Checkout actual repository here: https://github.com/Stiffstream/json_dto
json_dto library is a small header-only helper for converting data between json representation and c++ structs. DTO here stands for data transfer object. It was made and used as a part of a larger project inside Stiffstream.. And since Fall 2016 is ready for public. We are still using it for working with JSON in various projects.
Git repository is a mirror for bitbucket repo: bitbucket.org/sobjectizerteam/json_dto-0.2
A full commit history and version changes can be viewed there.
To use json_dto it is necessary to have:
- C++14 compiler (VC++14.0, GCC 5.2 or above, clang 3.6 or above)
- rapidjson
And for building with mxxru:
- rapidjson_mxxru (v.1.0.0 or above)
- Mxx_ru 1.6.13 or above
And for running test:
- CATCH 1.10.0
Assuming that Mercurial, Git and Mxx_ru are already installed.
git clone https://github.com/ngrodzitski/json_dto.git
And then:
cd json_dto
mxxruexternals
to download and extract json_dto's dependencies.
For json_dto itself:
MxxRu::arch_externals :json_dto do |e|
e.url 'https://bitbucket.org/sobjectizerteam/json_dto-0.1/get/v.0.1.2.tar.bz2'
e.map_dir 'dev/json_dto' => 'dev'
end
For rapidjson and rapidjson_mxxru dependencies:
MxxRu::arch_externals :rapidjson do |e|
e.url 'https://github.com/miloyip/rapidjson/archive/v1.1.0.zip'
e.map_dir 'include/rapidjson' => 'dev/rapidjson/include'
end
MxxRu::arch_externals :rapidjson_mxxru do |e|
e.url 'https://bitbucket.org/sobjectizerteam/rapidjson_mxxru-1.0/get/v.1.0.0.tar.bz2'
e.map_dir 'dev/rapidjson_mxxru' => 'dev'
end
While json_dto is header-only library test and samples require a build.
Compiling with Mxx_ru:
git clone https://github.com/ngrodzitski/json_dto.git
cd json_dto
mxxruexternals
cd dev
ruby build.rb
NOTE. It might be necessary to set up MXX_RU_CPP_TOOLSET
environment variable,
see Mxxx_ru documentation for further details.
To start using json_dto simply include <json_dto/pub.hpp>
header.
The usage principle of json_dto is borrowed from Boost serialization where rapidjson::Value plays the role of archive.
Let's assume we have a c++ structure that must be serialized to JSON and deserialized from JSON:
struct message_t
{
std::string m_from;
std::int64_t m_when;
std::string m_text;
};
For integrating this struct with json_dto facilities the struct must be modified as follows:
struct message_t
{
std::string m_from;
std::int64_t m_when;
std::string m_text;
// Entry point for json_dto.
template < typename JSON_IO >
void
json_io( JSON_IO & io )
{
io
& json_dto::mandatory( "from", m_from )
& json_dto::mandatory( "when", m_when )
& json_dto::mandatory( "text", m_text );
}
};
Here json_io()
function is an entry point for json_dto library.
It describes how to read the data from rapidjson::Value
(that is usualy parsed from string) and how to set the data
in rapidjson::Value.
json_io()
is a template function. It allows to have a single
description for read and write operations.
The template is instantiated with JSON_IO=json_dto::json_input_t
for reading dto from JSON-value and JSON_IO=json_dto::json_output_t
for writing
dto to JSON-value. Both json_dto::json_input_t
and json_dto::json_output_t
override operator&
for splitting io functionality.
There are also iostream-like overrides for operator<<
and operator>>
:
template < typename Dto >
json_input_t &
operator >> ( json_input_t & i, Dto & v );
template < typename Dto >
inline json_output_t &
operator << ( json_output_t & o, const Dto & v );
But they are only helpful for top level read/write operations.
In general json_dto gets data from rapidjson::Value
and puts
the data into rapidjson::Value
. So read/write operations look like this:
// Read
rapidjson::Document document;
// ...
json_dto::json_input_t jin{ document };
message_t msg;
jin >> msg;
// If no exceptions were thrown DTO contains data received from JSON.
// Write
rapidjson::Document document;
// ...
json_dto::json_output_t jout{ document, document.GetAllocator() };
const message_t msg = get_message();
jout << msg;
// If no exceptions were thrown document contains data received from DTO.
But usually it is enough to work with std::string
objects, so json_dto
comes with handy to/from string helpers:
template < typename Dto >
std::string
to_json( const Dto & dto );
template < typename Type >
Type
from_json( const std::string & json );
See full example without to/from string helpers.
When it is unwanted to add an extra function to C++ structure
it is possible to use a non intrusive json_io()
version.
In previous example dto part will look like this:
struct message_t
{
std::string m_from;
std::int64_t m_when;
std::string m_text;
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, message_t & msg )
{
io
& json_dto::mandatory( "from", msg.m_from )
& json_dto::mandatory( "when", msg.m_when )
& json_dto::mandatory( "text", msg.m_text );
}
} /* namespace json_dto */
Note that it is necessary to define json_io()
in namespace json_dto
.
Out of the box json_dto lib supports following types:
- Bool: bool;
- Numeric: std::int16_t, std::uint16_t, std::int32_t, std::uint32_t, std::int64_t, std::uint64_t, double;
- Strings: std::string.
- C++17 specific: std::optional (or std::experimental::optional)
Example:
struct supported_types_t
{
bool m_bool{ false };
std::int16_t m_int16{};
std::uint16_t m_uint16{};
std::int32_t m_int32{};
std::uint32_t m_uint32{};
std::int64_t m_int64{};
std::uint64_t m_uint64{};
double m_double{};
std::string m_string{};
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, supported_types_t & obj )
{
io
& json_dto::mandatory( "bool", obj.m_bool )
& json_dto::mandatory( "int16", obj.m_int16 )
& json_dto::mandatory( "uint16", obj.m_uint16 )
& json_dto::mandatory( "int32", obj.m_int32 )
& json_dto::mandatory( "uint32", obj.m_uint32 )
& json_dto::mandatory( "int64", obj.m_int64 )
& json_dto::mandatory( "uint64", obj.m_uint64 )
& json_dto::mandatory( "double", obj.m_double )
& json_dto::mandatory( "string", obj.m_string );
}
} /* namespace json_dto */
Each data member (at least those of them which are considered to be present in JSON) in C++ struct binds to JSON field. Bind can be mandatory or optional. Optional bind is extended with default value, but it is also possible to set optional fields without defaults. Also it is possible to add a value validator to the bind.
Binds are created by mandatory()
, optional()
and
optional_no_default()
functions. These functions returns a field binder.
Binder is an instantiation of binder_t
template class
which carries a part of internal logic
capable for handling field input/output operations.
With the help of binders JSON_IO
object understands how read, write and validate
the underlying field.
Binders for mandatory fields are created via mandatory()
function:
template <
typename Field_Type,
typename Validator = empty_validator_t>
auto mandatory(
string_ref_t field_name,
Field_Type & field,
Validator validator = Validator{} );
First parameter field_name is of type string_ref_t
which is an alias for rapidjson::Value::StringRefType
.
Typically it is enough to pass std::string
or char *
args
(see rapidjson
documentation
for further details).
The second parameter is a reference to the instance of the field value.
The third parameter is optional and it sets validator on fields value.
Validators will be described later. By default empty_validator_t
is used, and as it says it does nothing.
Binders for optional fields are created via optional()
and
optional_no_default()
functions:
template <
typename Field_Type,
typename Field_Default_Value_Type,
typename Validator = empty_validator_t>
auto optional(
string_ref_t field_name,
Field_Type & field,
Field_Default_Value_Type default_value,
Validator validator = Validator{} );
template <
typename Field_Type,
typename Validator = empty_validator_t >
auto optional_no_default(
string_ref_t field_name,
Field_Type & field,
Validator validator = Validator{} );
Parameters for functions are pretty much the same as for
mandatory()
functon.
The only difference is the third parameter for optional()
function,
it defines default value for a field if it is not defined in JSON.
In case of reading DTO, if optional field has default value and JSON object doesn't define this field then default value is used. In case of writing DTO, if value equals to default then this field wouldn't be included in JSON.
For optional()
there is a partial specification that accepts
nullptr
argument as default_value parameter, it is usefull for
nullable_t<T>
fields.
Example of using optional fields:
struct message_t
{
std::string m_from;
std::int64_t m_when;
std::string m_text;
std::string m_text_format;
bool m_is_private{ false };
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, message_t & msg )
{
io
& json_dto::mandatory( "from", msg.m_from )
& json_dto::mandatory( "when", msg.m_when )
& json_dto::mandatory( "text", msg.m_text )
& json_dto::optional( "text_format", msg.m_text_format, "text/plain" )
& json_dto::optional_no_default( "is_private", msg.m_is_private );
}
} /* namespace json_dto */
Since v.0.2 it is possible to use C++17's std::optional
template as a type
for field. In this case std::nullopt
can be passed as third argument to
json_dto::optional()
function:
struct email_data_t
{
std::string m_from;
std::string m_to;
std::string m_subject;
std::optional< std::vector< std::string > > m_cc;
std::optional< std::vector< std::string > > m_bcc;
...
template<typename Json_Io>
void json_io(Json_Io & io)
{
io & json_dto::mandatory("from", m_from)
& json_dto::mandatory("to", m_to)
& json_dto::mandatory("subject", m_subject)
& json_dto::optional("cc", m_cc, std::nullopt)
& json_dto::optional("bcc", m_bcc, std::nullopt)
...
}
};
Note. If a compiler doesn't have std::optional
but have
std::experimental::optional
then std::experimental::optional
and
std::experimental::nullopt
can be used.
JSON arrays are supported by json_dto, but there is one very important
limitation: all elements of the array must have the same type.
To set up an array simply use std::vector<T>
.
If DTO member is of std::vector<T>
type,
then corresponding JSON field is considered to be an array.
While for output the elements of the array-field will be automatically
of the same type, for successful input it is mandatory
that all elements of the array are convertible to vector value type.
Example for array-fields:
struct vector_types_t
{
std::vector< bool > m_bool{};
std::vector< std::int16_t > m_int16{};
std::vector< std::uint16_t > m_uint16{};
std::vector< std::int32_t > m_int32{};
std::vector< std::uint32_t > m_uint32{};
std::vector< std::int64_t > m_int64{};
std::vector< std::uint64_t > m_uint64{};
std::vector< double > m_double{};
std::vector< std::string > m_string{};
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, vector_types_t & obj )
{
io
& json_dto::mandatory( "bool", obj.m_bool )
& json_dto::mandatory( "int16", obj.m_int16 )
& json_dto::mandatory( "uint16", obj.m_uint16 )
& json_dto::mandatory( "int32", obj.m_int32 )
& json_dto::mandatory( "uint32", obj.m_uint32 )
& json_dto::mandatory( "int64", obj.m_int64 )
& json_dto::mandatory( "uint64", obj.m_uint64 )
& json_dto::mandatory( "double", obj.m_double )
& json_dto::mandatory( "string", obj.m_string );
}
} /* namespace json_dto */
To support JSON null values, json_dto introduces nullable_t<T>
.
It is required that nullable field is explicitly defined as
data member of type nullable_t<T>
.
Interface of nullable_t<T>
tries to mimic std::optional
interface.
Example for nullable_t<T>
field:
struct message_t
{
message_t() {}
message_t(
std::string from,
std::int64_t when,
std::string text )
: m_from{ std::move( from ) }
, m_when{ when }
, m_text{ std::move( text ) }
{}
std::string m_from;
std::int64_t m_when;
std::string m_text;
// Log level.
// By default is constructed with null value.
json_dto::nullable_t< std::int32_t > m_log_level{};
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, message_t & msg )
{
io
& json_dto::mandatory( "from", msg.m_from )
& json_dto::mandatory( "when", msg.m_when )
& json_dto::mandatory( "text", msg.m_text )
& json_dto::optional( "log_level", msg.m_log_level, nullptr );
}
} /* namespace json_dto */
void
some_function( ... )
{
// ...
auto msg = json_dto::from_json< message_t >( json_data );
// ...
// If field is defined then its value can be obtained and used.
if( msg.m_log_level )
use_value( *msg.m_log_level );
// ...
msg.m_log_level = 1; // Set new value.
// ...
// equivalent to msg.m_log_level.reset();
msg.m_log_level = nullptr; // Reset value.
// ...
}
Here default value for optional nullble field is nullptr
.
And it means that absence of value is a default state for a field.
So when converting to JSON no-value nullable field
wouldn't be included in JSON as "field":null
piece.
Nullable fields can be used with arrays:
struct message_t
{
message_t() {}
message_t(
std::string from,
std::int64_t when,
std::string text )
: m_from{ std::move( from ) }
, m_when{ when }
, m_text{ std::move( text ) }
{}
// Who sent a message.
std::string m_from;
// When the message was sent (unixtime).
std::int64_t m_when;
// Message text.
std::string m_text;
// Log level.
// By default is constructed with null value.
json_dto::nullable_t< std::int32_t > m_log_level{};
json_dto::nullable_t< std::vector< std::string > > m_tags{};
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, message_t & msg )
{
io
& json_dto::mandatory( "from", msg.m_from )
& json_dto::mandatory( "when", msg.m_when )
& json_dto::mandatory( "text", msg.m_text )
& json_dto::optional( "log_level", msg.m_log_level, nullptr )
& json_dto::optional( "tags", msg.m_tags, nullptr );
}
} /* namespace json_dto */
void some_function( ... )
{
// ...
auto msg = json_dto::from_json< message_t >( json_data );
// ...
if( msg.m_tags )
use_tags( *msg.m_tags );
// ...
}
void some_other_function( ... )
{
message_t msg{ ... };
// ...
// Add tags:
msg.m_tags.emplace(); // equivalent to msg = std::vector< std::string >{};
msg.m_tags->emplace_back( "sample" );
msg.m_tags->emplace_back( "tutorial" );
// ...
}
json_dto allows to construct complex types with nested objects. Using nested objects is pretty much the same as using data of a simple types. Nested objects can be optional, nullable and be elements of array-fields. However there are some constraints:
- nested type must be itself integrated with json_dto;
- type must be default-constructible (for input);
- for optional fields with default value equality operator must be defined (more precisely an equality operator between nested type and type of p[assed default value).
Suppose there is a type which is already integrated with json_dto:
struct message_source_t
{
std::int32_t m_thread_id{ 0 };
std::string m_subsystem{};
template < typename Json_Io >
void json_io( Json_Io & io )
{
io
& json_dto::optional( "thread_id", m_thread_id, 0 )
& json_dto::mandatory( "subsystem", m_subsystem );
}
};
Then it can be used as a nested object in other type:
struct message_t
{
message_source_t m_from;
std::int64_t m_when;
std::string m_text;
template < typename Json_Io >
void json_io( Json_Io & io )
{
io
& json_dto::mandatory( "from", m_from ) // Exactly as with simple types.
& json_dto::mandatory( "when", m_when )
& json_dto::mandatory( "text", m_text );
}
};
And See full example using nested objects as nullable and arrays
json_dto works well with inheritance. It is possible to use
base implementation of json_io()
function or completely override it.
For example derived class can use base class like this:
struct derived_t : public base_t
{
//...
template < typename Json_Io >
void json_io( Json_Io & io )
{
base_t::json_io( io ); // Run io on base class.
// Run io on extra data:
io
& json_dto::mandatory( "some_field", m_some_field )
// ...
;
}
};
However for easier maintenance it is recommended to use non intrusive
json_io()
function. Because if base class is integrated with json_dto
in non intrusive manner, then the following wouldn't work:
template < typename Json_Io >
void
json_io( Json_Io & io )
{
// Base class doesn't provide such member function.
base_t::json_io( io ); // Run io on base class.
// ...
}
So it is preferred to put inheritance this way:
struct message_source_t
{
std::int32_t m_thread_id{ 0 };
std::string m_subsystem{};
};
namespace json_dto
{
template < typename Json_Io >
void json_io( Json_Io & io, message_source_t & m )
{
io
& json_dto::optional( "thread_id", m.m_thread_id, 0 )
& json_dto::mandatory( "subsystem", m.m_subsystem );
}
} /* namespace json_dto */
struct message_t : public message_source_t
{
std::int64_t m_when;
std::string m_text;
template < typename Json_Io >
void json_io( Json_Io & io )
{
json_dto::json_io( io, static_cast< message_source_t & >( *this ) );
io
& json_dto::mandatory( "when", m_when )
& json_dto::mandatory( "text", m_text );
}
};
json_dto allows to set validator on each field.
Validator is a function object (an object of a type supporting an
operator()
member function) that receives a single parameter.
When handling input json_dto calls specified validator
and passes resulting field value as an argument.
If validator returns without throwing exception,
then field value considered to be valid, and execution continues.
Otherwise exception is catched and another will be thrown:
json_dto::ex_t
. This exeption contains original exception description
supplemented with field name information.
When handling ouput json_dto calls specified validator before trying to assign field value of JSON object. In all other respects validation is the same as for input.
A simple example of using validators:
void
check_all_7bit(
const std::string & text )
{
auto it =
std::find_if(
std::begin( text ),
std::end( text ),
[]( char c ){ return c & 0x80; } );
if( std::end( text ) != it )
{
throw std::runtime_error{
"non 7bit char at pos " +
std::to_string( std::distance( std::begin( text ), it ) ) };
}
}
struct message_t
{
std::string m_from;
std::int64_t m_when;
// Message text. Must be 7bit ascii.
std::string m_text;
template < typename Json_Io >
void json_io( Json_Io & io )
{
io
& json_dto::mandatory( "from", m_from )
& json_dto::mandatory( "when", m_when )
& json_dto::mandatory( "text", m_text, check_all_7bit );
}
};
json_dto comes with some useful ready to use validators for simple types.
They are defined in <json_dto/pub.hpp>
header.
Standard validators curently available:
min_max_constraint_t< Num >
- range validator, targeted for numeric types;one_of_validator_t< T >
- validator for set of values.
Standard validators are template classes with overloaded operator()
.
And as they are template classes so for convenience
for each validator there is an auxiliary function that helps deduce
type of template instance from arguments:
template < typename Number >
auto min_max_constraint( Number min_value, Number max_value );
template < typename Field_Type >
auto one_of_constraint( std::initializer_list< Field_Type > values );
See full example with standard validators
It is possible to define custom IO logic for a specific type. It might be useful for types when using object is an overkill, for example time point that can be stored in format of 'YYYY.MM.DD hh:mm:ss' or some token composed of several small items like '--'.
There are two way to introduce custom IO logic.
The first way uses C++'s Argument Dependent Lookup feature:
an user should define read_json_value
and write_json_value
in the same
namespace where types are defined. The right implementations of
read_json_value
and write_json_value
will be found by C++ compiler automatically.
For example:
namespace importance_levels
{
enum class level_t
{
low,
normal,
high
};
// read_json_value and write_json_value for level_t are
// defined in importance_levels namespace.
// They will be found by argument dependent lookup.
void read_json_value(
level_t & value,
const rapidjson::Value & from)
{...}
void
write_json_value(
const level_t & value,
rapidjson::Value & object,
rapidjson::MemoryPoolAllocator<> & allocator)
{...}
} /* namespace importance_levels */
his approach also allows to define read_json_value
and write_json_value
for user's template type. For example:
namespace demo
{
template<typename T>
class some_template
{...}
template<typename T>
void
read_json_value(
some_template<T> & value,
const rapidjson::Value & from)
{...}
template<typename T>
void
write_json_value(
const some_template<T> & value,
rapidjson::Value & object,
rapidjson::MemoryPoolAllocator<> & allocator)
{...}
} /* namespace demo */
struct my_data_t
{
demo::some_template<int> m_first;
demo::some_template<double> m_second;
...
template<typename Json_Io>
void json_io(Json_Io & io)
{
io & json_dto::mandatory("first", m_first)
& json_dto::mandatory("second", m_second)
...
}
};
See full example with custom IO and ADL
The second way uses explicit template specialization for 2 functons
inside json_dto
namespace:
namespace json_dto
{
template<>
void read_json_value(
Custom_Type & v,
const rapidjson::Value & object)
{
// ...
}
template<>
void write_json_value(
const Custom_Type & v,
rapidjson::Value & object,
rapidjson::MemoryPoolAllocator<> & allocator)
{
// ...
}
} /* namespace json_dto */
json_dto will consider these specializations for using with
specified Custom_Type
. This way can be used when it is impossible
to place read_json_value
and write_json_value
into the namespace where
the type if defined (for example if it is standard type like std::filesystem::path
).
See full example with custom IO
json_dto is distributed under BSD-3-Clause license. See LICENSE file for more information.
For the license of rapidson library see LICENSE file in rapidson distributive.
For the license of rapidson_mxxru library see LICENSE file in rapidson_mxxru distributive.
For the license of CATCH library see LICENSE file in CATCH distributive.