./configure.py generates the
build.ninja files used to build
ninja. It accepts various flags to adjust build parameters.
Run './configure.py --help' for more configuration options.
The primary build target of interest is
ninja, but when hacking on
Ninja your changes should be testable so it's more useful to build and
ninja_test when developing.
Ninja is built using itself. To bootstrap the first binary, run the
configure script as
./configure.py --bootstrap. This first compiles
all non-test source files together, then re-builds Ninja using itself.
You should end up with a
ninja binary (or
ninja.exe) in the source root.
On Windows, you'll need to install Python to run
run everything under a Visual Studio Tools Command Prompt (or after
vcvarsall in a normal command prompt). See below if you
want to use mingw or some other compiler instead using Visual Studio.
Adjusting build flags
Build in "debug" mode while developing (disables optimizations and builds way faster on Windows):
To use clang, set
How to successfully make changes to Ninja
Github pull requests are convenient for me to merge (I can just click
a button and it's all handled server-side), but I'm also comfortable
accepting pre-github git patches (via
Good pull requests have all of these attributes:
- Are scoped to one specific issue
- Include a test to demonstrate their correctness
- Update the docs where relevant
- Match the Ninja coding style (see below)
- Don't include a mess of "oops, fix typo" commits
These are typically merged without hesitation. If a change is lacking any of the above I usually will ask you to fix it, though there are obvious exceptions (fixing typos in comments don't need tests).
I am very wary of changes that increase the complexity of Ninja (in particular, new build file syntax or command-line flags) or increase the maintenance burden of Ninja. Ninja is already successfully used by hundreds of developers for large projects and it already achieves (most of) the goals I set out for it to do. It's probably best to discuss new feature ideas on the mailing list before I shoot down your patch.
Set your build command to
./ninja ninja_test && ./ninja_test --gtest_filter=MyTest.Name
now you can repeatedly run that while developing until the tests pass (I frequently set it as my compilation command in Emacs). Remember to build "all" before committing to verify the other source still works!
Testing performance impact of changes
If you have a Chrome build handy, it's a good test case. Otherwise, the github downoads page has a copy of the Chrome build files (and depfiles). You can untar that, then run
and compare that against a baseline Ninja.
There's a script at
misc/measure.py that repeatedly runs a command like
the above (to address variance) and summarizes its runtime. E.g.
path/to/misc/measure.py path/to/my/ninja chrome
For changing the depfile parser, you can also build
and run that directly on some representative input files.
Generally it's the Google C++ coding style, but in brief:
- Function name are camelcase.
- Member methods are camelcase, expect for trivial getters which are underscore separated.
- Local variables are underscore separated.
- Member variables are underscore separated and suffixed by an extra underscore.
- Two spaces indentation.
- Opening braces is at the end of line.
- Lines are 80 columns maximum.
- All source files should have the Google Inc. license header.
\ato refer to arguments.
- It's not necessary to document each argument, especially when they're
relatively self-evident (e.g. in
CanonicalizePath(string* path, string* err), the arguments are hopefully obvious)
Building the manual
sudo apt-get install asciidoc --no-install-recommends ./ninja manual
Building the code documentation
sudo apt-get install doxygen ./ninja doxygen
Building for Windows
While developing, it's helpful to copy
ninja.exe to another name like
n.exe; otherwise, rebuilds will be unable to write
it's locked while in use.
Via Visual Studio
- Install Visual Studio (Express is fine), Python for Windows, and (if making changes) googletest (see above instructions)
- In a Visual Studio command prompt:
python configure.py --bootstrap
Via mingw on Windows (not well supported)
- Install mingw, msys, and python
- In the mingw shell, put Python in your path, and
python configure.py --bootstrap
- To reconfigure, run
- Remember to strip the resulting executable if size matters to you
Via mingw on Linux (not well supported)
Setup on Ubuntu Lucid:
sudo apt-get install gcc-mingw32 wine
export CC=i586-mingw32msvc-cc CXX=i586-mingw32msvc-c++ AR=i586-mingw32msvc-ar
Setup on Ubuntu Precise:
sudo apt-get install gcc-mingw-w64-i686 g++-mingw-w64-i686 wine
export CC=i686-w64-mingw32-gcc CXX=i686-w64-mingw32-g++ AR=i686-w64-mingw32-ar
Setup on Arch:
- Uncomment the
sudo pacman -Sy.
sudo pacman -S mingw-w64-gcc wine
export CC=x86_64-w64-mingw32-cc CXX=x86_64-w64-mingw32-c++ AR=x86_64-w64-mingw32-ar
./configure.py --platform=mingw --host=linux
ninja.exeusing a Linux ninja binary:
./ninja.exe(implicitly runs through wine(!))
Using Microsoft compilers on Linux (extremely flaky)
The trick is to install just the compilers, and not all of Visual Studio, by following these instructions.
Do a clean debug build with the right flags:
CFLAGS=-coverage LDFLAGS=-coverage ./configure.py --debug ninja -t clean ninja_test && ninja ninja_test
Run the test binary to generate
.gcno files in the build
directory, then run gcov on the .o files to generate
.gcov files in the
./ninja_test gcov build/*.o
Look at the generated
.gcov files directly, or use your favorite gcov viewer.
Build with afl-clang++:
CXX=path/to/afl-1.20b/afl-clang++ ./configure.py ninja
Then run afl-fuzz like so:
afl-fuzz -i misc/afl-fuzz -o /tmp/afl-fuzz-out ./ninja -n -f @@
You can pass
-x misc/afl-fuzz-tokens to use the token dictionary. In my
testing, that did not seem more effective though.
Using afl-fuzz with asan
If you want to use asan (the
isysroot bit is only needed on OS X; if clang
can't find C++ standard headers make sure your LLVM checkout includes a libc++
checkout and has libc++ installed in the build directory):
CFLAGS="-fsanitize=address -isysroot $(xcrun -show-sdk-path)" \ LDFLAGS=-fsanitize=address CXX=path/to/afl-1.20b/afl-clang++ \ ./configure.py AFL_CXX=path/to/clang++ ninja
Make sure ninja can find the asan runtime:
DYLD_LIBRARY_PATH=path/to//lib/clang/3.7.0/lib/darwin/ \ afl-fuzz -i misc/afl-fuzz -o /tmp/afl-fuzz-out ./ninja -n -f @@