The document presents a comparison between JSON object transformation in C++ and Rust, outlining methods to achieve this functionality while discussing various approaches like object description passing and automatic description detection. It emphasizes Rust's memory safety, ownership system, and powerful macro capabilities, along with concrete code examples for defining traits and using procedural macros. The document concludes by highlighting Serde's efficiency and widespread use for serialization and deserialization in Rust.

1. Bind me if you can
Răzvan Rotari
Cristian Neamțu

2. How will you transform JSON into
an object ?

3. C++
{
"a": "1",
"b": 2,
"c": 3.0
}
struct SimpleStruct {
std::string a;
int b;
double c;
};
auto j =
nlohmann::json::parse(jsonString);
SimpleStruct s;
s.a = j[“a”];
s.b = j[“b”];
s.c = j[“c”];

4. Rust
{
"a": "1",
"b": 2,
"c": 3.0
}
#[derive(Serialize, Deserialize)]
struct Example {
a: String,
b: i32,
c: f64
}
let e: Example = serde_json::from_str(data)?;

5. Can we reproduce this
in c++?

6. NO!

7. But how close can we get?

8. Idea 1- Pass object description as parameter
const auto description = std::make_tuple(
std::make_pair("a", &SimpleStruct::a),
std::make_pair("b", &SimpleStruct::b),
std::make_pair("c", &SimpleStruct::c));
const auto output = readJson<SimpleStruct>(jsonData, description);

9. template <typename ReturnType, typename... Tuple>
ReturnType readJson(std::string_view jsonString, const std::tuple&
description) {
ReturnType ret;
auto j = nlohmann::json::parse(jsonString);
auto readValue = [&](const auto& key) { return j[key]; };
auto populateObject = [&](const auto& elemDesc) {
auto ReturnType::*ptr = std::get<1>(elemDesc);
ret.*ptr = readValue(std::get<0>(elemDesc));
};
std::apply([&](auto&... x) { (..., populateObject(x)); }, description);
/* [&](std::pair<char*, int SimpleStruct::*>& x1,
std::pair<char*, std::string SimpleStruct::*>& x2, ...) {
(populateObject(x1), populateObject(x2), populateObject(x3));
} */
return ret;
}

10. Idea 1- Pass object description as parameter
- No direct link between object and description
- Boilerplate
- Does not exposes implementation details

11. Idea 2- Automatic description detection
template <>
struct Descriptor {
static auto getDescription() {
return std::make_tuple(
std::make_pair("a", &SimpleStruct::a),
std::make_pair("b", &SimpleStruct::b),
std::make_pair("c", &SimpleStruct::c));
}
};
const auto output = readJson<SimpleStruct>(jsonData);

12. template <typename ReturnType>
struct Descriptor {
static void getDescription() {}
};
template <typename ReturnType>
ReturnType readJson(std::string_view jsonString) {
ReturnType ret;
auto j = json::parse(jsonString);
auto populateObject = /*Same as above*/
const auto description = Descriptor<ReturnType>{}.getDescription();
std::apply([&](auto&... x) { (..., populateObject(x)); }, description);
return ret;
}

13. Idea 2- Automatic description detection
- Even more boilerplate
- Longer compilation times
- Simpler interface
- Does not exposes implementation details

14. Idea 3 - Embed description into a type
//Requires c++20
template <>
struct Descriptor {
using type = std::tuple<
SETTER("a", &SimpleStruct::a),
SETTER("b", &SimpleStruct::b),
SETTER("c", &SimpleStruct::c)>;
};
const auto output = readJson<SimpleStruct>(jsonData);

15. template <>
struct Descriptor {
using type =
std::tuple<std::pair<decltype([]() { return "a"; }),
decltype(setter<&SimpleStruct::a>())>,
std::pair<decltype([]() { return "b"; }),
decltype(setter<&SimpleStruct::b>())>,
std::pair<decltype([]() { return "c"; }),
decltype(setter<&SimpleStruct::c>())> >;
};
EXPANDED VERSION

16. setter() function
template<auto PtrToMember>
constexpr auto setter() {
using Def = PtrMemberExtractor<PtrToMember>;
constexpr auto setterf = [](Def::containing_type & obj,
const Def::result& value) constexpr {
obj.*(Def::value) = value;
};
return setterf;
}
template <typename Class, typename Result, Result Class::*Value>
struct PtrMemberExtractor {
using containing_type = Class;
using result = Result;
static const auto value = Value;
};

17. template <typename ReturnType>
ReturnType readJson(std::string_view jsonString) {
ReturnType ret;
const auto j = json::parse(jsonString);
auto populateObject = [&](const auto& elemDesc) {
auto setter = std::get<1>(elemDesc);
auto keyFunc = std::get<0>(elemDesc);
setter(ret, j[(keyFunc())]);
};
const typename Descriptor<ReturnType>::type desc;
std::apply([&](auto&... x) { (..., populateObject(x)); }, desc);
/*The above expands to this
[&](std::pair<decltype([]() { return "a"; }),
decltype(setter<&SimpleStruct::a>())> x1,...){
(populateObject(x1), populateObject(x2), populateObject(x3));
} */
return ret;
}

18. Idea 3 - Embed description into a type
- Uses macros
- Even longer compilation times
- Requires c++20
- Does not exposes implementation details
-

19. Performace
Baseline Parameter Automatic Compile
mean 2.631 us
Low mean 2.623 us
High mean 2.656 us

20. Conclusions
- Good to hide implementation
- In practice the keys need to be provided so the boilerplate is reduced
- Works better for complex data, like the output of a SQL JOIN
- Serialization can use the same description
- Flexible pattern

21. Rust

22. What Why Rust?
● Focused on memory safety
● No classes, no inheritance
● Traits over Interfaces
● No variadics in general
● Types can be deduced implicitly
● macro_rules! and procedural macros

23. The Ownership system
1. Each value has an owner
2. There can be only one owner at a time
3. When the owner goes out of scope the value gets dropped
The compiler:
● checks if the rules are respected
● checks the lifetimes of the data
● inserts clean up code during compilation
Code Examples

24. Traits
● similar to the idea of interfaces with some differences
● define a contract that must be supported by the desired data type
● can define include both static and instance specific methods
● can provide default implementations
● can be attached to any datatype (owned code standard-library 3rd-party)
Code Examples

25. macro_rules!
macro_rules! map {
( $($key:expr => $value:expr),* ) => {{
let mut map = HashMap::new();
$(map.insert($key, $value); )*
map
}};
}
fn main() {
let person = map!(
"name" => "John",
"surname" => "Brown"
);
println!("{:?}", person);
}
● Pattern matched
● Token-type safe
○ ty - types
○ ident - identifiers
○ expr - expressions
○ etc.
● Steep learning curve
● Must produce syntactically correct code
● Rust Playground Link

26. Procedural macros
● a compiler plugin written in Rust that is loaded during compilation
○ it receives the (method, struct, etc.) AST as a parameter
○ produces another AST (rust syntax)

27. struct SimpleVisitor;
impl Visitor for SimpleVisitor {
type Value = Simple;
type Error = BindError;
fn visit_map(self, mut map: MapAccess) -> Result<Simple, BindError> {
Ok(Simple {
a: map.get_value("a")?.unwrap(),
b: map.get_value("b")?.unwrap(),
c: map.get_value("c")?.unwrap(),
})
}
}
How can I get from this?

28. To this?
#[derive(Deserializable,Debug)]
pub struct Simple {
pub a: i32,
pub b: String,
pub c: f64,
}

29. ProcMacro - TokenStream
pub[Ident] struct[Ident] Simple[Ident]
[Group]
pub[Ident] a[Ident] :[Punct] i32[Ident] ,[Punct]
pub[Ident] b[Ident] :[Punct] String[Ident] ,[Punct]
pub[Ident] c[Ident] :[Punct] f64[Ident] ,[Punct]
Implementation

30. Getting into Serde
● Main Traits
● Examples && Unit Tests
● Macros

32. Conclusions
● No boilerplate (due to the powerful macro system)
○ Serde: Extensive configurability (renaming, transforming or ignoring attributes, etc.)
○ Type safe conversions
● Serde efficiency due zero-copy deserialization
○ Benchmark - comparison
● Serde has been widely adopted as the “standard” for serialization and
deserialization in Rust:
○ https://serde.rs/#data-formats (json, yaml, csv, etc.)

33. Implementations available at:
● https://github.com/RazvanRotari/binding_experiment

34. Thank you!
Questions?