CppInterOp exposes API from Clang and LLVM in a backward compatibe way. The API support downstream tools that utilize interactive C++ by using the compiler as a service. That is, embed Clang and LLVM as a libraries in their codebases. The API are designed to be minimalistic and aid non-trivial tasks such as language interoperability on the fly. In such scenarios CppInterOp can be used to provide the necessary introspection information to the other side helping the language cross talk.
The CppInterOp library provides a minimalist approach for other languages to bridge C++ entities (variables, classes, etc.). This enables interoperability with C++ code, bringing the speed and efficiency of C++ to simpler, more interactive languages like Python.
CppInterOp can be adopted incrementally. While the rest of the framework is the same, a small part of CppInterOp can be utilized. More components may be adopted over time.
While the library includes some tricky code, it is designed to be simple and robust (simple function calls, no inheritance, etc.). The goal is to make it as close to the compiler API as possible, and each routine to do just one thing that it was designed for.
The main use case for CppInterOp is with the CPPYY service. CPPYY is an automatic run-time bindings generator for Python & C++, and supports a wide range of C++ features (e.g., template instantiation). It operates on demand and generates only what is necessary. It requires a compiler (Cling1 /Clang-REPL2) that can be available during program runtime.
Once CppInterOp is integrated with LLVM's3 Clang-REPL component (that can then be used as a runtime compiler for CPPYY), it will further enhance CPPYY's performance in the following ways:
- Simpler codebase: Removal of string parsing logic will lead to a simpler code base.
- LLVM Integration: The CppInterOp interfaces will be a part of the LLVM toolchain (as part of Clang-REPL).
- Better C++ Support: C++ features such as Partial Template Specialization will be available through CppInterOp.
- Fewer Lines of Code: A lot of dependencies and workarounds will be removed, reducing the lines of code required to execute CPPYY.
- Well tested interoperability Layer: The CppInterOp interfaces have full unit test coverage.
Besides being developed as a general-purpose library, one of the long-term goals of CppInterOp is to stay backward compatible and be adopted in the High Energy Physics (HEP) field, as it will become an essential part of the Root framework. Over time, parts of the Root framework can be swapped by this API, adding speed and resilience with it.
Build instructions for CppInterOp and its dependencies are as follows. CppInterOP can be built with either Cling and Clang-REPL, so instructions will differ slightly depending on which option you would like to build, but should be clear from the section title which instructions to follow.
First clone the CppInterOp repository, as this contains patches that need to be applied to the subsequently cloned llvm-project repo (these patches are only applied if building CppInterOp with Clang-REPL)
git clone --depth=1 https://github.com/compiler-research/CppInterOp.git
and clone cppyy-backend repository where we will be installing the CppInterOp library
git clone --depth=1 https://github.com/compiler-research/cppyy-backend.git
Clone the 18.x release of the LLVM project repository.
git clone --depth=1 --branch release/18.x https://github.com/llvm/llvm-project.git
cd llvm-project
For Clang 16 & 17, the following patches required for development work. To apply these patches on Linux and MacOS execute the following command(substitute {version}
with your clang version):
git apply -v ../CppInterOp/patches/llvm/clang{version}-*.patch
and
cp -r ..\CppInterOp\patches\llvm\clang17* .
git apply -v clang{version}-*.patch
on Windows.
Clang-REPL is an interpreter that CppInterOp works alongside. Build Clang (and Clang-REPL along with it). On Linux and MaxOS you do this by executing the following command
mkdir build
cd build
cmake -DLLVM_ENABLE_PROJECTS=clang \
-DLLVM_TARGETS_TO_BUILD="host;NVPTX" \
-DCMAKE_BUILD_TYPE=Release \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_USE_LINKER=lld \
-DCLANG_ENABLE_STATIC_ANALYZER=OFF \
-DCLANG_ENABLE_ARCMT=OFF \
-DCLANG_ENABLE_FORMAT=OFF \
-DCLANG_ENABLE_BOOTSTRAP=OFF \
../llvm
cmake --build . --target clang clang-repl --parallel $(nproc --all)
On Windows you would do this by executing the following
$env:ncpus = $([Environment]::ProcessorCount)
mkdir build
cd build
cmake -DLLVM_ENABLE_PROJECTS=clang `
-DLLVM_TARGETS_TO_BUILD="host;NVPTX" `
-DCMAKE_BUILD_TYPE=Release `
-DLLVM_ENABLE_ASSERTIONS=ON `
-DCLANG_ENABLE_STATIC_ANALYZER=OFF `
-DCLANG_ENABLE_ARCMT=OFF `
-DCLANG_ENABLE_FORMAT=OFF `
-DCLANG_ENABLE_BOOTSTRAP=OFF `
..\llvm
cmake --build . --target clang clang-repl --parallel $env:ncpus
Note the 'llvm-project' directory location. On linux and MacOS you execute the following
cd ../
export LLVM_DIR=$PWD
cd ../
On Windows you execute the following
cd ..\
$env:LLVM_DIR= $PWD.Path
cd ..\
Besides the Clang-REPL interpreter, CppInterOp also works alongside the Cling
interpreter. Cling depends on its own customised version of llvm-project
,
hosted under the root-project
(see the git path below).
Use the following build instructions to build on Linux and MacOS
git clone https://github.com/root-project/cling.git
cd ./cling/
git checkout tags/v1.0
cd ..
git clone --depth=1 -b cling-llvm13 https://github.com/root-project/llvm-project.git
mkdir llvm-project/build
cd llvm-project/build
cmake -DLLVM_ENABLE_PROJECTS=clang \
-DLLVM_EXTERNAL_PROJECTS=cling \
-DLLVM_EXTERNAL_CLING_SOURCE_DIR=../../cling \
-DLLVM_TARGETS_TO_BUILD="host;NVPTX" \
-DCMAKE_BUILD_TYPE=Release \
-DLLVM_ENABLE_ASSERTIONS=ON \
-DLLVM_USE_LINKER=lld \
-DCLANG_ENABLE_STATIC_ANALYZER=OFF \
-DCLANG_ENABLE_ARCMT=OFF \
-DCLANG_ENABLE_FORMAT=OFF \
-DCLANG_ENABLE_BOOTSTRAP=OFF \
../llvm
cmake --build . --target clang --parallel $(nproc --all)
cmake --build . --target cling --parallel $(nproc --all)
cmake --build . --target gtest_main --parallel $(nproc --all)
Use the following build instructions to build on Windows
git clone https://github.com/root-project/cling.git
cd .\cling\
git checkout tags/v1.0
cd ..
git clone --depth=1 -b cling-llvm13 https://github.com/root-project/llvm-project.git
$env:ncpus = %NUMBER_OF_PROCESSORS%
$env:PWD_DIR= $PWD.Path
$env:CLING_DIR="$env:PWD_DIR\cling"
mkdir llvm-project\build
cd llvm-project\build
cmake -DLLVM_ENABLE_PROJECTS=clang `
-DLLVM_EXTERNAL_PROJECTS=cling `
-DLLVM_EXTERNAL_CLING_SOURCE_DIR="$env:CLING_DIR" `
-DLLVM_TARGETS_TO_BUILD="host;NVPTX" `
-DCMAKE_BUILD_TYPE=Release `
-DLLVM_ENABLE_ASSERTIONS=ON `
-DCLANG_ENABLE_STATIC_ANALYZER=OFF `
-DCLANG_ENABLE_ARCMT=OFF `
-DCLANG_ENABLE_FORMAT=OFF `
-DCLANG_ENABLE_BOOTSTRAP=OFF `
../llvm
cmake --build . --target clang --parallel $env:ncpus
cmake --build . --target cling --parallel $env:ncpus
cmake --build . --target gtest_main --parallel $env:ncpus
Note the 'llvm-project' directory location. On linux and MacOS you execute the following
cd ../
export LLVM_DIR=$PWD
cd ../
On Windows you execute the following
cd ..\
$env:LLVM_DIR= $PWD.Path
cd ..\
Regardless of whether you are building CppInterOP with Cling or Clang-REPL you will need to define the following Envirnoment variables (as they clear for a new session, it is recommended that you also add these to your .bashrc in linux, .bash_profile if on MacOS, or profile.ps1 on Windows). On Linux and MacOS you define as follows
export CB_PYTHON_DIR="$PWD/cppyy-backend/python"
export CPPINTEROP_DIR="$CB_PYTHON_DIR/cppyy_backend"
export CPLUS_INCLUDE_PATH="${CPLUS_INCLUDE_PATH}:${LLVM_DIR}/llvm/include:${LLVM_DIR}/clang/include:${LLVM_DIR}/build/include:${LLVM_DIR}/build/tools/clang/include"
export PYTHONPATH=$PYTHONPATH:$CPYCPPYY_DIR:$CB_PYTHON_DIR
If on MacOS you will also need the following envirnoment variable defined
export SDKROOT=`xcrun --show-sdk-path`
On Windows you define as follows (assumes you have defined $env:PWD_DIR= $PWD.Path )
$env:CB_PYTHON_DIR="$env:PWD_DIR\cppyy-backend\python"
$env:CPPINTEROP_DIR="$env:CB_PYTHON_DIR\cppyy_backend"
$env:CPLUS_INCLUDE_PATH="$env:CPLUS_INCLUDE_PATH;$env:LLVM_DIR\llvm\include;$env:LLVM_DIR\clang\include;$env:LLVM_DIR\build\include;$env:LLVM_DIR\build\tools\clang\include"
$env:PYTHONPATH="$env:PYTHONPATH;$env:CPYCPPYY_DIR;$env:CB_PYTHON_DIR"
Now CppInterOp can be installed. On Linux and MacOS execute
mkdir CppInterOp/build/
cd CppInterOp/build/
On Windows execute
mkdir CppInterOp\build\
cd CppInterOp\build\
Now if you want to build CppInterOp with Clang-REPL then execute the following commands on Linux and MacOS
cmake -DBUILD_SHARED_LIBS=ON -DUSE_CLING=Off -DUSE_REPL=ON -DLLVM_DIR=$LLVM_DIR/build/lib/cmake/llvm -DClang_DIR=$LLVM_DIR/build/lib/cmake/clang -DCMAKE_INSTALL_PREFIX=$CPPINTEROP_DIR ..
cmake --build . --target install --parallel $(nproc --all)
and
cmake -DUSE_CLING=Off -DUSE_REPL=ON -DLLVM_DIR=$env:LLVM_DIR\build\lib\cmake\llvm -DClang_DIR=$env:LLVM_DIR\build\lib\cmake\clang -DCMAKE_INSTALL_PREFIX=$env:CPPINTEROP_DIR ..
cmake --build . --target install --parallel $env:ncpus
on Windows. If alternatively you would like to install CppInterOp with Cling then execute the following commands on Linux and MacOS
cmake -DBUILD_SHARED_LIBS=ON -DUSE_CLING=ON -DUSE_REPL=Off -DCling_DIR=$LLVM_DIR/build/tools/cling -DLLVM_DIR=$LLVM_DIR/build/lib/cmake/llvm -DClang_DIR=$LLVM_DIR/build/lib/cmake/clang -DCMAKE_INSTALL_PREFIX=$CPPINTEROP_DIR ..
cmake --build . --target install --parallel $(nproc --all)
and
cmake -DUSE_CLING=ON -DUSE_REPL=Off -DCling_DIR=$env:LLVM_DIR\build\tools\cling -DLLVM_DIR=$env:LLVM_DIR\build\lib\cmake\llvm -DClang_DIR=$env:LLVM_DIR\build\lib\cmake\clang -DCMAKE_INSTALL_PREFIX=$env:CPPINTEROP_DIR ..
cmake --build . --target install --parallel $env:ncpus
To test the built CppInterOp execute the following command in the CppInterOP build folder on Linux and MacOS
cmake --build . --target check-cppinterop --parallel $(nproc --all)
and
cmake --build . --target check-cppinterop --parallel $env:ncpus
on Windows. Now go back to the top level directory in which your building CppInterOP. On Linux and MacOS you do this by executing
cd ../..
and
cd ..\..
on Windows. Now you are in a position to install cppyy following the instructions below.
Cd into the cppyy-backend directory, build it and copy library files into python/cppyy-backend
directory:
cd cppyy-backend
mkdir -p python/cppyy_backend/lib build
cd build
cmake -DCppInterOp_DIR=$CPPINTEROP_DIR ..
cmake --build .
If on a linux system now execute the following command
cp libcppyy-backend.so ../python/cppyy_backend/lib/
and if on MacOS execute the following command
cp libcppyy-backend.dylib ../python/cppyy_backend/lib/
Note go back to the top level build directory
cd ../..
Create virtual environment and activate it:
python3 -m venv .venv
source .venv/bin/activate
git clone --depth=1 https://github.com/compiler-research/CPyCppyy.git
mkdir CPyCppyy/build
cd CPyCppyy/build
cmake ..
cmake --build .
Note down the path to the build
directory as CPYCPPYY_DIR
:
export CPYCPPYY_DIR=$PWD
cd ../..
git clone --depth=1 https://github.com/compiler-research/cppyy.git
cd cppyy
python -m pip install --upgrade . --no-deps
cd ..
Each time you want to run cppyy you need to: Activate the virtual environment
source .venv/bin/activate
Now you can import cppyy
in python
python -c "import cppyy"
Follow the steps in Run cppyy. Change to the test directory, make the library files and run pytest:
cd cppyy/test
make all
python -m pip install pytest
python -m pytest -sv
Further Reading: C++ Language Interoperability Layer