Code generator for serializing/deserializing C++ objects to/from JSON using Clang and RapidJSON

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README.md

Reflective RapidJSON

The main goal of this project is to provide a code generator for serializing/deserializing C++ objects to/from JSON using Clang and RapidJSON.

Extending the generator to generate code for other formats or other applications of reflection is possible as well. A serializer/deserializer for a platform independent binary format has already been implemented.

It would also be possible to extend the library/generator to provide generic reflection (not implemented yet).

The following documentation focuses on the JSON (de)serializer. However, most of it is also true for the mentioned binary (de)serializer which works quite similar.

Open for other reflection approaches

The reflection implementation used behind the scenes of this library is exchangeable:

  • This repository already provides a small, additional header to use RapidJSON with Boost.Hana. This allows to serialize or dezerialize simple data structures declared using the BOOST_HANA_DEFINE_STRUCT macro rather than requiring the code generator.
  • When native reflection becomes standardized, it would be possible to make use of it as well. In this case, the code generator could still act as a fallback.

Current state

The basic functionality is implemented, tested and documented:

  • Serialization and deserialization of datatypes listed under "Supported datatypes"
    • Nesting and inheritance is possible
    • Adapting 3rdparty structs/classes is supported
  • Basic error handling when deserializing
  • CMake macro to conveniently include the code generator into the build process
  • Allow to use Boost.Hana

Planned features and TODOs

There are still things missing which would likely be very useful in practise. The following list contains the open TODOs which are supposed to be most relevant in practise:

  • Allow to specify which member variables should be considered
    • This could work similar to Qt's Signals & Slots macros.
    • But there should also be a way to do this for 3rdparty types.
    • Note that currently all public, non-static member variables are (de)serialized.
  • Support getter/setter methods
    • Allow to serialize the result of methods
    • Allow to pass a deserialized value to a method
  • Validate enum values when deserializing
  • Untie serialization and deserialization

For a full list of further ideas, see TODOs.md.

Supported datatypes

The following table shows the mapping of supported C++ types to supported JSON types:

C++ type JSON type
custom structures/classes object
bool true/false
signed and unsigned integral types number
float and double number
enum and enum class number
std::string string
const char * string
iteratable lists (std::vector, std::list, ...) array
sets (std::set, std::unordered_set, std::multiset, ...) array
std::tuple array
std::unique_ptr, std::shared_ptr depends/null
std::map, std::unordered_map object
JsonSerializable object

Remarks

  • Raw pointer are not supported. This prevents forgetting to free memory which would have to be allocated when deserializing.
  • For the same reason const char * strings are only supported for serialization.
  • Enums are (de)serialized as their underlying integer value. When deserializing, it is currently not checked whether the present integer value is a valid enumeration item.
  • The JSON type for smart pointer depends on the type the pointer refers to. It can also be null.
  • If multiple std::shared_ptr instances point to the same object this object is serialized multiple times. When deserializing those identical objects, it is currently not possible to share the memory (again). So each std::shared_ptr will point to its own copy. Note that this limitation is not present when using binary (de)serialization instead of JSON.
  • For deserialization
    • iteratables must provide an emplace_back method. So deserialization of eg. std::forward_list is currently not supported.
    • custom types must provide a default constructor.
    • constant member variables are skipped.
  • It is possible to treat custom types as set/map using the macro REFLECTIVE_RAPIDJSON_TREAT_AS_MAP_OR_HASH, REFLECTIVE_RAPIDJSON_TREAT_AS_MULTI_MAP_OR_HASH, REFLECTIVE_RAPIDJSON_TREAT_AS_SET or REFLECTIVE_RAPIDJSON_TREAT_AS_MULTI_SET.
  • The key type of std::map and std::unordered_map must be std::string.
  • For custom (de)serialization, see the section below.
  • The binary (de)serializer supports approximately the same C++ types but obviously maps them to a platform independent binary representation rather than a JSON type.

Usage

This example shows how the library can be used to make a struct serializable:

#include <reflective_rapidjson/json/serializable.h>

// define structures, eg. struct TestObject : public ReflectiveRapidJSON::JsonSerializable<TestObject> {

int number;
double number2;
vector&lt;int&gt; numbers;
string text;
bool boolean;

}; struct NestingObject : public ReflectiveRapidJSON::JsonSerializable<NestingObject> {

string name;
TestObject testObj;

}; struct NestingArray : public ReflectiveRapidJSON::JsonSerializable<NestingArray> {

string name;
vector&lt;TestObject&gt; testObjects;

};

// serialize to JSON NestingArray obj{ ... }; cout << "JSON: " << obj.toJson().GetString();

// deserialize from JSON const auto obj = NestingArray::fromJson(...);

// in exactly one of the project's translation units #include "reflection/code-defining-structs.h"

Note that the header included at the bottom must be generated by invoking the code generator appropriately, eg.:

reflective_rapidjson_generator 

--input-file "$srcdir/code-defining-structs.cpp" \
--output-file "$builddir/reflection/code-defining-structs.h"

There are further arguments available, see:

reflective_rapidjson_generator --help

Binary (de)serialization

It works very similar to the example above. Just use the BinarySerializable class instead (or in addition):

#include <reflective_rapidjson/binary/serializable.h>
struct TestObject : public ReflectiveRapidJSON::BinarySerializable<TestObject>

Invoking code generator with CMake macro

It is possible to use the provided CMake macro to automate the code generator invocation:

find the package and make macro available

find_package(reflective-rapidjson REQUIRED) list(APPEND CMAKE_MODULE_PATH ${REFLECTIVE_RAPIDJSON_MODULE_DIRS}) include(ReflectionGenerator)

"link" against reflective_rapidjson

it is a header-only lib so this will only add the required include paths

to your target

target_link_libraries(mytarget PRIVATE reflective_rapidjson)

invoke macro

add_reflection_generator_invocation(

INPUT_FILES code-defining-structs.cpp
GENERATORS json binary
OUTPUT_LISTS LIST_OF_GENERATED_HEADERS
CLANG_OPTIONS_FROM_TARGETS mytarget

)

This will produce the file code-defining-structs.h in the directory reflection in the current build directory. So make sure the current build directory is added to the include directories of your target. The default output directory can also be overridden by passing OUTPUT_DIRECTORY custom/directory to the arguments.

It is possible to specify multiple input files at once. A separate output file is generated for each input. The output files will always have the extension .h, independently of the extension of the input file.

The full paths of the generated files are also appended to the variable LIST_OF_GENERATED_HEADERS which then can be added to the sources of your target. Of course this can be skipped if not required/wanted.

The GENERATORS argument specifies the generators to run. Use json to generate code for JSON (de)serialization and binary to generate code for binary (de)serialization. As shown in the example, multiple generators can be specified at a time.

The macro will also automatically pass Clang's resource directory which is detected by invoking clang -print-resource-dir. To adjust that, just set the cache variable REFLECTION_GENERATOR_CLANG_RESOURCE_DIR before including the module.

For an explanation of the CLANG_OPTIONS_FROM_TARGETS argument, read the next section.

Passing Clang options

It is possible to pass additional options to the Clang tool invocation used by the code generator. This can be done using the --clang-opt argument or the CLANG_OPTIONS argument when using the CMake macro.

For example, additional definitions could be added using --clang-opt -DSOME_DEFINE -DANOTHER_DEFINE. But it is actually possible to pass anything from clang --help, including the -X... options.

Specifying Clang's resource directory

In case you get a massive number of errors, ensure Clang's resource directory can be located. Clang documentation:

The default location to look for builtin headers is in a path $(dirname /path/to/tool)/../lib/clang/3.3/include relative to the tool binary.

To adjust the default location, just add eg. --clang-opt -resource-dir /usr/lib/clang/5.0.1 to the arguments.

Pass options from regular targets

It makes most sense to specify the same options for the code generator as during the actual compilation. This way the code generator uses the same flags, defines and include directories as the compiler and hence behaves like the compiler.
When using the CMake macro, it is possible to automatically pass all compile flags, compile definitions and include directories from certain targets to the code generator. Those targets can be specified using the Macro's CLANG_OPTIONS_FROM_TARGETS argument.

Notes regarding cross-compilation

  • For cross compilation, it is required to build the code generator for the platform you're building on.
  • Since the code generator is likely not required under the target platform, you should add -DNO_GENERATOR:BOOL=ON to the CMake arguments when building Reflective RapidJSON for the target platform.
  • When using the add_reflection_generator_invocation macro, you need to set the following CMake cache variables:
    • REFLECTION_GENERATOR_EXECUTABLE:FILEPATH=/path/to/reflective_rapidjson_generator
      • specifies the path of the code generator executable built for the platform you're building on
      • only required if the executable is not in the path anyways
    • REFLECTION_GENERATOR_TRIPLE:STRING=machine-vendor-operatingsystem
      • specifies the GNU platform triple for the target platform
      • examples for cross compiling with mingw-w64 under GNU/Linux:
        x86_64-w64-mingw32, i686-w64-mingw32
    • REFLECTION_GENERATOR_INCLUDE_DIRECTORIES:STRING=/custom/prefix/include
      • implicit include directories for target platform
      • example for cross compiling with mingw-w64 under GNU/Linux:
        /usr/lib/gcc/x86_64-w64-mingw32/7.2.1/include;/usr/x86_64-w64-mingw32/include/c++/7.2.1/x86_64-w64-mingw32;/usr/x86_64-w64-mingw32/include
  • The Arch Linux packages mentioned at the end of the README file also include mingw-w64 variants which give a concrete example how cross-compilation can be done.

Using Boost.Hana instead of the code generator

The same example as above. However, this time Boost.Hana is used - so it doesn't require invoking the generator.

#include "<reflective_rapidjson/json/serializable-boosthana.h>

// define structures using BOOST_HANA_DEFINE_STRUCT, eg.
struct TestObject : public JsonSerializable<TestObject> {
    BOOST_HANA_DEFINE_STRUCT(TestObject,
        (int, number),
        (double, number2),
        (vector<int>, numbers),
        (string, text),
        (bool, boolean)
    );
};
struct NestingObject : public JsonSerializable<NestingObject> {
    BOOST_HANA_DEFINE_STRUCT(NestingObject,
        (string, name),
        (TestObject, testObj)
    );
};
struct NestingArray : public JsonSerializable<NestingArray> {
    BOOST_HANA_DEFINE_STRUCT(NestingArray,
        (string, name),
        (vector<TestObject>, testObjects)
    );
};

// serialize to JSON
NestingArray obj{ ... };
cout << "JSON: " << obj.toJson().GetString();

// deserialize from JSON
const auto obj = NestingArray::fromJson(...);

So beside the BOOST_HANA_DEFINE_STRUCT macro, the usage remains the same.

Disadvantages

  • Use of ugly macro required
  • No context information for errors like type-mismatch available
  • Inherited members not considered
  • Proper support for enums is unlikely

Enable reflection for 3rd party classes/structs

It is obvious that the previously shown examples do not work for classes defined in 3rd party header files as it requires adding an additional base class.

To work around this issue, one can use the REFLECTIVE_RAPIDJSON_MAKE_JSON_SERIALIZABLE macro. It will enable the toJson and fromJson methods for the specified class in the ReflectiveRapidJSON::JsonReflector namespace:

// somewhere in included header
struct ThridPartyStruct
{ ... };

// somewhere in own header or source file
REFLECTIVE_RAPIDJSON_MAKE_JSON_SERIALIZABLE(ThridPartyStruct)

// (de)serialization
ReflectiveRapidJSON::JsonReflector::toJson(...).GetString();
ReflectiveRapidJSON::JsonReflector::fromJson<ThridPartyStruct>("...");

The code generator will emit the code in the same way as if JsonSerializable was used.

By the way, the functions in the ReflectiveRapidJSON::JsonReflector namespace can also be used when inheriting from JsonSerializable (instead of the member functions).

(De)serializing private members

By default, private members are not considered for (de)serialization. However, it is possible to enable this by adding friend methods for the helper functions of Reflective RapidJSON.

To make things easier, there's a macro provided:

struct SomeStruct : public JsonSerializable<SomeStruct> {

REFLECTIVE_RAPIDJSON_ENABLE_PRIVATE_MEMBERS(SomeStruct);

public:

std::string publicMember = "will be (de)serialized anyways";

private:

std::string privateMember = "will be (de)serialized with the help of REFLECTIVE_RAPIDJSON_ENABLE_PRIVATE_MEMBERS macro";

};

Caveats

  • It will obviously not work for 3rd party structs.
  • This way to allow (de)serialization of private members must be applied when using Boost.Hana and there are any private members present. The reason is that accessing the private members can currently not prevented when using Boost.Hana.

Custom (de)serialization

Sometimes it is appropriate to implement custom (de)serialization. For instance, a custom object representing a time value should likey be serialized as a string rather than an object containing the internal structure.

An example for such custom (de)serialization can be found in the file json/reflector-chronoutilities.h. It provides (de)serialization of DateTime and TimeSpan objects from the C++ utilities library mentioned under dependencies.

Remarks

  • Static member variables and member functions are currently ignored by the generator.
  • It is currently not possible to ignore a specific member variable.

Further examples

  • Checkout the test cases for further examples. Relevant files are in the directories lib/tests and generator/tests.
  • There's also my tag editor, which uses Reflective RapidJSON to provide a JSON export. See json.h and mainfeatures.cpp#exportToJson.

Architecture

The following diagram gives an overview about the architecture of the code generator and wrapper library around RapidJSON:

Architectue overview

  • blue: classes from LibTooling/Clang
  • grey: conceivable extension or use

Install instructions

Dependencies

The following dependencies are required at build time. Note that Reflective RapidJSON itself and none of these dependencies are required at runtime by an application which makes use of Reflective RapidJSON.

  • C++ compiler and C++ standard library supporting at least C++14
  • the CMake build system
  • LibTooling from Clang for the code generator (optional when using Boost.Hana)
  • RapidJSON for JSON (de)serialization
  • C++ utilities for various helper functions

Optional

  • Boost.Hana for using BOOST_HANA_DEFINE_STRUCT instead of code generator
  • CppUnit for building and running the tests
  • Doxygen for generating API documentation
  • Graphviz for diagrams in the API documentation

Remarks

  • It is not required to use CMake as build system for your own project. However, when using a different build system, there is no helper for adding the code generator to the build process provided (so far).
  • I usually develop using the latest version of those dependencies. So it is recommend to get the the latest versions as well. I tested the following versions so far:
    • GCC 7.2.1/7.3.0/8.1.0/9.1.0 or Clang 5.0/6.0/7.0/8.0 as compiler
    • libstdc++ from GCC 7.2.1/7.3.0/8.1.0/9.1.0
    • CMake 3.10.x to 3.15.x
    • Clang 5.x/6.x/7.x/8.x/9.x for LibTooling
    • RapidJSON 1.1.0
    • C++ utilities 5.0.0
    • Boost.Hana 1.65.1, 1.66.0, 1.67.0, 1.68.0, 1.69.0
    • CppUnit 1.14.0
    • Doxygen 1.8.13 to 1.8.16
    • Graphviz 2.40.1
  • The binary (de)serializer requires C++ utilities at runtime. So when using it, it is required to link against C++ utilities.

How to build

1. Install dependencies

Install all required dependencies. Under a typical GNU/Linux system most of these dependencies can be installed via the package manager. Otherwise follow the links in the "Dependencies" section above.

C++ utilities is likely not available as package. However, it is possible to build C++ utilities together with reflective-rapidjson to simplify the build process. The following build script makes use of this. (To use system C++ utilities, just skip any lines with "c++utilities" in the following examples.)

2. Make dependencies available

When installing (some) of the dependencies at custom locations, it is likely neccassary to tell CMake where to find them. If you installed everything using packages provided by the system, you can skip this step of course.

To specify custom locations, just set some environment variables before invoking CMake. This can likely be done in your IDE settings and of course at command line. Here is a Bash example:

export PATH=$CUSTOM_INSTALL_PREFIX/bin:$PATH
export CMAKE_PREFIX_PATH=$CUSTOM_INSTALL_PREFIX:$CMAKE_PREFIX_PATH
export CMAKE_LIBRARY_PATH=$CUSTOM_INSTALL_PREFIX/lib:$CMAKE_LIBRARY_PATH
export CMAKE_INCLUDE_PATH=$CUSTOM_INSTALL_PREFIX/include:$CMAKE_INCLUDE_PATH

There are also a lot of useful variables that can be specified as CMake arguments. It is also possible to create a toolchain file.

3. Get sources, eg. using Git:

cd $SOURCES
git clone https://github.com/Martchus/cpp-utilities.git c++utilities
git clone https://github.com/Martchus/reflective-rapidjson.git

If you don't want to build the development version, just checkout the desired version tag.

4. Run the build script

Here is an example for building with GNU Make:

cd $BUILD_DIR

generate Makefile

cmake \ -DCMAKE_BUILD_TYPE:STRING=Release \ -DCMAKE_INSTALL_PREFIX:PATH="/final/install/prefix" \ -DBUNDLED_CPP_UTILITIES_PATH:PATH="$SOURCES/c++utilities" \ "$SOURCES/reflective-rapidjson"

build library and generators

make

build and run tests (optional, requires CppUnit)

make check

build tests but do not run them (optional, requires CppUnit)

make tests

generate API documentation (optional, reqquires Doxygen)

make apidoc

install header files, libraries and generator

make install DESTDIR="/temporary/install/location"

Add eg. -j$(nproc) to make arguments for using all cores.

Packages

These packages shows the required dependencies and commands to build in a plain way. So they might be useful for making Reflective RapidJSON available under other platforms, too.