Notice

cquery is not yet production ready. I use it day-to-day, but there are still a number of significant issues and unimplemented features.

cquery

cquery is a low-latency language server for C++. It is extremely scalable and has been designed for and tested on large code bases like Chromium. It's primary goal is to make working on large code bases much faster by providing accurate and fast semantic analysis.

There are rough edges (especially when editing), but it is already possible to be productive with cquery. Here's a list of implemented features:

• code completion (with both signature help and snippets)
• references
• type hierarchy
• calls to functions, calls to base and derived functions
• rename
• goto definition, goto base method
• document symbol search
• global symbol search
• hover
• diagnostics
• code actions (clang FixIts)
• darken/fade code disabled by preprocessor
• #include auto-complete and quick-jump (goto definition, document links)

Setup - build cquery, install extension, setup project

There are three steps to get cquery up and running. Eventually, cquery will be published in the vscode extension marketplace which will reduce these three steps to only project setup.

Build cquery

Building cquery is simple. The external dependencies are few:

• clang (3.4 or greater)
• python
• git

$ git clone https://github.com/jacobdufault/cquery --recursive
$ cd cquery
$ ./waf configure
$ ./waf build

Install extension

cquery includes a vscode extension; it is part of the repository. Launch vscode and install the vscode-extension.tsix extension. To do this:

• Hit F1; execute the command Install from VSIX.
• Select vscode-extension.tsix in the file chooser.

IMPORTANT: Please reinstall the extension when you sync the code base - it is still being developed.

If you run into issues, you can view debug output by running the (F1) View: Toggle Output command and opening the cquery output section.

Project setup (system includes, clang configuration)

Part 1: System includes

cquery will likely fail to resolve system includes like <vector> unless the include path is updated to point to them. Add the system include paths to cquery.extraClangArguments. For example,

{
  // ...
  "cquery.extraClangArguments": [
    // Generated by running the following in a Chrome checkout:
    // $ ./third_party/llvm-build/Release+Asserts/bin/clang++ -v ash/debug.cc
    "-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/c++/4.8",
    "-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/x86_64-linux-gnu/c++/4.8",
    "-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/c++/4.8/backward",
    "-isystem/usr/local/include",
    "-isystem/work/chrome/src/third_party/llvm-build/Release+Asserts/lib/clang/5.0.0/include",
    "-isystem/usr/include/x86_64-linux-gnu",
    "-isystem/usr/include",
  ],
  // ...
}

Part 2: Clang configuration

compile_commands.json (Best)

To get the most accurate index possible, you can give cquery a compilation database emitted from your build system of choice. For example, here's how to generate one in ninja. When you sync your code you should regenerate this file.

$ ninja -C out/Release -t compdb cxx cc > compile_commands.json

The compile_commands.json file should be in the top-level workspace directory.

cquery.extraClangArguments

If for whatever reason you cannot generate a compile_commands.json file, you can add the flags to the cquery.extraClangArguments configuration option.

clang_args

If for whatever reason you cannot generate a compile_commands.json file, you can add the flags to a file called clang_args located in the top-level workspace directory.

Each argument in that file is separated by a newline. Lines starting with # are skipped. Here's an example:

# Language
-xc++
-std=c++11

# Includes
-I/work/cquery/third_party

Building extension

If you wish to modify the vscode extension, you will need to build it locally. Luckily, it is pretty easy - the only dependency is npm.

# Build extension
$ cd vscode-client
$ npm install
$ code .

When VSCode is running, you can hit F5 to build and launch the extension locally.

Limitations

cquery is able to respond to queries quickly because it caches a huge amount of information. When a request comes in, cquery just looks it up in the cache without running many computations. As a result, there's a large memory overhead. For example, a full index of Chrome will take about 10gb of memory. If you exclude v8, webkit, and third_party, it goes down to about 6.5gb.

License

MIT