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Contributing

This document provides information for developers who want to contribute to the RLS or run it in a heavily customised configuration.

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) in #rust-dev-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.

If you want to implement RLS support in an editor, see clients.md.

Building

Note, you don't need to build the rls to use it. Instead, you can install via rustup, which is the currently preferred method. See the readme for more information.

Step 1: Install build dependencies

On Linux, you will need cmake, pkg-config and zlib:

  • On Ubuntu run: sudo apt-get install cmake pkg-config zlib1g-dev libssl-dev
  • On Fedora run: sudo dnf install cmake pkgconfig zlib-devel openssl-devel

On Windows, you will need to have cmake installed.

Step 2: Clone and build the RLS

Since the RLS is closely linked to the compiler and is in active development, you'll need a recent nightly compiler to build it.

git clone https://github.com/rust-lang/rls.git
cd rls
cargo build --release

Step 3: Connect the RLS to your compiler

If you're using recent versions of rustup, you will also need to make sure that the compiler's dynamic libraries are available for the RLS to load. You can see where they are using:

rustc --print sysroot

This will show you where the compiler keeps the dynamic libs. In Windows, this will be in the bin directory under this path. On other platforms, it will be in the lib directory.

Next, you'll make the compiler available to the RLS:

Windows

On Windows, make sure this path (plus bin) is in your PATH. For example:

set PATH=%PATH%;C:\Users\appveyor\.multirust\toolchains\nightly-i686-pc-windows-gnu\bin

Mac

For Mac, you need to set the DYLD_LIBRARY_PATH. For example:

export DYLD_LIBRARY_PATH=$(rustc --print sysroot)/lib

Linux

For Linux, this path is called LD_LIBRARY_PATH.

export LD_LIBRARY_PATH=$(rustc --print sysroot)/lib

Step 4: Download standard library metadata

Finally, we need to get the metadata for the standard library. This lets us get additional docs and types for all of std. The command is currently only supported on the nightly compilers, though we hope to remove this restriction in the future.

rustup component add rust-analysis

If you've never set up Racer before, you may also need to follow the Racer configuration steps

Running and testing

You can run the rls by hand with:

cargo run

Though more commonly, you'll use an IDE plugin to invoke it for you (see README.md for details).

We recommend using https://github.com/rust-lang/rls-vscode in VSCode. You can configure rls-vscode to use custom built binary by changing the rust-client.rlsPath setting to a full path to the binary you want to use.

Anything the RLS writes to stderr is redirected to the output pane in VSCode - select "Rust Language Server" from the drop down box ("Rust Language Server" will only show up if there is any debugging output from RLS). Do not write to stdout, that will cause LSP errors (this means you cannot println). You can enable logging using RUST_LOG environment variable (e.g. RUST_LOG=rls=debug code). For adding your own, temporary logging you may find the eprintln macro useful.

Test using cargo test.

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

You can run the RLS in command line mode by running with a --cli flag, e.g., cargo run -- --cli. You need to run it in the root directory of the project to be analyzed. This should initialize the RLS (which will take some time for large projects) and then give you a > prompt. Type help (or just h) to see the commands available.

During initialization RLS will print out a number of progress messages to the console. Those messages might hide the prompt. Look for progress[done:true] message.

The command line interface is useful for debugging and testing, especially to narrow down a bug to either the RLS or a client.

Standard library support

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. Rustup takes care of this for you and is the preferred (and easiest) method for installing this data. If you want to use the RLS with a Rust compiler/libraries you have built yourself, then you'll need to take some extra steps.

Install with rustup

You'll need to be using rustup to manage your Rust compiler toolchains. The RLS does not yet support cross-compilation - your compiler host and target must be exactly the same.

You must be using nightly (you need to be using nightly for the RLS to work at the moment in any case). To install a nightly toolchain use rustup install nightly. To switch to using that nightly toolchain by default use rustup default nightly.

Add the RLS data component using rustup component add rust-analysis.

Everything should now work! You may need to restart the RLS.

Build it yourself

When you build Rust, run it with a RUSTC_SAVE_ANALYSIS=api environment variable, e.g. with:

RUSTC_SAVE_ANALYSIS=api ./x.py build

When the build has finished, you should have a bunch of JSON data in a directory like ~/rust1/build/x86_64-unknown-linux-gnu/stage1-std/x86_64-unknown-linux-gnu/release/deps/save-analysis.

You need to copy all those files (should be around 16) into a new directory: ~/rust1/build/x86_64-unknown-linux-gnu/stage2/lib/rustlib/x86_64-unknown-linux-gnu/analysis (assuming you are running the stage 2 compiler you just built. You'll need to modify the root directory (~/rust1 here) and the host triple (x86_64-unknown-linux-gnu in both places)).

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

export RUSTC="~/rust1/build/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.

Details

Rustup (or you, manually) will install the rls data (which is a bunch of json files) into $SYSROOT/lib/rustlib/$TARGET_TRIPLE/analysis, where $SYSROOT is your Rust sysroot, this can be found using rustc --print=sysroot. $TARGET_TRIPLE is the triple which defines the compilation target. Since the RLS currently does not support cross-compilation, this must match your host triple. It will look something like x86_64-unknown-linux-gnu.

For example, on my system RLS data is installed at:

/home/ncameron/.rustup/toolchains/nightly-x86_64-unknown-linux-gnu/lib/rustlib/x86_64-unknown-linux-gnu/analysis

This data is only for the standard libraries, project-specific data is stored inside your project's target directory.

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 analyze 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.

Building

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/build.rs.

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 serialized 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.

Extensions to the Language Server Protocol

The RLS uses some custom extensions to the Language Server Protocol.

RLS to LSP Client

These are all sent from the RLS to an LSP client and are only used to improve the user experience by showing progress indicators.

  • window/progress: notification, title: "Building". Sent before build starts.
  • window/progress: notification with title: "Building", repeated for each compile target.
    • When total amount of work is not known, has field message set to the current crate name.
    • When total amount of work is known, has field percentage set to how much of build has started.
  • window/progress: notification, title: "Building", "done": true. Sent when build ends.
  • window/progress: notification, title: "Indexing". Sent before analysis of build starts.
  • ... standard LSP publishDiagnostics
  • window/progress: notification, title: "Indexing", "done": true. Sent when analysis ends.

LSP Client to RLS

The following request is to support Rust specific features.

  • rustDocument/implementations: request params: TextDocumentPositionParams result: Location[]

    List all implementation blocks for a trait, struct, or enum denoted by the given text document position.