mirror of
https://github.com/MaskRay/ccls.git
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141 lines
4.4 KiB
Markdown
141 lines
4.4 KiB
Markdown
# Notice
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cquery is not yet production ready. I use it day-to-day, but there are still a number of significant issues and unimplemented features.
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# cquery
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[](https://gitter.im/cquery-project/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
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cquery is a low-latency language server for C++. It is extremely scalable and
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has been designed for and tested on large code bases like
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[Chromium](https://chromium.googlesource.com/chromium/src/). It's primary goal
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is to make working on large code bases much faster by providing accurate and
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fast semantic analysis.
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There are rough edges (especially when editing), but it is already possible to
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be productive with cquery. Here's a list of implemented features:
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* code completion
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* references
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* type hierarchy
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* calls to functions, calls to base and derived functions
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* rename
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* goto definition, goto base method
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* document symbol search
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* global symbol search
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* hover
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* diagnostics
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# Setup
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## Building
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Eventually, cquery will be published in the vscode extension marketplace and you
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will be able to install and run it without any additional steps. To use cquery
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you need to clone this repository, build it, and then run the vscode extension
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in the `vscode-client` folder.
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```bash
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# Build cquery
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$ git clone https://github.com/jacobdufault/cquery --recursive
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$ cd cquery
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$ ./waf configure
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$ ./waf build
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# Build extension
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$ cd vscode-client
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$ npm install
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$ code .
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```
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After VSCode is running, update the `ServerOptions` inside of `extension.ts` to
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point to the absolute path of your build directory. For example,
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```js
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let serverOptions: ServerOptions = {
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command: './app',
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args: ['--language-server'],
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options: {
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cwd: '/home/cquery/build/'
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}
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}
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```
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You can hit then `F5` to launch the extension locally. Consider taking a look at
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the options cquery makes available in vscode settings.
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If you run into issues, you can view debug output by running the
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(`F1`) `View: Toggle Output` command and opening the `cquery` output section.
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## Project setup
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### System includes
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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,
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```js
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{
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// ...
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"cquery.extraClangArguments": [
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// Generated by running the following in a Chrome checkout:
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// $ ./third_party/llvm-build/Release+Asserts/bin/clang++ -v ash/debug.cc
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"-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/c++/4.8",
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"-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/x86_64-linux-gnu/c++/4.8",
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"-isystem/usr/lib/gcc/x86_64-linux-gnu/4.8/../../../../include/c++/4.8/backward",
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"-isystem/usr/local/include",
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"-isystem/work/chrome/src/third_party/llvm-build/Release+Asserts/lib/clang/5.0.0/include",
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"-isystem/usr/include/x86_64-linux-gnu",
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"-isystem/usr/include",
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],
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// ...
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}
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```
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### compile_commands.json (Best)
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To get the most accurate index possible, you can give cquery a compilation
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database emitted from your build system of choice. For example, here's how to
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generate one in ninja. When you sync your code you should regenerate this file.
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```bash
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$ ninja -t compdb cxx cc > compile_commands.json
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```
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The `compile_commands.json` file should be in the top-level workspace directory.
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### cquery.extraClangArguments
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If for whatever reason you cannot generate a `compile_commands.json` file, you
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can add the flags to the `cquery.extraClangArguments` configuration option.
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### clang_args
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If for whatever reason you cannot generate a `compile_commands.json` file, you
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can add the flags to a file called `clang_args` located in the top-level
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workspace directory.
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Each argument in that file is separated by a newline. Lines starting with `#`
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are skipped. Here's an example:
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```
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# Language
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-xc++
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-std=c++11
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# Includes
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-I/work/cquery/third_party
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```
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# Limitations
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cquery is able to respond to queries quickly because it caches a huge amount of
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information. When a request comes in, cquery just looks it up in the cache
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without running many computations. As a result, there's a large memory overhead.
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For example, a full index of Chrome will take about 10gb of memory. If you
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exclude v8, webkit, and third_party, it goes down to about 6.5gb.
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# License
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MIT
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