A JSON library for Modern C++ by Niels Lohmann.

• Design goals
• Sponsors
• Support (documentation, FAQ, discussions, API, bug issues)
• Quick reference
• Examples
  • Read JSON from a file
  • Creating json objects from JSON literals
  • JSON as a first-class data type
  • Serialization / Deserialization
  • STL-like access
  • Conversion from STL containers
  • JSON Pointer and JSON Patch
  • JSON Merge Patch
  • Implicit conversions
  • Conversions to/from arbitrary types
  • Specializing enum conversion
  • Binary formats (BSON, CBOR, MessagePack, UBJSON, and BJData)
• Customers
• Supported compilers
• Integration
  • CMake
  • Package Managers
  • Pkg-config
• License
• Contact
• Thanks
• Used third-party tools
• Notes
• Execute unit tests

Installation

Run:

$ npm i json.cxx

And then include json.hpp as follows:

#include "node_modules/json.cxx/single_include/nlohmann/json.hpp"
#include "node_modules/json.cxx/single_include/nlohmann/json_fwd.hpp"  // optional: forward declaration

Design goals

There are myriads of JSON libraries out there, and each may even have its reason to exist. Our class had these design goals:

• Intuitive syntax. In languages such as Python, JSON feels like a first-class data type. We used all the operator magic of modern C++ to achieve the same feeling in your code. Check out the examples below and you'll know what I mean.

• Trivial integration. Our whole code consists of a single header file json.hpp. That's it. No library, no subproject, no dependencies, no complex build system. The class is written in vanilla C++11. All in all, everything should require no adjustment of your compiler flags or project settings. The library is also included in all popular package managers.

• Serious testing. Our code is heavily unit-tested and covers 100% of the code, including all exceptional behavior. Furthermore, we checked with Valgrind and the Clang Sanitizers that there are no memory leaks. Google OSS-Fuzz additionally runs fuzz tests against all parsers 24/7, effectively executing billions of tests so far. To maintain high quality, the project is following the Core Infrastructure Initiative (CII) best practices. See the quality assurance overview documentation.

Other aspects were not so important to us:

• Memory efficiency. Each JSON object has an overhead of one pointer (the maximal size of a union) and one enumeration element (1 byte). The default generalization uses the following C++ data types: std::string for strings, int64_t, uint64_t or double for numbers, std::map for objects, std::vector for arrays, and bool for Booleans. However, you can template the generalized class basic_json to your needs.

• Speed. There are certainly faster JSON libraries out there. However, if your goal is to speed up your development by adding JSON support with a single header, then this library is the way to go. If you know how to use a std::vector or std::map, you are already set.

See the contribution guidelines for more information.

Sponsors

You can sponsor this library at GitHub Sponsors.

:raising_hand: Priority Sponsor

• Martti Laine
• Paul Harrington

:label: Named Sponsors

• Michael Hartmann
• Stefan Hagen
• Steve Sperandeo
• Robert Jefe Lindstädt
• Steve Wagner
• Lion Yang

Further support

The development of the library is further supported by JetBrains by providing free access to their IDE tools.

Thanks everyone!

Support

:question: If you have a question, please check if it is already answered in the FAQ or the Q&A section. If not, please ask a new question there.

:books: If you want to learn more about how to use the library, check out the rest of the README, have a look at code examples, or browse through the help pages.

:construction: If you want to understand the API better, check out the API Reference or have a look at the quick reference below.

:bug: If you found a bug, please check the FAQ if it is a known issue or the result of a design decision. Please also have a look at the issue list before you create a new issue. Please provide as much information as possible to help us understand and reproduce your issue.

There is also a docset for the documentation browsers Dash, Velocity, and Zeal that contains the full documentation as an offline resource.

Quick reference

• Constructors basic_json, array, binary, object
• Object inspection: type, operator value_t, type_name, is_primitive, is_structured, is_null, is_boolean, is_number, is_number_integer, is_number_unsigned, is_number_float, is_object, is_array, is_string, is_binary, is_discarded
• Value access; get, get_to, get_ptr, get_ref, operator ValueType, get_binary
• Element access: at, operator[], value, front, back
• Lookup: find, count, contains
• Iterators: begin, cbegin, end, cend, rbegin, rend, crbegin, crend, items
• Capacity: empty, size, max_size
• Modifiers: clear, push_back, operator+=, emplace_back, emplace, erase, insert, update, swap
• Lexicographical comparison operators: operator==, operator!=, operator<, operator>, operator<=, operator>=, operator<=>
• Serialization / Dumping: dump
• Deserialization / Parsing: parse, accept, sax_parse
• JSON Pointer functions: flatten, unflatten
• JSON Patch functions: patch, patch_inplace, diff, merge_patch
• Static functions: meta, get_allocator
• Binary formats: from_bjdata, from_bson, from_cbor, from_msgpack, from_ubjson, to_bjdata, to_bson, to_cbor, to_msgpack, to_ubjson
• Non-member functions: operator<<, operator>>, to_string
• Literals: operator""_json
• Helper classes: std::hash<basic_json>, std::swap<basic_json>

Full API documentation

Examples

Here are some examples to give you an idea how to use the class.

Besides the examples below, you may want to:

→ Check the documentation
→ Browse the standalone example files
→ Read the full API Documentation with self-contained examples for every function

Read JSON from a file

The json class provides an API for manipulating a JSON value. To create a json object by reading a JSON file:

#include <fstream>
#include <nlohmann/json.hpp>
using json = nlohmann::json;

// ...

std::ifstream f("example.json");
json data = json::parse(f);

If using modules (enabled with NLOHMANN_JSON_BUILD_MODULES), this example becomes:

import std;
import nlohmann.json;

using json = nlohmann::json;

// ...

std::ifstream f("example.json");
json data = json::parse(f);

Creating json objects from JSON literals

Assume you want to create hard-code this literal JSON value in a file, as a json object:

{
  "pi": 3.141,
  "happy": true
}

There are various options:

// Using (raw) string literals and json::parse
json ex1 = json::parse(R"(
  {
    "pi": 3.141,
    "happy": true
  }
)");

// Using user-defined (raw) string literals
using namespace nlohmann::literals;
json ex2 = R"(
  {
    "pi": 3.141,
    "happy": true
  }
)"_json;

// Using initializer lists
json ex3 = {
  {"happy", true},
  {"pi", 3.141},
};

JSON as a first-class data type

Here are some examples to give you an idea how to use the class.

Assume you want to create the JSON object

{
  "pi": 3.141,
  "happy": true,
  "name": "Niels",
  "nothing": null,
  "answer": {
    "everything": 42
  },
  "list": [1, 0, 2],
  "object": {
    "currency": "USD",
    "value": 42.99
  }
}

With this library, you could write:

// create an empty structure (null)
json j;

// add a number stored as double (note the implicit conversion of j to an object)
j["pi"] = 3.141;

// add a Boolean stored as bool
j["happy"] = true;

// add a string stored as std::string
j["name"] = "Niels";

// add another null object by passing nullptr
j["nothing"] = nullptr;

// add an object inside the object
j["answer"]["everything"] = 42;

// add an array stored as std::vector (using an initializer list)
j["list"] = { 1, 0, 2 };

// add another object (using an initializer list of pairs)
j["object"] = { {"currency", "USD"}, {"value", 42.99} };

// instead, you could also write (which looks very similar to the JSON above)
json j2 = {
  {"pi", 3.141},
  {"happy", true},
  {"name", "Niels"},
  {"nothing", nullptr},
  {"answer", {
    {"everything", 42}
  }},
  {"list", {1, 0, 2}},
  {"object", {
    {"currency", "USD"},
    {"value", 42.99}
  }}
};

Note that in all these cases, you never need to "tell" the compiler which JSON value type you want to use. If you want to be explicit or express some edge cases, the functions json::array() and json::object() will help:

// a way to express the empty array []
json empty_array_explicit = json::array();

// ways to express the empty object {}
json empty_object_implicit = json({});
json empty_object_explicit = json::object();

// a way to express an _array_ of key/value pairs [["currency", "USD"], ["value", 42.99]]
json array_not_object = json::array({ {"currency", "USD"}, {"value", 42.99} });

Serialization / Deserialization

To/from strings

You can create a JSON value (deserialization) by appending _json to a string literal:

// create object from string literal
json j = "{ \"happy\": true, \"pi\": 3.141 }"_json;

// or even nicer with a raw string literal
auto j2 = R"(
  {
    "happy": true,
    "pi": 3.141
  }
)"_json;

Note that without appending the _json suffix, the passed string literal is not parsed, but just used as JSON string value. That is, json j = "{ \"happy\": true, \"pi\": 3.141 }" would just store the string "{ "happy": true, "pi": 3.141 }" rather than parsing the actual object.

The string literal should be brought into scope with using namespace nlohmann::literals; (see json::parse()).

The above example can also be expressed explicitly using json::parse():

// parse explicitly
auto j3 = json::parse(R"({"happy": true, "pi": 3.141})");

You can also get a string representation of a JSON value (serialize):

// explicit conversion to string
std::string s = j.dump();    // {"happy":true,"pi":3.141}

// serialization with pretty printing
// pass in the amount of spaces to indent
std::cout << j.dump(4) << std::endl;
// {
//     "happy": true,
//     "pi": 3.141
// }

Note the difference between serialization and assignment:

// store a string in a JSON value
json j_string = "this is a string";

// retrieve the string value
auto cpp_string = j_string.get<std::string>();
// retrieve the string value (alternative when a variable already exists)
std::string cpp_string2;
j_string.get_to(cpp_string2);

// retrieve the serialized value (explicit JSON serialization)
std::string serialized_string = j_string.dump();

// output of original string
std::cout << cpp_string << " == " << cpp_string2 << " == " << j_string.get<std::string>() << '\n';
// output of serialized value
std::cout << j_string << " == " << serialized_string << std::endl;

.dump() returns the originally stored string value.

Note the library only supports UTF-8. When you store strings with different encodings in the library, calling dump() may throw an exception unless json::error_handler_t::replace or json::error_handler_t::ignore are used as error handlers.

To/from streams (e.g., files, string streams)

You can also use streams to serialize and deserialize:

// deserialize from standard input
json j;
std::cin >> j;

// serialize to standard output
std::cout << j;

// the setw manipulator was overloaded to set the indentation for pretty printing
std::cout << std::setw(4) << j << std::endl;

These operators work for any subclasses of std::istream or std::ostream. Here is the same example with files:

// read a JSON file
std::ifstream i("file.json");
json j;
i >> j;

// write prettified JSON to another file
std::ofstream o("pretty.json");
o << std::setw(4) << j << std::endl;

Please note that setting the exception bit for failbit is inappropriate for this use case. It will result in program termination due to the noexcept specifier in use.

Read from iterator range

You can also parse JSON from an iterator range; that is, from any container accessible by iterators whose value_type is an integral type of 1, 2, or 4 bytes, which will be interpreted as UTF-8, UTF-16, and UTF-32 respectively. For instance, a std::vector<std::uint8_t>, or a std::list<std::uint16_t>:

std::vector<std::uint8_t> v = {'t', 'r', 'u', 'e'};
json j = json::parse(v.begin(), v.end());

You may leave the iterators for the range [begin, end):

std::vector<std::uint8_t> v = {'t', 'r', 'u', 'e'};
json j = json::parse(v);

Custom data source

Since the parse function accepts arbitrary iterator ranges, you can provide your own data sources by implementing the LegacyInputIterator concept.

struct MyContainer {
  void advance();
  const char& get_current();
};

struct MyIterator {
    using difference_type = std::ptrdiff_t;
    using value_type = char;
    using pointer = const char*;
    using reference = const char&;
    using iterator_category = std::input_iterator_tag;

    MyIterator& operator++() {
        target->advance();
        return *this;
    }

    bool operator!=(const MyIterator& rhs) const {
        return rhs.target != target;
    }

    reference operator*() const {
        return target->get_current();
    }

    MyContainer* target = nullptr;
};

MyIterator begin(MyContainer& tgt) {
    return MyIterator{&tgt};
}

MyIterator end(const MyContainer&) {
    return {};
}

void foo() {
    MyContainer c;
    json j = json::parse(c);
}

SAX interface

The library uses a SAX-like interface with the following functions:

// called when null is parsed
bool null();

// called when a boolean is parsed; value is passed
bool boolean(bool val);

// called when a signed or unsigned integer number is parsed; value is passed
bool number_integer(number_integer_t val);
bool number_unsigned(number_unsigned_t val);

// called when a floating-point number is parsed; value and original string is passed
bool number_float(number_float_t val, const string_t& s);

// called when a string is parsed; value is passed and can be safely moved away
bool string(string_t& val);
// called when a binary value is parsed; value is passed and can be safely moved away
bool binary(binary_t& val);

// called when an object or array begins or ends, resp. The number of elements is passed (or -1 if not known)
bool start_object(std::size_t elements);
bool end_object();
bool start_array(std::size_t elements);
bool end_array();
// called when an object key is parsed; value is passed and can be safely moved away
bool key(string_t& val);

// called when a parse error occurs; byte position, the last token, and an exception is passed
bool parse_error(std::size_t position, const std::string& last_token, const detail::exception& ex);

The return value of each function determines whether parsing should proceed.

To implement your own SAX handler, proceed as follows:

1. Implement the SAX interface in a class. You can use class nlohmann::json_sax<json> as base class, but you can also use any class where the functions described above are implemented and public.
2. Create an object of your SAX interface class, e.g. my_sax.
3. Call bool json::sax_parse(input, &my_sax); where the first parameter can be any input like a string or an input stream and the second parameter is a pointer to your SAX interface.

Note the sax_parse function only returns a bool indicating the result of the last executed SAX event. It does not return a json value - it is up to you to decide what to do with the SAX events. Furthermore, no exceptions are thrown in case of a parse error -- it is up to you what to do with the exception object passed to your parse_error implementation. Internally, the SAX interface is used for the DOM parser (class json_sax_dom_parser) as well as the acceptor (json_sax_acceptor), see file json_sax.hpp.

STL-like access

We designed the JSON class to behave just like an STL container. In fact, it satisfies the ReversibleContainer requirement.

// create an array using push_back
json j;
j.push_back("foo");
j.push_back(1);
j.push_back(true);

// also use emplace_back
j.emplace_back(1.78);

// iterate the array
for (json::iterator it = j.begin(); it != j.end(); ++it) {
  std::cout << *it << '\n';
}

// range-based for
for (auto& element : j) {
  std::cout << element << '\n';
}

// getter/setter
const auto tmp = j[0].get<std::string>();
j[1] = 42;
bool foo = j.at(2);

// comparison
j == R"(["foo", 1, true, 1.78])"_json;  // true

// other stuff
j.size();     // 4 entries
j.empty();    // false
j.type();     // json::value_t::array
j.clear();    // the array is empty again

// convenience type checkers
j.is_null();
j.is_boolean();
j.is_number();
j.is_object();
j.is_array();
j.is_string();

// create an object
json o;
o["foo"] = 23;
o["bar"] = false;
o["baz"] = 3.141;

// also use emplace
o.emplace("weather", "sunny");

// special iterator member functions for objects
for (json::iterator it = o.begin(); it != o.end(); ++it) {
  std::cout << it.key() << " : " << it.value() << "\n";
}

// the same code as range for
for (auto& el : o.items()) {
  std::cout << el.key() << " : " << el.value() << "\n";
}

// even easier with structured bindings (C++17)
for (auto& [key, value] : o.items()) {
  std::cout << key << " : " << value << "\n";
}

// find an entry
if (o.contains("foo")) {
  // there is an entry with key "foo"
}

// or via find and an iterator
if (o.find("foo") != o.end()) {
  // there is an entry with key "foo"
}

// or simpler using count()
int foo_present = o.count("foo"); // 1
int fob_present = o.count("fob"); // 0

// delete an entry
o.erase("foo");

Conversion from STL containers

Any sequence container (std::array, std::vector, std::deque, std::forward_list, std::list) whose values can be used to construct JSON values (e.g., integers, floating point numbers, Booleans, string types, or again STL containers described in this section) can be used to create a JSON array. The same holds for similar associative containers (std::set, std::multiset, std::unordered_set, std::unordered_multiset), but in these cases the order of the elements of the array depends on how the elements are ordered in the respective STL container.

std::vector<int> c_vector {1, 2, 3, 4};
json j_vec(c_vector);
// [1, 2, 3, 4]

std::deque<double> c_deque {1.2, 2.3, 3.4, 5.6};
json j_deque(c_deque);
// [1.2, 2.3, 3.4, 5.6]

std::list<bool> c_list {true, true, false, true};
json j_list(c_list);
// [true, true, false, true]

std::forward_list<int64_t> c_flist {12345678909876, 23456789098765, 34567890987654, 45678909876543};
json j_flist(c_flist);
// [12345678909876, 23456789098765, 34567890987654, 45678909876543]

std::array<unsigned long, 4> c_array {{1, 2, 3, 4}};
json j_array(c_array);
// [1, 2, 3, 4]

std::set<std::string> c_set {"one", "two", "three", "four", "one"};
json j_set(c_set); // only one entry for "one" is used
// ["four", "one", "three", "two"]

std::unordered_set<std::string> c_uset {"one", "two", "three", "four", "one"};
json j_uset(c_uset); // only one entry for "one" is used
// maybe ["two", "three", "four", "one"]

std::multiset<std::string> c_mset {"one", "two", "one", "four"};
json j_mset(c_mset); // both entries for "one" are used
// maybe ["one", "two", "one", "four"]

std::unordered_multiset<std::string> c_umset {"one", "two", "one", "four"};
json j_umset(c_umset); // both entries for "one" are used
// maybe ["one", "two", "one", "four"]

Likewise, any associative key-value containers (std::map, std::multimap, std::unordered_map, std::unordered_multimap) whose keys can construct an std::string and whose values can be used to construct JSON values (see examples above) can be used to create a JSON object. Note that in case of multimaps, only one key is used in the JSON object and the value depends on the internal order of the STL container.

std::map<std::string, int> c_map { {"one", 1}, {"two", 2}, {"three", 3} };
json j_map(c_map);
// {"one": 1, "three": 3, "two": 2 }

std::unordered_map<const char*, double> c_umap { {"one", 1.2}, {"two", 2.3}, {"three", 3.4} };
json j_umap(c_umap);
// {"one": 1.2, "two": 2.3, "three": 3.4}

std::multimap<std::string, bool> c_mmap { {"one", true}, {"two", true}, {"three", false}, {"three", true} };
json j_mmap(c_mmap); // only one entry for key "three" is used
// maybe {"one": true, "two": true, "three": true}

std::unordered_multimap<std::string, bool> c_ummap { {"one", true}, {"two", true}, {"three", false}, {"three", true} };
json j_ummap(c_ummap); // only one entry for key "three" is used
// maybe {"one": true, "two": true, "three": true}

JSON Pointer and JSON Patch

The library supports JSON Pointer (RFC 6901) as an alternative means to address structured values. On top of this, JSON Patch (RFC 6902) allows describing differences between two JSON values -- effectively allowing patch and diff operations known from Unix.

// a JSON value
json j_original = R"({
  "baz": ["one", "two", "three"],
  "foo": "bar"
})"_json;

// access members with a JSON pointer (RFC 6901)
j_original["/baz/1"_json_pointer];
// "two"

// a JSON patch (RFC 6902)
json j_patch = R"([
  { "op": "replace", "path": "/baz", "value": "boo" },
  { "op": "add", "path": "/hello", "value": ["world"] },
  { "op": "remove", "path": "/foo"}
])"_json;

// apply the patch
json j_result = j_original.patch(j_patch);
// {
//    "baz": "boo",
//    "hello": ["world"]
// }

// calculate a JSON patch from two JSON values
json::diff(j_result, j_original);
// [
//   { "op":" replace", "path": "/baz", "value": ["one", "two", "three"] },
//   { "op": "remove","path": "/hello" },
//   { "op": "add", "path": "/foo", "value": "bar" }
// ]

JSON Merge Patch

The library supports JSON Merge Patch (RFC 7386) as a patch format. Instead of using JSON Pointer (see above) to specify values to be manipulated, it describes the changes using a syntax that closely mimics the document being modified.

// a JSON value
json j_document = R"({
  "a": "b",
  "c": {
    "d": "e",
    "f": "g"
  }
})"_json;

// a patch
json j_patch = R"({
  "a":"z",
  "c": {
    "f": null
  }
})"_json;

// apply the patch
j_document.merge_patch(j_patch);
// {
//  "a": "z",
//  "c": {
//    "d": "e"
//  }
// }

Implicit conversions

Supported types can be implicitly converted to JSON values.

It is recommended to NOT USE implicit conversions FROM a JSON value. You can find more details about this recommendation here. You can switch off implicit conversions by defining JSON_USE_IMPLICIT_CONVERSIONS to 0 before including the json.hpp header. When using CMake, you can also achieve this by setting the option JSON_ImplicitConversions to OFF.

// strings
std::string s1 = "Hello, world!";
json js = s1;
auto s2 = js.get<std::string>();
// NOT RECOMMENDED
std::string s3 = js;
std::string s4;
s4 = js;

// Booleans
bool b1 = true;
json jb = b1;
auto b2 = jb.get<bool>();
// NOT RECOMMENDED
bool b3 = jb;
bool b4;
b4 = jb;

// numbers
int i = 42;
json jn = i;
auto f = jn.get<double>();
// NOT RECOMMENDED
double f2 = jb;
double f3;
f3 = jb;

// etc.

Note that char types are not automatically converted to JSON strings, but to integer numbers. A conversion to a string must be specified explicitly:

char ch = 'A';                       // ASCII value 65
json j_default = ch;                 // stores integer number 65
json j_string = std::string(1, ch);  // stores string "A"

Arbitrary types conversions

Every type can be serialized in JSON, not just STL containers and scalar types. Usually, you would do something along those lines:

namespace ns {
    // a simple struct to model a person
    struct person {
        std::string name;
        std::string address;
        int age;
    };
}

ns::person p = {"Ned Flanders", "744 Evergreen Terrace", 60};

// convert to JSON: copy each value into the JSON object
json j;
j["name"] = p.name;
j["address"] = p.address;
j["age"] = p.age;

// ...

// convert from JSON: copy each value from the JSON object
ns::person p {
    j["name"].get<std::string>(),
    j["address"].get<std::string>(),
    j["age"].get<int>()
};

It works, but that's quite a lot of boilerplate... Fortunately, there's a better way:

// create a person
ns::person p {"Ned Flanders", "744 Evergreen Terrace", 60};

// conversion: person -> json
json j = p;

std::cout << j << std::endl;
// {"address":"744 Evergreen Terrace","age":60,"name":"Ned Flanders"}

// conversion: json -> person
auto p2 = j.get<ns::person>();

// that's it
assert(p == p2);

Basic usage

To make this work with one of your types, you only need to provide two functions:

using json = nlohmann::json;

namespace ns {
    void to_json(json& j, const person& p) {
        j = json{{"name", p.name}, {"address", p.address}, {"age", p.age}};
    }

    void from_json(const json& j, person& p) {
        j.at("name").get_to(p.name);
        j.at("address").get_to(p.address);
        j.at("age").get_to(p.age);
    }
} // namespace ns

That's all! When calling the json constructor with your type, your custom to_json method will be automatically called. Likewise, when calling get<your_type>() or get_to(your_type&), the from_json method will be called.

Some important things:

• Those methods MUST be in your type's namespace (which can be the global namespace), or the library will not be able to locate them (in this example, they are in namespace ns, where person is defined).
• Those methods MUST be available (e.g., proper headers must be included) everywhere you use these conversions. Look at issue 1108 for errors that may occur otherwise.
• When using get<your_type>(), your_type MUST be DefaultConstructible. (There is a way to bypass this requirement described later.)
• In function from_json, use function at() to access the object values rather than operator[]. In case a key does not exist, at throws an exception that you can handle, whereas operator[] exhibits undefined behavior.
• You do not need to add serializers or deserializers for STL types like std::vector: the library already implements these.

Simplify your life with macros

If you just want to serialize/deserialize some structs, the to_json/from_json functions can be a lot of boilerplate. There are several macros to make your life easier as long as you (1) want to use a JSON object as serialization and (2) want to use the member variable names as object keys in that object.

Which macro to choose depends on whether private member variables need to be accessed, a deserialization is needed, missing values should yield an error or should be replaced by default values, and if derived classes are used. See this overview to choose the right one for your use case.

Example usage of macros

The to_json/from_json functions for the person struct above can be created with NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE. In all macros, the first parameter is the name of the class/struct, and all remaining parameters name the members.

namespace ns {
    NLOHMANN_DEFINE_TYPE_NON_INTRUSIVE(person, name, address, age)
}

Here is another example with private members, where NLOHMANN_DEFINE_TYPE_INTRUSIVE is needed:

namespace ns {
    class address {
      private:
        std::string street;
        int housenumber;
        int postcode;
  
      public:
        NLOHMANN_DEFINE_TYPE_INTRUSIVE(address, street, housenumber, postcode)
    };
}

How do I convert third-party types?

This requires a bit more advanced technique. But first, let's see how this conversion mechanism works:

The library uses JSON Serializers to convert types to JSON. The default serializer for nlohmann::json is nlohmann::adl_serializer (ADL means Argument-Dependent Lookup).

It is implemented like this (simplified):

template <typename T>
struct adl_serializer {
    static void to_json(json& j, const T& value) {
        // calls the "to_json" method in T's namespace
    }

    static void from_json(const json& j, T& value) {
        // same thing, but with the "from_json" method
    }
};

This serializer works fine when you have control over the type's namespace. However, what about boost::optional or std::filesystem::path (C++17)? Hijacking the boost namespace is pretty bad, and it's illegal to add something other than template specializations to std...

To solve this, you need to add a specialization of adl_serializer to the nlohmann namespace, here's an example:

// partial specialization (full specialization works too)
namespace nlohmann {
    template <typename T>
    struct adl_serializer<boost::optional<T>> {
        static void to_json(json& j, const boost::optional<T>& opt) {
            if (opt == boost::none) {
                j = nullptr;
            } else {
              j = *opt; // this will call adl_serializer<T>::to_json which will
                        // find the free function to_json in T's namespace!
            }
        }

        static void from_json(const json& j, boost::optional<T>& opt) {
            if (j.is_null()) {
                opt = boost::none;
            } else {
                opt = j.get<T>(); // same as above, but with
                                  // adl_serializer<T>::from_json
            }
        }
    };
}

How can I use get() for non-default constructible/non-copyable types?

There is a way if your type is MoveConstructible. You will need to specialize the adl_serializer as well, but with a special from_json overload:

struct move_only_type {
    move_only_type() = delete;
    move_only_type(int ii): i(ii) {}
    move_only_type(const move_only_type&) = delete;
    move_only_type(move_only_type&&) = default;

    int i;
};

namespace nlohmann {
    template <>
    struct adl_serializer<move_only_type> {
        // note: the return type is no longer 'void', and the method only takes
        // one argument
        static move_only_type from_json(const json& j) {
            return {j.get<int>()};
        }

        // Here's the catch! You must provide a to_json method! Otherwise, you
        // will not be able to convert move_only_type to json, since you fully
        // specialized adl_serializer on that type
        static void to_json(json& j, move_only_type t) {
            j = t.i;
        }
    };
}

Can I write my own serializer? (Advanced use)

Yes. You might want to take a look at unit-udt.cpp in the test suite, to see a few examples.

If you write your own serializer, you'll need to do a few things:

• use a different basic_json alias than nlohmann::json (the last template parameter of basic_json is the JSONSerializer)
• use your basic_json alias (or a template parameter) in all your to_json/from_json methods
• use nlohmann::to_json and nlohmann::from_json when you need ADL

Here is an example, without simplifications, that only accepts types with a size <= 32, and uses ADL.

// You should use void as a second template argument
// if you don't need compile-time checks on T
template<typename T, typename SFINAE = typename std::enable_if<sizeof(T) <= 32>::type>
struct less_than_32_serializer {
    template <typename BasicJsonType>
    static void to_json(BasicJsonType& j, T value) {
        // we want to use ADL, and call the correct to_json overload
        using nlohmann::to_json; // this method is called by adl_serializer,
                                 // this is where the magic happens
        to_json(j, value);
    }

    template <typename BasicJsonType>
    static void from_json(const BasicJsonType& j, T& value) {
        // same thing here
        using nlohmann::from_json;
        from_json(j, value);
    }
};

Be very careful when reimplementing your serializer, you can stack overflow if you don't pay attention:

template <typename T, void>
struct bad_serializer
{
    template <typename BasicJsonType>
    static void to_json(BasicJsonType& j, const T& value) {
      // this calls BasicJsonType::json_serializer<T>::to_json(j, value)
      // if BasicJsonType::json_serializer == bad_serializer ... oops!
      j = value;
    }

    template <typename BasicJsonType>
    static void to_json(const BasicJsonType& j, T& value) {
      // this calls BasicJsonType::json_serializer<T>::from_json(j, value)
      // if BasicJsonType::json_serializer == bad_serializer ... oops!
      value = j.get<T>(); // oops!
    }
};

Specializing enum conversion

By default, enum values are serialized to JSON as integers. In some cases, this could result in undesired behavior. If an enum is modified or re-ordered after data has been serialized to JSON, the later deserialized JSON data may be undefined or a different enum value than was originally intended.

It is possible to more precisely specify how a given enum is mapped to and from JSON as shown below:

// example enum type declaration
enum TaskState {
    TS_STOPPED,
    TS_RUNNING,
    TS_COMPLETED,
    TS_INVALID=-1,
};

// map TaskState values to JSON as strings
NLOHMANN_JSON_SERIALIZE_ENUM( TaskState, {
    {TS_INVALID, nullptr},
    {TS_STOPPED, "stopped"},
    {TS_RUNNING, "running"},
    {TS_COMPLETED, "completed"},
})

The NLOHMANN_JSON_SERIALIZE_ENUM() macro declares a set of to_json() / from_json() functions for type TaskState while avoiding repetition and boilerplate serialization code.

Usage:

// enum to JSON as string
json j = TS_STOPPED;
assert(j == "stopped");

// json string to enum
json j3 = "running";
assert(j3.get<TaskState>() == TS_RUNNING);

// undefined json value to enum (where the first map entry above is the default)
json jPi = 3.14;
assert(jPi.get<TaskState>() == TS_INVALID);

Just as in Arbitrary Type Conversions above,

• NLOHMANN_JSON_SERIALIZE_ENUM() MUST be declared in your enum type's namespace (which can be the global namespace), or the library will not be able to locate it, and it will default to integer serialization.
• It MUST be available (e.g., proper headers must be included) everywhere you use the conversions.

Other Important points:

• When using get<ENUM_TYPE>(), undefined JSON values will default to the first pair specified in your map. Select this default pair carefully.
• If an enum or JSON value is specified more than once in your map, the first matching occurrence from the top of the map will be returned when converting to or from JSON.

Binary formats (BSON, CBOR, MessagePack, UBJSON, and BJData)

Though JSON is a ubiquitous data format, it is not a very compact format suitable for data exchange, for instance over a network. Hence, the library supports BSON (Binary JSON), CBOR (Concise Binary Object Representation), MessagePack, UBJSON (Universal Binary JSON Specification) and BJData (Binary JData) to efficiently encode JSON values to byte vectors and to decode such vectors.

// create a JSON value
json j = R"({"compact": true, "schema": 0})"_json;

// serialize to BSON
std::vector<std::uint8_t> v_bson = json::to_bson(j);

// 0x1B, 0x00, 0x00, 0x00, 0x08, 0x63, 0x6F, 0x6D, 0x70, 0x61, 0x63, 0x74, 0x00, 0x01, 0x10, 0x73, 0x63, 0x68, 0x65, 0x6D, 0x61, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00

// roundtrip
json j_from_bson = json::from_bson(v_bson);

// serialize to CBOR
std::vector<std::uint8_t> v_cbor = json::to_cbor(j);

// 0xA2, 0x67, 0x63, 0x6F, 0x6D, 0x70, 0x61, 0x63, 0x74, 0xF5, 0x66, 0x73, 0x63, 0x68, 0x65, 0x6D, 0x61, 0x00

// roundtrip
json j_from_cbor = json::from_cbor(v_cbor);

// serialize to MessagePack
std::vector<std::uint8_t> v_msgpack = json::to_msgpack(j);

// 0x82, 0xA7, 0x63, 0x6F, 0x6D, 0x70, 0x61, 0x63, 0x74, 0xC3, 0xA6, 0x73, 0x63, 0x68, 0x65, 0x6D, 0x61, 0x00

// roundtrip
json j_from_msgpack = json::from_msgpack(v_msgpack);

// serialize to UBJSON
std::vector<std::uint8_t> v_ubjson = json::to_ubjson(j);

// 0x7B, 0x69, 0x07, 0x63, 0x6F, 0x6D, 0x70, 0x61, 0x63, 0x74, 0x54, 0x69, 0x06, 0x73, 0x63, 0x68, 0x65, 0x6D, 0x61, 0x69, 0x00, 0x7D

// roundtrip
json j_from_ubjson = json::from_ubjson(v_ubjson);

The library also supports binary types from BSON, CBOR (byte strings), and MessagePack (bin, ext, fixext). They are stored by default as std::vector<std::uint8_t> to be processed outside the library.

// CBOR byte string with payload 0xCAFE
std::vector<std::uint8_t> v = {0x42, 0xCA, 0xFE};

// read value
json j = json::from_cbor(v);

// the JSON value has type binary
j.is_binary(); // true

// get reference to stored binary value
auto& binary = j.get_binary();

// the binary value has no subtype (CBOR has no binary subtypes)
binary.has_subtype(); // false

// access std::vector<std::uint8_t> member functions
binary.size(); // 2
binary[0]; // 0xCA
binary[1]; // 0xFE

// set subtype to 0x10
binary.set_subtype(0x10);

// serialize to MessagePack
auto cbor = json::to_msgpack(j); // 0xD5 (fixext2), 0x10, 0xCA, 0xFE

Customers

The library is used in multiple projects, applications, operating systems, etc. The list below is not exhaustive, but the result of an internet search. If you know further customers of the library, please let me know, see contact.

Supported compilers

Though it's 2025 already, the support for C++11 is still a bit sparse. Currently, the following compilers are known to work:

• GCC 4.8 - 14.2 (and possibly later)
• Clang 3.4 - 21.0 (and possibly later)
• Apple Clang 9.1 - 16.0 (and possibly later)
• Intel C++ Compiler 17.0.2 (and possibly later)
• Nvidia CUDA Compiler 11.0.221 (and possibly later)
• Microsoft Visual C++ 2015 / Build Tools 14.0.25123.0 (and possibly later)
• Microsoft Visual C++ 2017 / Build Tools 15.5.180.51428 (and possibly later)
• Microsoft Visual C++ 2019 / Build Tools 16.3.1+1def00d3d (and possibly later)
• Microsoft Visual C++ 2022 / Build Tools 19.30.30709.0 (and possibly later)

I would be happy to learn about other compilers/versions.

Please note:

• GCC 4.8 has a bug 57824: multiline raw strings cannot be the arguments to macros. Don't use multiline raw strings directly in macros with this compiler.

• Android defaults to using very old compilers and C++ libraries. To fix this, add the following to your Application.mk. This will switch to the LLVM C++ library, the Clang compiler, and enable C++11 and other features disabled by default.

  APP_STL := c++_shared
  NDK_TOOLCHAIN_VERSION := clang3.6
  APP_CPPFLAGS += -frtti -fexceptions

  The code compiles successfully with Android NDK, Revision 9 - 11 (and possibly later) and CrystaX's Android NDK version 10.

• For GCC running on MinGW or Android SDK, the error 'to_string' is not a member of 'std' (or similarly, for strtod or strtof) may occur. Note this is not an issue with the code, but rather with the compiler itself. On Android, see above to build with a newer environment. For MinGW, please refer to this site and this discussion for information on how to fix this bug. For Android NDK using APP_STL := gnustl_static, please refer to this discussion.

• Unsupported versions of GCC and Clang are rejected by #error directives. This can be switched off by defining JSON_SKIP_UNSUPPORTED_COMPILER_CHECK. Note that you can expect no support in this case.

See the page quality assurance on the compilers used to check the library in the CI.

Integration

json.hpp is the single required file in single_include/nlohmann or released here. You need to add

#include <nlohmann/json.hpp>

// for convenience
using json = nlohmann::json;

to the files you want to process JSON and set the necessary switches to enable C++11 (e.g., -std=c++11 for GCC and Clang).

You can further use file include/nlohmann/json_fwd.hpp for forward-declarations. The installation of json_fwd.hpp (as part of cmake's install step) can be achieved by setting -DJSON_MultipleHeaders=ON.

CMake

You can also use the nlohmann_json::nlohmann_json interface target in CMake. This target populates the appropriate usage requirements for INTERFACE_INCLUDE_DIRECTORIES to point to the appropriate include directories and INTERFACE_COMPILE_FEATURES for the necessary C++11 flags.

External

To use this library from a CMake project, you can locate it directly with find_package() and use the namespaced imported target from the generated package configuration:

# CMakeLists.txt
find_package(nlohmann_json 3.12.0 REQUIRED)
...
add_library(foo ...)
...
target_link_libraries(foo PRIVATE nlohmann_json::nlohmann_json)

The package configuration file, nlohmann_jsonConfig.cmake, can be used either from an install tree or directly out of the build tree.

Embedded

To embed the library directly into an existing CMake project, place the entire source tree in a subdirectory and call add_subdirectory() in your CMakeLists.txt file:

# Typically you don't care so much for a third party library's tests to be
# run from your own project's code.
set(JSON_BuildTests OFF CACHE INTERNAL "")

# If you only include this third party in PRIVATE source files, you do not
# need to install it when your main project gets installed.
# set(JSON_Install OFF CACHE INTERNAL "")

# Don't use include(nlohmann_json/CMakeLists.txt) since that carries with it
# unintended consequences that will break the build.  It's generally
# discouraged (although not necessarily well documented as such) to use
# include(...) for pulling in other CMake projects anyways.
add_subdirectory(nlohmann_json)
...
add_library(foo ...)
...
target_link_libraries(foo PRIVATE nlohmann_json::nlohmann_json)

Embedded (FetchContent)

Since CMake v3.11, FetchContent can be used to automatically download a release as a dependency at configure time.

Example:

include(FetchContent)

FetchContent_Declare(json URL https://github.com/nlohmann/json/releases/download/v3.12.0/json.tar.xz)
FetchContent_MakeAvailable(json)

target_link_libraries(foo PRIVATE nlohmann_json::nlohmann_json)

Note: It is recommended to use the URL approach described above, which is supported as of version 3.10.0. See https://json.nlohmann.me/integration/cmake/#fetchcontent for more information.

Supporting Both

To allow your project to support either an externally supplied or an embedded JSON library, you can use a pattern akin to the following:

# Top level CMakeLists.txt
project(FOO)
...
option(FOO_USE_EXTERNAL_JSON "Use an external JSON library" OFF)
...
add_subdirectory(thirdparty)
...
add_library(foo ...)
...
# Note that the namespaced target will always be available regardless of the
# import method
target_link_libraries(foo PRIVATE nlohmann_json::nlohmann_json)

# thirdparty/CMakeLists.txt
...
if(FOO_USE_EXTERNAL_JSON)
  find_package(nlohmann_json 3.12.0 REQUIRED)
else()
  set(JSON_BuildTests OFF CACHE INTERNAL "")
  add_subdirectory(nlohmann_json)
endif()
...

thirdparty/nlohmann_json is then a complete copy of this source tree.

Package Managers

Use your favorite package manager to use the library.

•  Homebrew nlohmann-json
•  Meson nlohmann_json
•  Bazel nlohmann_json
•  Conan nlohmann_json
•  Spack nlohmann-json
• Hunter nlohmann_json
•  vcpkg nlohmann-json
• cget nlohmann/json
•  Swift Package Manager nlohmann/json
•  Nuget nlohmann.json
•  Conda nlohmann_json
•  MacPorts nlohmann-json
•  cpm.cmake gh:nlohmann/json
•  xmake nlohmann_json

The library is part of many package managers. See the documentation for detailed descriptions and examples.

Pkg-config

If you are using bare Makefiles, you can use pkg-config to generate the include flags that point to where the library is installed:

pkg-config nlohmann_json --cflags

License

The class is licensed under the MIT License:

Copyright © 2013-2025 Niels Lohmann

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

• The class contains the UTF-8 Decoder from Bjoern Hoehrmann which is licensed under the MIT License (see above). Copyright © 2008-2009 Björn Hoehrmann [email protected]
• The class contains a slightly modified version of the Grisu2 algorithm from Florian Loitsch which is licensed under the MIT License (see above). Copyright © 2009 Florian Loitsch
• The class contains a copy of Hedley from Evan Nemerson which is licensed as CC0-1.0.
• The class contains parts of Google Abseil which is licensed under the Apache 2.0 License.

The library is compliant to version 3.3 of the REUSE specification:

• Every source file contains an SPDX copyright header.
• The full text of all licenses used in the repository can be found in the LICENSES folder.
• File .reuse/dep5 contains an overview of all files' copyrights and licenses.
• Run pipx run reuse lint to verify the project's REUSE compliance and pipx run reuse spdx to generate a SPDX SBOM.

Contact

If you have questions regarding the library, I would like to invite you to open an issue at GitHub. Please describe your request, problem, or question as detailed as possible, and also mention the version of the library you are using as well as the version of your compiler and operating system. Opening an issue at GitHub allows other users and contributors to this library to collaborate. For instance, I have little experience with MSVC, and most issues in this regard have been solved by a growing community. If you have a look at the closed issues, you will see that we react quite timely in most cases.

Only if your request would contain confidential information, please send me an email. For encrypted messages, please use this key.

Security

Commits by Niels Lohmann and releases are signed with this PGP Key.

Thanks

I deeply appreciate the help of the following peopl