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#ifndef RFL_PARSING_VECTORPARSER_HPP_
#define RFL_PARSING_VECTORPARSER_HPP_
#include <iterator>
#include <map>
#include <stdexcept>
#include <string>
#include <type_traits>
#include "../Result.hpp"
#include "../always_false.hpp"
#include "MapParser.hpp"
#include "Parent.hpp"
#include "Parser_base.hpp"
#include "VectorReader.hpp"
#include "is_forward_list.hpp"
#include "is_map_like.hpp"
#include "is_map_like_not_multimap.hpp"
#include "is_set_like.hpp"
#include "schema/Type.hpp"
namespace rfl {
namespace parsing {
/// This can be used for data structures that would be expressed as array in
/// serialized format (std::vector, std::set, std::deque, ...),
/// but also includes map-like types, when the key is not of type
/// std::string.
template <class R, class W, class VecType, class ProcessorsType>
requires AreReaderAndWriter<R, W, VecType>
struct VectorParser {
public:
using InputArrayType = typename R::InputArrayType;
using InputVarType = typename R::InputVarType;
using ParentType = Parent<W>;
using T = typename VecType::value_type;
static Result<VecType> read(const R& _r, const InputVarType& _var) noexcept {
if constexpr (treat_as_map()) {
return MapParser<R, W, VecType, ProcessorsType>::read(_r, _var);
} else if constexpr (is_forward_list<VecType>()) {
const auto to_forward_list = [](auto&& vec) -> std::forward_list<T> {
std::forward_list<T> list;
for (auto it = vec.rbegin(); it != vec.rend(); ++it) {
list.emplace_front(std::move(*it));
}
return list;
};
return Parser<R, W, std::vector<T>, ProcessorsType>::read(_r, _var)
.transform(to_forward_list);
} else {
const auto parse = [&](const InputArrayType& _arr) -> Result<VecType> {
VecType vec;
auto vector_reader =
VectorReader<R, W, VecType, ProcessorsType>(&_r, &vec);
const auto err = _r.read_array(vector_reader, _arr);
if (err) {
return error(*err);
}
return vec;
};
return _r.to_array(_var).and_then(parse);
}
}
template <class P>
static void write(const W& _w, const VecType& _vec,
const P& _parent) noexcept {
if constexpr (treat_as_map()) {
MapParser<R, W, VecType, ProcessorsType>::write(_w, _vec, _parent);
} else {
auto arr = ParentType::add_array(
_w, std::distance(_vec.begin(), _vec.end()), _parent);
const auto new_parent = typename ParentType::Array{&arr};
for (const auto& v : _vec) {
Parser<R, W, std::remove_cvref_t<T>, ProcessorsType>::write(_w, v,
new_parent);
}
_w.end_array(&arr);
}
}
/// Generates a schema for the underlying type.
static schema::Type to_schema(
std::map<std::string, schema::Type>* _definitions) {
if constexpr (treat_as_map()) {
return MapParser<R, W, VecType, ProcessorsType>::to_schema(_definitions);
} else {
using Type = schema::Type;
return Type{Type::TypedArray{
.type_ = Ref<Type>::make(
Parser<R, W, T, ProcessorsType>::to_schema(_definitions))}};
}
}
private:
static constexpr bool treat_as_map() {
if constexpr (is_map_like_not_multimap<VecType>()) {
if constexpr (internal::has_reflection_type_v<typename T::first_type>) {
using U = std::remove_cvref_t<typename T::first_type::ReflectionType>;
return std::is_same<U, std::string>() || std::is_integral_v<U> ||
std::is_floating_point_v<U>;
// We do not need std::string here, it is already caught by the template
// specialization.
} else if constexpr (std::is_integral_v<typename T::first_type> ||
std::is_floating_point_v<typename T::first_type>) {
return true;
} else {
return false;
}
} else {
return false;
}
}
};
} // namespace parsing
} // namespace rfl
#endif
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