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Fast and nice to use C++ JSON library.

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A C++17 JSON writer and parser library. It

  • parses and serializes directly to and from statically typed C++ objects,
  • requires very little boilerplate code,
  • is fast and makes use of vectorization,
  • supports UTF-8,
  • comes with a good suite of tests,
  • is deployed and in active use on over 250 million devices,
  • and has API documentation.

spotify-json depends on Google's double-conversion library, which must be linked in to the code that uses spotify-json.




using namespace spotify::json;

struct Track { std::string uri; std::string uid; std::map<:string std::string> metadata; };

namespace spotify { namespace json {

// Specialize spotify::json::default_codec_t to specify default behavior when // encoding and decoding objects of certain types. template <> struct default_codec_t { static object_t codec() { auto codec = object(); codec.required("uri", &Track::uri); codec.optional("uid", &Track::uid); codec.optional("metadata", &Track::metadata); return codec; } };

} // namespace json } // namespace spotify

int main() { const auto parsed_track = decode(R"({ "uri": "spotify:track:xyz", "metadata": { "a": "b" } })"); std::cout << "Parsed track with uri " << parsed_track.uri << std::endl;

Track track; track.uri = "spotify:track:abc"; track.uid = "a-uid"; const auto json = encode(track); std::cout << "Encoded the track into " << json << std::endl;

return 0; }


spotify-json offers a range of codec types that can serialize and parse specific JSON values. There are codecs for each of the basic data types that JSON offers: strings, numbers, arrays, booleans, objects and null.

Constructing and composing codecs

A codec for integers can be made using

. The codec for strings can be instantiated with

Codecs are composable. It is for example possible to construct a codec for parsing and serialization of JSON arrays of numbers, such as


Constructing deeply nested codecs manually as above can become tedious. To ease this pain,

is a helper function that makes it easy to construct codecs for built-in types. For example,

is a codec that can parse and serialize numbers, and
is one that works on arrays of numbers.

It is possible to work with JSON objects with arbitrary keys. For example,

default_codec<:map bool>>()
is a codec for JSON objects with strings as keys and booleans as values.

Parsing and serialization

Parsing is done using the


try {
  decode(codec::number(), "123") == 123;
  decode("123") == 123;  // Shortcut for decode(default_codec(), "123")
  decode<:vector>>("[1,2,3]") == std::vector{ 1, 2, 3 };
} catch (const decode_exception &e) {
  std::cout << "Failed to decode: " << e.what() << std::endl;

when parsing fails. There is also a function
that doesn't throw on parse errors:

int result = 0;
if (try_decode(result, "123")) {
  result == 123;
} else {
  // Decoding failed!

Similarly, serialization is done using


encode(codec::number(), 123) == "123";
encode(123) == "123";  // Shortcut for encode(default_codec(), 123)
encode(std::vector{ 1, 2, 3 }) == "[1,2,3]";

Working with rich objects

Working with basic types such as numbers, strings, booleans and arrays is all nice and dandy, but most practical applications need to deal with rich JSON schemas that involve objects.

Many JSON libraries work by parsing JSON strings into a tree structure that can be read by the application. In our experience, this approach often leads to large amounts of boilerplate code to extract the information in this tree object into statically typed counterparts that are practical to use in C++. This boilerplate is painful to write, bug-prone and slow due to unnecessary copying. SAX-style event based libraries such as yajl avoid the slowdown but require even more boilerplate.

spotify-json avoids these issues by parsing the JSON directly into statically typed data structures. To explain how, let's use the example of a basic two-dimensional coordinate, represented in JSON as

. In C++, such a coordinate may be represented as a struct:
struct Coordinate {
  Coordinate() = default;
  Coordinate(int x, int y) : x(x), y(y) {}

int x = 0; int y = 0; };

With spotify-json, it is possible to construct a codec that can convert

directly to and from JSON:
auto coordinate_codec = object();
coordinate_codec.required("x", &Coordinate::x);
coordinate_codec.required("y", &Coordinate::y);

The use of

will cause parsing to fail if the fields are missing. There is also an
method. For more information, see
's API documentation

This codec can be used with

encode(coordinate_codec, Coordinate(10, 0)) == R"({"x":10,"y":0})";

const Coordinate coord = decode(coordinate_codec, R"({ "x": 12, "y": 13 })"); coord.x == 12; coord.y == 13;

Objects can be nested. To demonstrate this, let's introduce another data type:

struct Player {
  std::string name;
  std::string instrument;
  Coordinate position;

A codec for

might be created with
auto player_codec = object();
player_codec.required("name", &Player::name);
player_codec.required("instrument", &Player::instrument);
// Because there is no default_codec for Coordinate, we need to pass in the
// codec explicitly:
player_codec.required("position", &Player::position, coordinate_codec);

// Let's use it: Player player; = "Daniel"; player.instrument = "guitar"; encode(player_codec, player) == R"({"name":"Daniel","instrument":"guitar","position":{"x":0,"y":0}})";

Since codecs are just normal objects, it is possible to create and use several different codecs for any given data type. This makes it possible to parameterize parsing and do other fancy things, but for most data types there will only really exist one codec. For these cases, it is possible to extend the

helper to support your own data types.
namespace spotify {
namespace json {

template <> struct default_codec_t { static object_t codec() { auto codec = object(); codec.required("x", &Coordinate::x); codec.required("y", &Coordinate::y); return codec; } };

template <> struct default_codec_t { static object_t codec() { auto codec = object(); codec.required("name", &Player::name); codec.required("instrument", &Player::instrument); codec.required("position", &Player::position); return codec; } };

} // namespace json } // namespace spotify

can now be used like any other type that spotify-json supports out of the box:
encode(Coordinate(10, 0)) == R"({"x":10,"y":0})";
decode<:vector>>(R"([{ "x": 1, "y": -1 }])") == std::vector{ Coordinate(1, -1) };

Player player; = "Martin"; player.instrument = "drums"; encode(player) == R"({"name":"Martin","instrument":"drums","position":{"x":0,"y":0}})"; </:vector>

Advanced usage

The examples above cover the most commonly used parts of spotify-json. The library supports more things that sometimes come in handy:

Detailed API documentation

Linking against the library in a project

If your project is built with CMake, it is easy to use spotify-json. Here is an example of how it can be done:

  1. Add spotify-json as a git submodule under
  2. Add the following lines to the
    of your project:
target_link_libraries([YOUR TARGET] spotify-json)

Building and running tests


1. Make CMake find Boost

export BOOST_ROOT=/path/to/boost
export BOOST_LIBRARYDIR=/path/to/boost/lib/

2. Run CMake

mkdir build
cd build
cmake -G  ..

Run "cmake --help" for a list of generators available on your system.

3. Build project with Visual Studio / Xcode / Ninja

4. Run CTest

cd build
ctest -j 8

Code of conduct

This project adheres to the Open Code of Conduct. By participating, you are expected to honor this code.

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