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
• references
• type hierarchy
• calls to functions, calls to base and derived functions
• rename
• goto definition, goto base method
• document symbol search
• global symbol search

Setup

Building

Eventually, cquery will be published in the vscode extension marketplace and you will be able to install and run it without any additional steps. To use cquery you need to clone this repository, build it, and then run the vscode extension in the vscode-client folder.

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

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

After VSCode is running, update the ServerOptions inside of extension.ts to point to the absolute path of your build directory. For example,

let serverOptions: ServerOptions = {
    command: './app',
    args: ['--language-server'],
    options: {
      cwd: '/home/cquery/build/'
    }
  }

You can hit then F5 to launch the extension locally. Consider taking a look at the options cquery makes available in vscode settings.

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

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",
  ],
  // ...
}

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 -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

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