A library for C++ reflection and introspection
All reflection metadata is processed by DRLParser, a python script that takes input about a proejct (Compilation options, include dirs, etc) and scans the project headers, generating C++ header files with the reflection information of the corresponding input header. All generated code is C++11 compatible.
Users should not worry about DRLParser and its input, a set of cmake
scripts is given to simplify reflection in user projects. Just include
siplasplas.cmake and invoke configure_siplasplas_reflection() with your target:
add_library(MyLibrary myLib.cpp)
target_include_directories(MyLibrary PUBLIC include/)
target_compile_options(MyLibrary PRIVATE -std=c++11 -Wall)
configure_siplasplas_reflection(MyLibrary)This will add a custom pre-build target that automatically runs DRLParser and generates reflection metadata headers before building your library.
SIplasplas provides a template-based API to access to static reflection information of user defined types:
// particle.hpp
class Particle
{
public:
struct Position
{
float x, y, z;
};
struct Color
{
float a, r, g, b;
};
enum class State
{
Alive,
Dead
};
Position position;
Color color;
State state;
};siplasplas uses a libclang based script to generate C++ code with all the metadata. After running this script, include both the user header and the generated header:
#include <particle.hpp>
#include <reflection/particle.hpp> // Reflection data (generated code)
std::vector<Particle> particles;
std::ostream& operator<<(std::ostream& os, const Particle::Position& position)
{
using PositionClass = cpp::static_reflection::Class<Particle::Position>;
os << "{";
// For each coordinate in the Position class...
cpp::foreach_type<PositionClass::Fields>([&](auto type)
{
using Field = cpp::meta::type_t<decltype(type)>;
os << Field::spelling() << ": " // Field name ("x", "y", "z")
<< cpp::invoke(Field::get(), position) // Field value (Like C++17 invoke with member object ptr)
<< " ";
});
return os << "}";
}
std::ostream& operator<<(std::ostream& os, const Particle::Color& color)
{
using ColorClass = cpp::static_reflection::Class<Particle::Color>;
os << "{";
// For each channel in the Color class...
cpp::foreach_type<ColorClass::Fields>([&](auto type)
{
using Field = cpp::meta::type_t<decltype(type)>;
os << Field::spelling() << ": " // channel name (r, g, b, ...)
<< cpp::invoke(Field::get(), color)*255 // channel value
<< " ";
});
return os << "}";
}
std::ostream& operator<<(std::ostream& os, const Particle::State& state)
{
// Use static reflection to get the name of the enum value:
return os << cpp::static_reflection::Enum<Particle::State>::toString(state);
}
int main()
{
for(const auto& particle : particles)
{
std::cout << "position: " << particle.position << std::endl;
std::cout << "color: " << particle.color << std::endl;
std::cout << "state: " << particle.state << std::endl;
}
}The static reflection API currently supports:
- User defined class types: Source information, set of public non-static member objects and functions, member types.
- User defined enumeration types: Set of enum constants values, enum constants names, to/from string methods
- User defined functions
Siplasplas also supports dynamic reflection in the form of a simple entity based component system:
cpp::dynamic_reflection::Runtime runtime = loadDynamicReflection();
// Get dynamic reflection info of the class ::Particle::Position:
cpp::dynamic_reflection::Class& positionClass = runtime.class_("Particle").class_("Position");
// Manipulate a particle object using dynamic reflection:
Particle particle;
positionCLass.field_("x").get(particle.position) = 42.0f; // particle.position.x = 42
// You can also create objects dynamically:
auto particle2 = runtime.class_("Particle").create();
// Returned objects are dynamically manipulable too:
particle2["color"]["r"] = 0.5f;The dynamic reflection API can be used to load APIs from external libraries at runtime in a straightforward way:
int main()
{
cpp::DynamicLibrary lib{"libmylibrary.so"};
cpp::dynamic_reflection::Runtimeloader loader{lib};
cpp::dynamic_reflection::Runtime& runtime = loader.runtime();
auto myObject = runtime.class_("MyClass").create();
// Invoke MyClass::function with params 1 and "hello":
myObject("function")(1, std::string("hello!"));
}Siplasplas offers other features, building blocks for the APIs explained above, including:
-
Type erasure: A module dedicated to type erasure, with classes designed to manipulate type erased functions, member object pointers, and objects.
-
Signals: Siplasplas implements a simple message passing system for inter-thread communication.
-
CMake API: With the ultimate goal of providing the basis for a work in progress runtime C++ compilation module, siplasplas implements a C++ API to configure and build existing CMake projects.
-
Utilities: Dynamic library loading, aligned malloc, assertions, function type introspection, metaprogramming, hashing, etc. Lots of stuff!
siplasplas has been tested in GCC 5.1/5.2/6.1, Clang 3.6/3.7/3.8, and Visual Studio 2015.
Documentation is available here
The documentation is available in Doxygen and Standardese format, each one with multiple versions corresponding to the latest documentation of each siplasplas release and active branch.
NOTE: siplasplas is a work in progress project subject to changes. We don't currently provide any kind of API or ABI stability guarantee, nor a production-ready installation process. The following instructions are to build siplasplas from sources.
You can build siplasplas from sources:
$ git clone https://github.com/Manu343726/siplasplas --recursive
$ cd siplasplas
$ mkdir build
$ cd build
$ cmake ..
$ cmake --build .Or download the bootstrap cmake script
and point it to one of the siplasplas releases:
set(SIPLASPLAS_PACKAGE_URL <url to siplasplas release package>)
set(SIPLASPLAS_INSTALL_DRLPARSER_DEPENDENCIES ON) # Download DRLparser deps with pip
set(SIPLASPLAS_LIBCLANG_VERSION 3.8.0) # libclang version
set(SIPLASPLAS_DOWNLOAD_LIBCLANG ON) # Download and configure libclang automatically
include(bootstrap.cmake)This will download and configure a siplasplas installation in your buildtree. After including
bootstrap.cmake, a FindSiplasplas.cmake module is available in your module path to link against
the different siplasplas modules:
find_package(Siplasplas)
target_link_libraries(MyLibrary PUBLIC siplasplas-reflection-dynamic)The module defines one imported library for each siplasplas module. All inter-module dependencies are already solved.
-
Python 2.7: The siplasplas relfection engine uses a libclang-based parser witten in python. Python 2.7 and pip for Python 2.7 are neccesary. All dependencies are handled automatically (Seeconfiguration bellow).
-
Mercurial: The Entropia Filesystem Watcher dependency is hosted on bitbucket using Mercurial for source control. Mercurial is needed to download the dependency.
-
Doxygen: Needed only if documentation build is enabled. See configuration bellow.
-
Libclang: Siplasplas will use the libclang library distributed as part of the system clang installation by default, but it can be configured to download and build libclang automatically. See configuration.
All siplasplas dependencies are managed automatically through CMake, users don't have to worry about installing deps. Anyway, here is the list of the thrid party dependencies of siplasplas:
- backward-cpp for exception stack traces
- chaiscript (For examples only)
- cmake tools for the cmake scripts
- ctti for type indexing and debugging
- efsw for runtime C++ compilation
- fmt for diagnostic messages
- googletest (For tests only)
- imgui (For examples only)
- SFML (For examples only)
- JSON For Modern C++ for cmake target properties and serialization
- libexecstream for cmake invocation
- readerwriterqueue for inter-thread message passing
- spdlog for logging
- standardese (For documentation only)
siplasplas also depends on some python modules:
- clang for C++ parsing
- colorama for parser logging
- asciitree for AST debugging
- jinja2 for code generation
Clone the siplasplas repository
$ git clone https://github.com/Manu343726/siplasplas --recursiveCreate a build/ directory inside the local repository
$ cd siplasplas
$ mkdir buildRun cmake in the build directory
$ cd build
$ cmake ..Make sure you installed all the requirements before running cmake, siplasplas configuration may fail if one or more of that requirements is missing.
To build the library, invoke the default build target:
$ cmake --build . # Or just "make" if using Makefiles generatorThe default cmake invocation will build siplasplas as dynamic libraries (one per module) using the default generator. Also, siplasplas configuration can be modified using some options and variables:
The syntax to pass variables to cmake during configuration is
-D<VARIABLE>=<VALUE>, for example:
$ cmake .. -DSIPLASPLAS_VERBOSE_CONFIG=ON
-
CMAKE_BUILD_TYPE: Build type to be used to build the project (Debug, Release, etc). Set toDebugby default. -
SIPLASPLAS_VERBOSE_CONFIG: Configure siplasplas using detailed output.OFFby default. -
SIPLASPLAS_LIBRARIES_STATIC: Build static libraries.FALSEby default. -
SIPLASPLAS_BUILD_EXAMPLES: Build siplasplas examples in addition to libraries.OFFby default. -
SIPLASPLAS_BUILD_TESTS: Build siplasplas unit tests.OFFby default. -
SIPLASPLAS_BUILD_DOCS: Generate targets to build siplasplas documentation.OFFby default. -
SIPLASPLAS_INSTALL_DRLPARSER_DEPENDENCIES: Install reflection parser python dependencies.ONby default. This needs pip version 2.7 installled. Dependencies can be manually installed too, there's is arequirements.txtfile in<siplasplas sources>/src/reflection/parser/. The requirements file doesn't cover theclangdependency, you must install the clang package with the same version of your installed libclang. For example, given:$ clang --version clang version 3.8.0 (tags/RELEASE_380/final) ...
you must install
clang==3.8.0package for Python 2.7. -
SIPLASPLAS_DOWNLOAD_LIBCLANG: Download libclang from LLVM repository. If enabled, siplasplas will download LLVM+Clang version${SIPLASPLAS_LIBCLANG_VERSION}from the LLVM repositories. This overridesSIPLASPLAS_LIBCLANG_INCLUDE_DIR,SIPLASPLAS_LIBCLANG_SYSTEM_INCLUDE_DIR, andSIPLASPLAS_LIBCLANG_LIBRARYvariables.OFFby default. -
SIPLASPLAS_LIBCLANG_VERSION: Version of libclang used by the reflection parser. Inferred from the installed clang version by default.NOTE: siplasplas has been tested with libclang 3.7 and 3.8 only. siplasplas sources use C++14 features, a clang version with C++14 support is needed. Actually, the siplasplas configuration uses
-std=c++14option, which limits the range of supported versions. -
SIPLASPLAS_LIBCLANG_INCLUDE_DIR: Path to the LLVM includes. When building docs, Standardese tool is built using this configuraton too. Inferred by default. -
SIPLASPLAS_LIBCLANG_SYSTEM_INCLUDE_DIR: Path to the installed clang includes. When building docs, Standardese tool is built using this configuraton too. Inferred by default. -
SIPLASPLAS_LIBCLANG_LIBRARY: Path to the libclang library. When building docs, Standardese tool is built using this configuraton too. Inferred by default.
Many thanks to:
- Jonathan "foonathan" Müller, as always
- George "Concepticide" Makrydakis, for feedback, debates, and "Guys, what the fuck is gitter?"
- Diego Rodriguez Losada, for feedback, palmeritas, and blue boxes
- Asier González, for holding on for six months in my C++ course, which eventually became this project
- To all my ByThech WM&IP team mates, for having to suffer me saying "this with reflection would be so easy!" every single day, and specifically to Javier Martín and Antonio Pérez for feedback
- All my twitter followers, still there even with docens of tweets a day about reflection! Seriously, some of the best people of the C++ community are there and give me a lot of feedback and ideas
- Jens Weller and the Fortune God, thanks for accepting my Meeting C++ 2016 talk about siplasplas
siplasplas project is released under the MIT open source license. This license applies to all C++ sources, CMake scripts, and any other file except explicitly stated.
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