where its not possible, (for example for code completion and where building is too slow), it uses Racer.

Since the Rust compiler does not yet support end-to-end incremental compilation, we can't offer a perfect experience. However, by optimising our use of the compiler and falling back to Racer, we can offer a pretty good experience for small to medium sized crates. As the RLS and compiler evolve, we'll offer a better experience for larger and larger crates.

The RLS is designed to be frontend-independent. We hope it will be widely adopted by different editors and IDEs. To seed development, we provide a reference implementation of an RLS frontend for Visual Studio Code.


Since the RLS is closely linked to the compiler and is in active development, you'll need a recent nightly compiler to build it. In our experience, the nightly from rustup should be avoided for the time being. Instead use a nightly you build, or one from a direct download.

Use cargo build to build.


You can run the rls by hand with:

cargo run

Though more commonly, you'll use an IDE plugin to invoke it for you. For this to work, ensure that the rls command is in your path.

To work with the RLS, your project must be buildable using cargo build. If you use syntax extensions or build scripts, it is likely things will go wrong.

VSCode integration

To run with VSCode, you'll need a recent version of that installed.

You'll then need a copy of our VSCode extension.

The RLS can operate via the Language Server protocol.

VSCode will start the RLS for you. Therefore to run, you just need to open the VSCode extension and run it. However, you must install the rls in your path so that the RLS can find it.

Be sure to provide an RLS_ROOT environment variable. Point this variable at the root of the RLS checkout:

export RLS_ROOT=/Source/rls


Test using RUST_TEST_THREADS=1 cargo test.

Testing is unfortunately minimal. There is support for regression tests, but not many actual tests exists yet. There is signifcant work to do before we have a comprehensive testing story.

Standard library support

Getting the RLS to work with the standard libraries takes a little more work, we hope to address this in the future for a more ergonomic solution (

The way it works is that when the libraries are built, the compiler can emit all the data that the RLS needs. This can be read by the RLS on startup and used to provide things like type on hover without having access to the source code for the libraries.

The compiler gives every definition an id, and the RLS matches up these ids. In order for the RLS to work, the id of a identifier used in the IDE and the id of its declaration in a library must match exactly. Since ids are very unstable, the data used by the RLS for libraries must match exactly with the crate that your source code links with.

You need a version of the above data which exactly matches the standard libraries you will use with your project. You can do this either by downloading matching data, or by building your own std libs and emitting the data at the same time.

Download the libs

You must be using nightly, find out what date nightly you have. Note that this may not be the date given by --version (build date vs distribution date). The easiest way to do this is to download a specific day's nightly and use that. Then, navigate to the Rust archives and click through to your Rust's date. You will see a lot of files. Find one that looks like rust-analysis-nightly-$YOUR_TARGET_TRIPLE.tar.gz, and download it. For example, if you are on regular Linux and have a compiler for 21st December 2016, you will want -unknown-linux-gnu.tar.gz.

OK, now open the archive. Navigate through the various sub-directories to find one called analysis. It will be somewhere like: rust-analysis-x86_64-unknown-linux-gnu/lib/rustlib/x86_64-unknown-linux-gnu/analysis. You must extract the JSON files in that analysis directory to lib/save-analysis in your Rust sysroot, e.g., (on Linux, no multi-rust/rustup) /usr/local/lib/save-analysis. To find your sysroot you can use rustc --print=sysroot. Note that if you change Rust installation (e.g., using rustup), your sysroot might change.

Build it yourself

In your Rust directory, you want to run the following:

# Or whatever -j you usually use.
RUSTFLAGS_STAGE2='-Zsave-analysis-api' make -j6

Then go get a coffee, possibly from a cafe on the other side of town if you have a slower machine.

If all goes well, you should have a bunch of JSON data in a directory like ~/rust/x86_64-unknown-linux-gnu/stage2/lib/rustlib/x86_64-unknown-linux-gnu/lib/save-analysis.

You need to copy all those files (should be around 16) into a directory called analysis in your Rust sysroot (see above for details).

Finally, to run the RLS you'll need to set things up to use the newly built compiler, something like:

export RUSTC="/home/ncameron/rust/x86_64-unknown-linux-gnu/stage2/bin/rustc"

Either before you run the RLS, or before you run the IDE which will start the RLS.

Implementation overview

The goal of the RLS project is to provide an awesome IDE experience now. That means not waiting for incremental compilation support in the compiler. However, Rust is a somewhat complex language to analyse and providing precise and complete information about programs requires using the compiler.

The RLS has two data sources - the compiler and Racer. The compiler is always right, and always precise. But can sometimes be too slow for IDEs. Racer is nearly always fast, but can't handle some constructs (e.g., macros) or can only handle them with limited precision (e.g., complex generic types).

The RLS tries to provide data using the compiler. It sets a time budget and queries both the compiler and Racer. If the compiler completes within the time budget, we use that data. If not, we use Racer's data.

We link both Racer and the compiler into the RLS, so we don't need to shell out to either (though see notes on the build process below). We also customise our use of the compiler (via standard APIs) so that we can read modified files directly from memory without saving them to disk.


The RLS tracks changes to files, and keeps the changed file in memory (i.e., the RLS does not need the IDE to save a file before providing data). These changed files are tracked by the 'Virtual File System' (which is a bit of a grandiose name for a pretty simple file cache at the moment, but I expect this area to grow significantly in the future). The VFS is in a separate crate.

We want to start building before the user needs information (it would be too slow to start a build when data is requested). However, we don't want to start a build on every keystroke (this would be too heavy on user resources). Nor is there any point starting multiple builds when we would throw away the data from some of them. We therefore try to queue up and coalesce builds. This is further documented in src/

When we do start a build, we may also need to build dependent crates. We therefore do a full cargo build. However, we do not compile the last crate (the one the user is editing in the IDE). We only run Cargo to get a command line to build that crate. Furthermore, we cache that command line, so for most builds (where we don't need to build dependent crates, and where we can be reasonably sure they haven't changed since a previous build) we don't run Cargo at all.

The command line we got from Cargo, we chop up and feed to the in-process compiler. We then collect error messages and analysis data in JSON format (although this is inefficient and should change).

Analysis data

From the compiler, we get a serialised dump of its analysis data (from name resolution and type checking). We combine data from all crates and the standard libraries and combine this into an index for the whole project. We cross- reference and store this data in HashMaps and use it to look up data for the IDE.

Reading, processing, and storing the analysis data is handled by the rls-analysis crate.

Communicating with IDEs

The RLS communicates with IDEs via the Language Server protocol.

The LS protocol uses JSON sent over stdin/stdout. The JSON is rather dynamic - we can't make structs to easily map to many of the protocol objects. The client sends commands and notifications to the RLS. Commands must get a reply, notifications do not. Usually the structure of the reply is dictated by the protocol spec. The RLS can also send notifications to the client. So for a long running task (such as a build), the RLS will reply quickly to acknowledge the request, then send a message later with the result of the task.

Associating requests with replies is done using an id which must be handled by the RLS.


The RLS is open source and we'd love you to contribute to the project. Testing, reporting issues, writing documentation, writing tests, writing code, and implementing clients are all extremely valuable.

Here is the list of known issues. These are good issues to start on.

We're happy to help however we can. The best way to get help is either to leave a comment on an issue in this repo, or to ping us (nrc or jntrnr) in #rust-tools on IRC.

We'd love for existing and new tools to use the RLS. If that sounds interesting please get in touch by filing an issue or on IRC.