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The Basics

An overview of what you need to know to use simdjson, with examples.

Requirements

  • A recent compiler (LLVM clang6 or better, GNU GCC 7.4 or better, Xcode 11 or better) on a 64-bit (PPC, ARM or x64 Intel/AMD) POSIX systems such as macOS, freeBSD or Linux. We require that the compiler supports the C++11 standard or better.
  • Visual Studio 2017 or better under 64-bit Windows. Users should target a 64-bit build (x64) instead of a 32-bit build (x86). We support the LLVM clang compiler under Visual Studio (clangcl) as well as as the regular Visual Studio compiler. We also support MinGW 64-bit under Windows.

Including simdjson

To include simdjson, copy simdjson.h and simdjson.cpp into your project. Then include it in your project with:

#include "simdjson.h"
using namespace simdjson; // optional

You can compile with:

c++ myproject.cpp simdjson.cpp

Note:

  • Users on macOS and other platforms where default compilers do not provide C++11 compliant by default should request it with the appropriate flag (e.g., c++ -std=c++17 myproject.cpp simdjson.cpp).

Using simdjson with package managers

You can install the simdjson library on your system or in your project using multiple package managers such as MSYS2, the conan package manager, vcpkg, brew, the apt package manager (debian-based Linux systems), the FreeBSD package manager (FreeBSD), and so on. Visit our wiki for more details.

Using simdjson as a CMake dependency

You can include the simdjson library as a CMake dependency by including the following lines in your CMakeLists.txt:

include(FetchContent)

FetchContent_Declare(
  simdjson
  GIT_REPOSITORY https://github.com/simdjson/simdjson.git
  GIT_TAG  tags/v0.9.6
  GIT_SHALLOW TRUE)

FetchContent_MakeAvailable(simdjson)

You should provide GIT_TAG with the release you need. If you omit GIT_TAG ..., you will work from the main branch of simdjson: we recommend that if you are working on production code, you always work from a release.

Elsewhere in your project, you can declare dependencies on simdjson with lines such as these:

add_executable(myprogram myprogram.cpp)
target_link_libraries(myprogram simdjson)

We recommend CMake version 3.15 or better.

See our CMake demonstration. It works under Linux, FreeBSD, macOS and Windows (including Visual Studio).

The CMake build in simdjson can be taylored with a few variables. You can see the available variables and their default values by entering the cmake -LA command.

Versions

Users are discouraged from building production code from the project's main branch. The main branch is used for development: it may contain new features but also additional bugs.

Users should pick a release. They should also access the documentation matching the release that they have chosen. Note that new features may be added over time.

Our releases are tagged using semantic versioning: the tags are made of three numbers prefixed by the letter v and separated by periods.

You can always find the latest release at the following hyperlink:

https://github.com/simdjson/simdjson/releases/latest/

The archive you download at this location contains its own corresponding documentation.

You can also choose to browse a specific version of the documentation and the code using GitHub, by appending the version number to the hyperlink, like so:

https://github.com/simdjson/simdjson/blob/vx.y.z/doc/basics.md

where x.y.z should correspond to the version number you have chosen.

The Basics: Loading and Parsing JSON Documents

The simdjson library allows you to navigate and validate JSON documents (RFC 8259). As required by the standard, your JSON document should be in a Unicode (UTF-8) string. The whole string, from the beginning to the end, needs to be valid: we do not attempt to tolerate bad inputs before or after a document.

The simdjson library offers a tree-like API, which you can access by creating a ondemand::parser and calling the iterate() method. The iterate method quickly indexes the input string and may detect some errors. The following example illustrates how to get started with an input JSON file ("twitter.json"):

ondemand::parser parser;
auto json = padded_string::load("twitter.json"); // load JSON file 'twitter.json'.
ondemand::document doc = parser.iterate(json); // position a pointer at the beginning of the JSON data

You can also create a padded string---for efficiency reasons, simdjson requires a string with a few bytes (simdjson::SIMDJSON_PADDING) at the end---and calling iterate():

ondemand::parser parser;
auto json = "[1,2,3]"_padded; // The _padded suffix creates a simdjson::padded_string instance
ondemand::document doc = parser.iterate(json); // parse a string

If you have a buffer of your own with enough padding already (SIMDJSON_PADDING extra bytes allocated), you can use padded_string_view to pass it in:

ondemand::parser parser;
char json[3+SIMDJSON_PADDING];
strcpy(json, "[1]");
ondemand::document doc = parser.iterate(json, strlen(json), sizeof(json));

The simdjson library will also accept std::string instances, as long as the capacity() of the string exceeds the size() by at least SIMDJSON_PADDING. You can increase the capacity() with the reserve() function of your strings.

We recommend against creating many std::string or many std::padding_string instances in your application to store your JSON data. Consider reusing the same buffers and limiting memory allocations.

By default, the simdjson library throws exceptions (simdjson_error) on errors. We omit try-catch clauses from our illustrating examples: if you omit try-catch in your code, an uncaught exception will halt your program. It is also possible to use simdjson without generating exceptions, and you may even build the library without exception support at all. See Error Handling for details.

Documents are Iterators

The simdjson library relies on an approach to parsing JSON that we call "On Demand". A document is not a fully-parsed JSON value; rather, it is an iterator over the JSON text. This means that while you iterate an array, or search for a field in an object, it is actually walking through the original JSON text, merrily reading commas and colons and brackets to make sure you get where you are going. This is the key to On Demand's performance: since it's just an iterator, it lets you parse values as you use them. And particularly, it lets you skip values you do not want to use.

We refer to "On Demand" as a front-end component since it is an interface between the low-level parsing functions and the user. It hides much of the complexity of parsing JSON documents.

Parser, Document and JSON Scope

For code safety, you should keep (1) the parser instance, (2) the input string and (3) the document instance alive throughout your parsing. Additionally, you should follow the following rules:

  • A parser may have at most one document open at a time, since it holds allocated memory used for the parsing.
  • By design, you should only have one document instance per JSON document. Thus, if you must pass a document instance to a function, you should avoid passing it by value: choose to pass it by reference instance to avoid the copy. (We also provide a document_reference class if you need to pass by value.)

During the iterate call, the original JSON text is never modified--only read. After you are done with the document, the source (whether file or string) can be safely discarded.

For best performance, a parser instance should be reused over several files: otherwise you will needlessly reallocate memory, an expensive process. It is also possible to avoid entirely memory allocations during parsing when using simdjson. See our performance notes for details.

C++11 Support and string_view

The simdjson library builds on compilers supporting the C++11 standard. It is also a strict requirement: we have no plan to support older C++ compilers.

We represent parsed Unicode (UTF-8) strings in simdjson using the std::string_view class. It avoids the need to copy the data, as would be necessary with the std::string class. It also avoids the pitfalls of null-terminated C strings. It makes it easier for our users to copy the data into their own favorite class instances (e.g., alternatives to std::string).

A std::string_view instance is effectively just a pointer to a region in memory representing a string. In simdjson, we return std::string_view instances that either point within the input string you parsed, or to a temporary string buffer inside our parser class instances. When using std::string_view instances, it is your responsibility to ensure that std::string_view instance does not outlive the pointed-to memory (e.g., either the input buffer or the parser instance). Furthermore, some operations reset the string buffer inside our parser instances: e.g., when we parse a new document. Thus a std::string_view instance is often best viewed as a temporary string value that is tied to the document you are parsing. At the cost of some memory allocation, you may convert your std::string_view instances for long-term storage into std::string instances: std::string mycopy(view) (C++17) or std::string mycopy(view.begin(), view.end()) (prior to C++17).

The std::string_view class has become standard as part of C++17 but it is not always available on compilers which only supports C++11. When we detect that string_view is natively available, we define the macro SIMDJSON_HAS_STRING_VIEW.

When we detect that it is unavailable, we use string-view-lite as a substitute. In such cases, we use the type alias using string_view = nonstd::string_view; to offer the same API, irrespective of the compiler and standard library. The macro SIMDJSON_HAS_STRING_VIEW will be undefined to indicate that we emulate string_view.

Some users prefer to use non-JSON native encoding formats such as UTF-16 or UTF-32. Users may transcode the UTF-8 strings produced by the simdjson library to other formats. See the simdutf library, for example.

Using the Parsed JSON

We recommend that you first compile and run your code in Debug mode (with NDEBUG undefined). When you do so, the simdjson library runs additional sanity tests on your code to help ensure that you are using the library in a safe manner. Once your code has been tested, you can then run it in Release mode (with NDEBUG defined) for best performance. Alternatively, you can set the macro SIMDJSON_DEVELOPMENT_CHECKS to 1 prior to including the simdjson.h header to enable these additional checks: just make sure you remove the definition once your code has been tested.

Once you have a document (simdjson::ondemand::document), you can navigate it with idiomatic C++ iterators, operators and casts. Besides the document instances and native types (double, uint64_t, int64_t, bool), we also access Unicode (UTF-8) strings (std::string_view), objects (simdjson::ondemand::object) and arrays (simdjson::ondemand::array). We also have a generic type (simdjson::ondemand::value) which represents a potential array or object, or scalar type (double, uint64_t, int64_t, bool, null, string) inside an array or an object. Both generic types (simdjson::ondemand::document and simdjson::ondemand::value) have a type() method returning a json_type value describing the value (json_type::array, json_type::object, json_type::number, json_type::string, json_type::boolean, json_type::null).

Advanced users who need to determine the number types (integer or float) dynamically, should review our section dynamic number types. Indeed, we have an additional ondemand::number type which may represent either integers or floating-point values, depending on how the numbers are formatted. floating-point values followed by an integer.

While you are accessing the document, the document instance should remain in scope: it is your "iterator" which keeps track of where you are in the JSON document. By design, there is one and only one document instance per JSON document.

The following specific instructions indicate how to use the JSON when exceptions are enabled, but simdjson has full, idiomatic support for users who avoid exceptions. See the simdjson error handling documentation for more.

  • Validate What You Use: When calling iterate, the document is quickly indexed. If it is not a valid Unicode (UTF-8) string or if there is an unclosed string, an error may be reported right away. However, it is not fully validated. On Demand only fully validates the values you use and the structure leading to it.

  • Extracting Values: You can cast a JSON element to a native type: double(element) or double x = json_element. This works for std::string_view, double, uint64_t, int64_t, bool, ondemand::object and ondemand::array. At this point, the number, string or boolean will be parsed, or the initial [ or { will be verified. An exception is thrown if the cast is not possible.

    IMPORTANT NOTE: values can only be parsed once. Since documents are iterators, once you have parsed a value (such as by casting to double), you cannot get at it again.

  • Field Access: To get the value of the "foo" field in an object, use object["foo"]. This will scan through the object looking for the field with the matching string, doing a character-by-character comparison. For efficiency reason, you should avoid looking up the same field repeatedly: e.g., do not do object["foo"] followed by object["foo"] with the same object instance. Furthermore, you can only consume one field at a time, on the same object. Thus if you have retrieved content["bids"].get_array() and you later call content["asks"].get_array(), then the first array should no longer be accessed: it would be unsafe to do so. You can detect such mistakes by first compiling and running the code in Debug mode: an OUT_OF_ORDER_ITERATION error is generated.

    NOTE: JSON allows you to escape characters in keys. E.g., the key "date" may be written as "\u0064\u0061\u0074\u0065". By default, simdjson does not unescape keys when matching by default. Thus if you search for the key "date" and the JSON document uses "\u0064\u0061\u0074\u0065" as a key, it will not be recognized. This is not generally a problem. Nevertheless, if you do need to support escaped keys, the method unescaped_key() provides the desired unescaped keys by parsing and writing out the unescaped keys to a string buffer and returning a std::string_view instance. You should expect a performance penalty when using unescaped_key().

     auto json = R"({"k\u0065y": 1})"_padded;
ondemand::parser parser;
auto doc = parser.iterate(json);
ondemand::object object = doc.get_object();
for(auto field : object) {
   // parses and writes out the key, after unescaping it,
   // to a string buffer. It causes a performance penalty.
   std::string_view keyv = field.unescaped_key();
   if(keyv == "key") { std::cout << uint64_t(field.value()); }
 }

    By default, field lookup is order-insensitive, so you can look up values in any order. However, we still encourage you to look up fields in the order you expect them in the JSON, as it is still faster.

    If you want to enforce finding fields in order, you can use object.find_field("foo") instead. This will only look forward, and will fail to find fields in the wrong order: for example, this will fail:

    ondemand::parser parser;
auto json = R"(  { "x": 1, "y": 2 }  )"_padded;
auto doc = parser.iterate(json);
double y = doc.find_field("y"); // The cursor is now after the 2 (at })
double x = doc.find_field("x"); // This fails, because there are no more fields after "y"

    By contrast, using the default (order-insensitive) lookup succeeds:

    ondemand::parser parser;
auto json = R"(  { "x": 1, "y": 2 }  )"_padded;
auto doc = parser.iterate(json);
double y = doc["y"]; // The cursor is now after the 2 (at })
double x = doc["x"]; // Success: [] loops back around to find "x"

  • Array Iteration: To iterate through an array, use for (auto value : array) { ... }. This will step through each value in the JSON array.

    If you know the type of the value, you can cast it right there, too! for (double value : array) { ... }.

  • Object Iteration: You can iterate through an object's fields, as well: for (auto field : object) { ... }

    • field.unescaped_key() will get you the unescaped key string.
    • field.value() will get you the value, which you can then use all these other methods on.

  • Array Index: Because it is forward-only, you cannot look up an array element by index by index. Instead, you should iterate through the array and keep an index yourself.

  • Output to strings: Given a document, a value, an array or an object in a JSON document, you can output a JSON string version suitable to be parsed again as JSON content: simdjson::to_json_string(element). A call to to_json_string consumes fully the element: if you apply it on a document, the JSON pointer is advanced to the end of the document. The simdjson::to_json_string does not allocate memory. The to_json_string function should not be confused with retrieving the value of a string instance which are escaped and represented using a lightweight std::string_view instance pointing at an internal string buffer inside the parser instance. To illustrate, the first of the following two code segments will print the unescaped string "test" complete with the quote whereas the second one will print the escaped content of the string (without the quotes).

    // serialize a JSON to an escaped std::string instance so that it can be parsed again as JSON
auto silly_json = R"( { "test": "result"  }  )"_padded;
ondemand::document doc = parser.iterate(silly_json);
std::cout << simdjson::to_json_string(doc["test"]) << std::endl; // Requires simdjson 1.0 or better
    // retrieves an unescaped string value as a string_view instance
auto silly_json = R"( { "test": "result"  }  )"_padded;
ondemand::document doc = parser.iterate(silly_json);
std::cout << std::string_view(doc["test"]) << std::endl;

    You can use to_json_string to efficiently extract components of a JSON document to reconstruct a new JSON document, as in the following example:

    auto cars_json = R"( [
  { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
  { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
  { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;
std::vector<std::string_view> arrays;
// We are going to collect string_view instances which point inside the `cars_json` string
// and are therefore valid as long as `cars_json` remains in scope.
{
  ondemand::parser parser;
  for (ondemand::object car : parser.iterate(cars_json)) {
    if(uint64_t(car["year"]) > 2000) {
      arrays.push_back(simdjson::to_json_string(car["tire_pressure"]));
    }
  }
}
// We can now convert to a JSON string:
std::ostringstream oss;
oss << "[";
for(size_t i = 0; i < arrays.size(); i++) {
  if(i>0) { oss << ","; }
  oss << arrays[i];
}
oss << "]";
auto json_string = oss.str();
// json_string == "[[ 40.1, 39.9, 37.7, 40.4 ],[ 30.1, 31.0, 28.6, 28.7 ]]"

  • Extracting Values (without exceptions): You can use a variant usage of get() with error codes to avoid exceptions. You first declare the variable of the appropriate type (double, uint64_t, int64_t, bool, ondemand::object and ondemand::array) and pass it by reference to get() which gives you back an error code: e.g.,

    auto abstract_json = R"(
  { "str" : { "123" : {"abc" : 3.14 } } }
)"_padded;
ondemand::parser parser;

double value;
auto doc = parser.iterate(abstract_json);
auto error = doc["str"]["123"]["abc"].get(value);
if (error) { std::cerr << error << std::endl; return EXIT_FAILURE; }
cout << value << endl; // Prints 3.14

    This examples also show how we can string several operations and only check for the error once, a strategy we call error chaining. Though error chaining makes the code very compact, it also makes error reporting less precise: in this instance, you may get the same error whether the field "str", "123" or "abc" is missing. If you need to break down error handling per operation, avoid error chaining.

  • Counting elements in arrays: Sometimes it is useful to scan an array to determine its length prior to parsing it. For this purpose, array instances have a count_elements method. Users should be aware that the count_elements method can be costly since it requires scanning the whole array. You may use it as follows if your document is itself an array:

    auto cars_json = R"( [ 40.1, 39.9, 37.7, 40.4 ] )"_padded;
auto doc = parser.iterate(cars_json);
size_t count = doc.count_elements(); // requires simdjson 1.0 or better
std::vector<double> values(count);
size_t index = 0;
for(double x : doc) { values[index++] = x; }

    If you access an array inside a document, you can use the count_elements method as follow. You should not let the array instance go out of scope before consuming it after calling the count_elements method:

    ondemand::parser parser;
auto cars_json = R"( { "test":[ { "val1":1, "val2":2 }, { "val1":1, "val2":2 } ] }   )"_padded;
auto doc = parser.iterate(cars_json);
auto test_array = doc.find_field("test").get_array();
size_t count = test_array.count_elements(); // requires simdjson 1.0 or better
std::cout << "Number of elements: " <<  count << std::endl;
for(ondemand::object elem: test_array) {
   std::cout << simdjson::to_string(elem);
}

  • Counting fields in objects: Other times, it is useful to scan an object to determine the number of fields prior to parsing it. For this purpose, object instances have a count_fields method. Again, users should be aware that the count_fields method can be costly since it requires scanning the whole objects. You may use it as follows if your document is itself an object:

    ondemand::parser parser;
auto json = R"( { "test":{ "val1":1, "val2":2 } }   )"_padded;
auto doc = parser.iterate(json);
size_t count = doc.count_fields(); // requires simdjson 1.0 or better
std::cout << "Number of fields: " <<  new_count << std::endl; // Prints "Number of fields: 1"

    Similarly to count_elements, you should not let an object instance go out of scope before consuming it after calling the count_fields method. If you access an object inside a document, you can use the count_fields method as follow.

    ondemand::parser parser;
auto json = R"( { "test":{ "val1":1, "val2":2 } }   )"_padded;
auto doc = parser.iterate(json);
auto test_object = doc.find_field("test").get_object();
size_t count = test_object.count_fields(); // requires simdjson 1.0 or better
std::cout << "Number of fields: " <<  count << std::endl; // Prints "Number of fields: 2"

  • Tree Walking and JSON Element Types: Sometimes you don't necessarily have a document with a known type, and are trying to generically inspect or walk over JSON elements. To do that, you can use iterators and the type() method. You can also represent arbitrary JSON values with ondemand::value instances: it can represent anything except a scalar document (lone number, string, null or Boolean). You can check for scalar documents with the method scalar(). For example, the following is a quick and dirty recursive function that verbosely prints the JSON document as JSON. This example also illustrates lifecycle requirements: the document instance holds the iterator. The document must remain in scope while you are accessing instances of value, object and array.

    void recursive_print_json(ondemand::value element) {
  bool add_comma;
  switch (element.type()) {
  case ondemand::json_type::array:
    cout << "[";
    add_comma = false;
    for (auto child : element.get_array()) {
      if (add_comma) {
        cout << ",";
      }
      // We need the call to value() to get
      // an ondemand::value type.
      recursive_print_json(child.value());
      add_comma = true;
    }
    cout << "]";
    break;
  case ondemand::json_type::object:
    cout << "{";
    add_comma = false;
    for (auto field : element.get_object()) {
      if (add_comma) {
        cout << ",";
      }
      // key() returns the key as it appears in the raw
      // JSON document, if we want the unescaped key,
      // we should do field.unescaped_key().
      cout << "\"" << field.key() << "\": ";
      recursive_print_json(field.value());
      add_comma = true;
    }
    cout << "}\n";
    break;
  case ondemand::json_type::number:
    // assume it fits in a double
    cout << element.get_double();
    break;
  case ondemand::json_type::string:
    // get_string() would return escaped string, but
    // we are happy with unescaped string.
    cout << "\"" << element.get_raw_json_string() << "\"";
    break;
  case ondemand::json_type::boolean:
    cout << element.get_bool();
    break;
  case ondemand::json_type::null:
    cout << "null";
    break;
  }
}
void basics_treewalk() {
  padded_string json = R"( [
  { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
  { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
  { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;
  ondemand::parser parser;
  ondemand::document doc = parser.iterate(json);
  ondemand::value val = doc;
  recursive_print_json(val);
  std::cout << std::endl;
}

Using the Parsed JSON: Additional examples

Let us review these concepts with some additional examples. For simplicity, we omit the include clauses (#include "simdjson.h") as well as namespace-using clauses (using namespace simdjson;).

The first example illustrates how we can chain operations. In this instance, we repeatedly select keys using the bracket operator (doc["str"]) and then finally request a number (using get_double()). It is safe to write code in this manner: if any step causes an error, the error status propagates and an exception is thrown at the end. You do not need to constantly check for errors.

auto abstract_json = R"(
  { "str" : { "123" : {"abc" : 3.14 } } }
)"_padded;
ondemand::parser parser;
auto doc = parser.iterate(abstract_json);
cout << doc["str"]["123"]["abc"].get_double() << endl; // Prints 3.14

In the following example, we start with a JSON document that contains an array of objects. We iterate through the objects using a for-loop. Within each object, we use the bracket operator (e.g., car["make"]) to select values. We also show how we can iterate through an array, corresponding to the key tire_pressure, that is contained inside each object.

ondemand::parser parser;
auto cars_json = R"( [
  { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
  { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
  { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;

// Iterating through an array of objects
for (ondemand::object car : parser.iterate(cars_json)) {
  // Accessing a field by name
  cout << "Make/Model: " << std::string_view(car["make"]) << "/" << std::string_view(car["model"]) << endl;

  // Casting a JSON element to an integer
  uint64_t year = car["year"];
  cout << "- This car is " << 2020 - year << "years old." << endl;

  // Iterating through an array of floats
  double total_tire_pressure = 0;
  for (double tire_pressure : car["tire_pressure"]) {
    total_tire_pressure += tire_pressure;
  }
  cout << "- Average tire pressure: " << (total_tire_pressure / 4) << endl;
}

The following example illustrates how you may also iterate through object values, effectively visiting all key-value pairs in the object.

#include <iostream>
#include "simdjson.h"
using namespace std;
using namespace simdjson;

// ...

ondemand::parser parser;
auto points_json = R"( [
      {  "12345" : {"x":12.34, "y":56.78, "z": 9998877}   },
      {  "12545" : {"x":11.44, "y":12.78, "z": 11111111}  }
    ] )"_padded;

// Parse and iterate through an array of objects
for (ondemand::object points : parser.iterate(points_json)) {
  // Iterating through an object, you iterate through key-value pairs (a 'field').
  for (auto point : points) {
    // Get the key corresponding the the field 'point'.
    cout << "id: " << std::string_view(point.unescaped_key()) << ": (";
    // Get the value corresponding the the field 'point'.
    ondemand::object xyz = point.value();
    cout << xyz["x"].get_double() << ", ";
    cout << xyz["y"].get_double() << ", ";
    cout << xyz["z"].get_int64() << endl;
  }
}

Minifying JSON strings without parsing

In some cases, you may have valid JSON strings that you do not wish to parse but that you wish to minify. That is, you wish to remove all unnecessary spaces. We have a fast function for this purpose (simdjson::minify(const char * input, size_t length, const char * output, size_t& new_length)). This function does not validate your content, and it does not parse it. It is much faster than parsing the string and re-serializing it in minified form (simdjson::minify(parser.parse())). Usage is relatively simple. You must pass an input pointer with a length parameter, as well as an output pointer and an output length parameter (by reference). The output length parameter is not read, but written to. The output pointer should point to a valid memory region that is as large as the original string length. The input pointer and input length are read, but not written to.

  // Starts with a valid JSON document as a string.
  // It does not have to be null-terminated.
  const char * some_string = "[ 1, 2, 3, 4] ";
  size_t length = std::strlen(some_string);
  // Create a buffer to receive the minified string. Make sure that there is enough room (length bytes).
  std::unique_ptr<char[]> buffer{new char[length]};
  size_t new_length{}; // It will receive the minified length.
  auto error = simdjson::minify(some_string, length, buffer.get(), new_length);
  // The buffer variable now has "[1,2,3,4]" and new_length has value 9.

Though it does not validate the JSON input, it will detect when the document ends with an unterminated string. E.g., it would refuse to minify the string "this string is not terminated because of the missing final quote.

UTF-8 validation (alone)

The simdjson library has fast functions to validate UTF-8 strings. They are many times faster than most functions commonly found in libraries. You can use our fast functions, even if you do not care about JSON.

  const char * some_string = "[ 1, 2, 3, 4] ";
  size_t length = std::strlen(some_string);
  bool is_ok = simdjson::validate_utf8(some_string, length);

The UTF-8 validation function merely checks that the input is valid UTF-8: it works with strings in general, not just JSON strings.

Your input string does not need any padding. Any string will do. The validate_utf8 function does not do any memory allocation on the heap, and it does not throw exceptions.

If you find yourself needing only fast Unicode functions, consider using the simdutf library instead: https://github.com/simdutf/simdutf

JSON Pointer

The simdjson library also supports JSON pointer through the at_pointer() method, letting you reach further down into the document in a single call. JSON pointer is supported by both the DOM approach as well as the On Demand approach.

Note: The On Demand implementation of JSON pointer relies on find_field which implies that it does not unescape keys when matching.

Consider the following example:

auto cars_json = R"( [
  { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
  { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
  { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;
ondemand::parser parser;
auto cars = parser.iterate(cars_json);
cout << cars.at_pointer("/0/tire_pressure/1") << endl; // Prints 39.9

A JSON Path is a sequence of segments each starting with the '/' character. Within arrays, an integer index allows you to select the indexed node. Within objects, the string value of the key allows you to select the value. If your keys contain the characters '/' or '~', they must be escaped as '~1' and '~0' respectively. An empty JSON Path refers to the whole document.

For multiple JSON pointer queries on a document, one can call at_pointer multiple times.

auto cars_json = R"( [
  { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
  { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
  { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;
ondemand::parser parser;
auto cars = parser.iterate(cars_json);
size_t size = cars.count_elements();

for (size_t i = 0; i < size; i++) {
    std::string json_pointer = "/" + std::to_string(i) + "/tire_pressure/1";
    double x = cars.at_pointer(json_pointer);
    std::cout << x << std::endl; // Prints 39.9, 31 and 30
}

Note that at_pointer calls rewind to reset the parser at the beginning of the document. Hence, it invalidates all previously parsed values, objects and arrays: make sure to consume the values between each call to at_pointer. Consider the following example where one wants to store each object from the JSON into a vector of struct car_type:

struct car_type {
    std::string make;
    std::string model;
    uint64_t year;
    std::vector<double> tire_pressure;
    car_type(std::string_view _make, std::string_view _model, uint64_t _year,
      std::vector<double>&& _tire_pressure) :
      make{_make}, model{_model}, year(_year), tire_pressure(_tire_pressure) {}
};

auto cars_json = R"( [
{ "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
{ "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
{ "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
] )"_padded;

ondemand::parser parser;
std::vector<double> measured;
ondemand::document cars = parser.iterate(cars_json);
std::vector<car_type> content;
for (int i = 0; i < 3; i++) {
    std::string json_pointer = "/" + std::to_string(i);
    // Each successive at_pointer call invalidates
    // previously parsed values, strings, objects and array.
    ondemand::object obj(cars.at_pointer(json_pointer).get_object());
    // We materialize the object.
    std::string_view make = obj["make"];
    std::string_view model = obj["model"];
    uint64_t year(obj["year"]);
    // We materialize the array.
    ondemand::array arr(obj["tire_pressure"].get_array());
    std::vector<double> values;
    for(auto x : arr) {
        double value_double(x.get_double());
        values.push_back(value_double);
    }
    content.emplace_back(make, model, year, std::move(values));
}

Furthermore, at_pointer calls rewind at the beginning of the call (i.e. the document is not reset after at_pointer). Consider the following example,

auto json = R"( {
  "k0": 27,
  "k1": [13,26],
  "k2": true
} )"_padded;
ondemand::parser parser;
auto doc = parser.iterate(json);
std::cout << doc.at_pointer("/k1/1") << std::endl; // Prints 26
std::cout << doc.at_pointer("/k2") << std::endl; // Prints true
doc.rewind();	// Need to manually rewind to be able to use find_field properly from start of document
std::cout << doc.find_field("k0") << std::endl; // Prints 27

When the JSON path is the empty string ("") applied to a scalar document (lone string, number, Boolean or null), a SCALAR_DOCUMENT_AS_VALUE error is returned because scalar document cannot be represented as value instances. You can check that a document is a scalar with the method scalar().

Error Handling

Error handing with exception and a single try/catch clause makes the code simple, but it gives you little control over errors. For easier debugging or more robust error handling, you may want to consider our exception-free approach.

The entire simdjson API is usable with and without exceptions. All simdjson APIs that can fail return simdjson_result<T>, which is a <value, error_code> pair. You can retrieve the value with .get() without generating an exception, like so:

ondemand::element doc;
auto error = parser.iterate(json).get(doc);
if (error) { cerr << error << endl; exit(1); }

When you use the code this way, it is your responsibility to check for error before using the result: if there is an error, the result value will not be valid and using it will caused undefined behavior. Most compilers should be able to help you if you activate the right set of warnings: they can identify variables that are written to but never otherwise accessed.

Let us illustrate with an example where we try to access a number that is not valid (3.14.1). If we want to proceed without throwing and catching exceptions, we can do so as follows:

bool simple_error_example() {
    ondemand::parser parser;
    auto json = R"({"bad number":3.14.1 })"_padded;
    ondemand::document doc;
    if( parser.iterate(json).get(doc) != SUCCESS ) { return false; }
    double x;
    auto error = doc["bad number"].get_double().get(x);
    // returns "simdjson::NUMBER_ERROR"
    if(error != SUCCESS) {
      std::cout << error << std::endl;
      return false;
    }
    std::cout << "Got " << x << std::endl;
    return true;
}

Observe how we verify the error variable before accessing the retrieved number (variable x).

The equivalent with exception handling might look as follows.

  bool simple_error_example_except() {
    TEST_START();
    ondemand::parser parser;
    auto json = R"({"bad number":3.14.1 })"_padded;
    try {
      ondemand::document doc = parser.iterate(json);
      double x = doc["bad number"].get_double();
      std::cout << "Got " << x << std::endl;
      return true;
    } catch(simdjson_error& e) {
      // e.error() == NUMBER_ERROR
      std::cout << e.error() << std::endl;
      return false;
    }
  }

Notice how we can retrieve the exact error condition (in this instance simdjson::NUMBER_ERROR) from the exception.

We can write a "quick start" example where we attempt to parse the following JSON file and access some data, without triggering exceptions:

{
  "statuses": [
    {
      "id": 505874924095815700
    },
    {
      "id": 505874922023837700
    }
  ],
  "search_metadata": {
    "count": 100
  }
}

Our program loads the file, selects value corresponding to key "search_metadata" which expected to be an object, and then it selects the key "count" within that object.

#include <iostream>
#include "simdjson.h"

int main(void) {
  simdjson::ondemand::parser parser;
  auto error = padded_string::load("twitter.json").get(json);
  if(error) { std::cerr << error << std::endl; return EXIT_FAILURE; }
  simdjson::ondemand::document tweets;
  error = parser.iterate(json).get(tweets);
  if( error ) { std::cerr << error << std::endl; return EXIT_FAILURE; }
  simdjson::ondemand::value res;
  error = tweets["search_metadata"]["count"].get(res);
  if (error != SUCCESS) {
    std::cerr << "could not access keys : " << error << std::endl;
    return EXIT_FAILURE;
  }
  std::cout << res << " results." << std::endl;
  return EXIT_SUCCESS;
}

The following is a similar example where one wants to get the id of the first tweet without triggering exceptions. To do this, we use ["statuses"].at(0)["id"]. We break that expression down:

  • Get the list of tweets (the "statuses" key of the document) using ["statuses"]). The result is expected to be an array.
  • Get the first tweet using .at(0). The result is expected to be an object.
  • Get the id of the tweet using ["id"]. We expect the value to be a non-negative integer.

Observe how we use the at method when querying an index into an array, and not the bracket operator.

#include <iostream>
#include "simdjson.h"

int main(void) {
  simdjson::ondemand::parser parser;
  simdjson::ondemand::document tweets;
  padded_string json;
  auto error = padded_string::load("twitter.json").get(json);
  if(error) { std::cerr << error << std::endl; return EXIT_FAILURE; }
  error = parser.iterate(json).get(tweets);
  if(error) { std::cerr << error << std::endl; return EXIT_FAILURE; }
  uint64_t identifier;
  error = tweets["statuses"].at(0)["id"].get(identifier);
  if(error) { std::cerr << error << std::endl; return EXIT_FAILURE; }
  std::cout << identifier << std::endl;
}

Error Handling Examples without Exceptions

This is how the example in "Using the Parsed JSON" could be written using only error code checking (without exceptions):

bool parse() {
  ondemand::parser parser;
  auto cars_json = R"( [
    { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
    { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
    { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
  ] )"_padded;
  ondemand::document doc;

  // Iterating through an array of objects
  auto error = parser.iterate(cars_json).get(doc);
  if(error) { std::cerr << error << std::endl; return false; }
  ondemand::array cars;
  error = doc.get_array().get(cars);

  for (auto car_value : cars) {
    ondemand::object car;
    error = car_value.get_object().get(car);
    if(error) { std::cerr << error << std::endl; return false; }

    // Accessing a field by name
    std::string_view make;
    std::string_view model;
    error = car["make"].get(make);
    if(error) { std::cerr << error << std::endl; return false; }
    error = car["model"].get(model);
    if(error) { std::cerr << error << std::endl; return false; }

    cout << "Make/Model: " << make << "/" << model << endl;

    // Casting a JSON element to an integer
    uint64_t year;
    error = car["year"].get(year);
    if(error) { std::cerr << error << std::endl; return false; }
    cout << "- This car is " << 2020 - year << " years old." << endl;

    // Iterating through an array of floats
    double total_tire_pressure = 0;
    ondemand::array pressures;
    error = car["tire_pressure"].get_array().get(pressures);
    if(error) { std::cerr << error << std::endl; return false; }
    for (auto tire_pressure_value : pressures) {
      double tire_pressure;
      error = tire_pressure_value.get_double().get(tire_pressure);
      if(error) { std::cerr << error << std::endl; return false; }
      total_tire_pressure += tire_pressure;
    }
    cout << "- Average tire pressure: " << (total_tire_pressure / 4) << endl;
  }
  return true;
}

The following examples illustrates how to iterate through the content of an object without having to handle exceptions.

  auto json = R"({"k\u0065y": 1})"_padded;
  ondemand::parser parser;
  ondemand::document doc;
  auto error = parser.iterate(json).get(doc);
  if(error) { return false; }
  ondemand::object object;
  error = doc.get_object().get(object);
  if(error) { return false; }
  for(auto field : object) {
    ondemand::raw_json_string keyv;
    error = field.key().get(keyv);
    if(error) { return false; }
    if(keyv == "key") {
      uint64_t intvalue;
      error = field.value().get(intvalue);
      if(error) { return false; }
      std::cout << intvalue;
    }
  }

Disabling Exceptions

The simdjson can be build with exceptions entirely disabled. It checks the __cpp_exceptions macro at compile time. Even if exceptions are enabled in your compiler, you may still disable exceptions specifically for simdjson, by setting SIMDJSON_EXCEPTIONS to 0 (false) at compile-time when building the simdjson library. If you are building with CMake, to ensure you don't write any code that uses exceptions, you compile with SIMDJSON_EXCEPTIONS=OFF. For example, if including the project via cmake:

target_compile_definitions(simdjson PUBLIC SIMDJSON_EXCEPTIONS=OFF)

Exceptions

Users more comfortable with an exception flow may choose to directly cast the simdjson_result<T> to the desired type:

simdjson::ondemande::document doc = parser.iterate(json); // Throws an exception if there was an error!

When used this way, a simdjson_error exception will be thrown if an error occurs, preventing the program from continuing if there was an error.

If one is willing to trigger exceptions, it is possible to write simpler code:

#include <iostream>
#include "simdjson.h"

int main(void) {
  simdjson::ondemand::parser parser;
  padded_string json = padded_string::load("twitter.json");
  simdjson::ondemand::document tweets = parser.iterate(json);
  uint64_t identifier = tweets["statuses"].at(0)["id"];
  std::cout << identifier << std::endl;
  return EXIT_SUCCESS;
}

Current location in document

Sometimes, it might be helpful to know the current location in the document during iteration. This is especially useful when encountering errors. The current_location() method on a document instances makes it easy to identify common JSON errors. Users can call the current_location() method on a validdocument instance to retrieve a const char * pointer to the current location in the document. This method also works even after an error has invalidated the document and the parser (e.g. TAPE_ERROR, INCOMPLETE_ARRAY_OR_OBJECT). When the input was a padding_string or another null-terminated source, then you may use the const char * pointer as a C string. As an example, consider the following example where we used the exception-free simdjson interface:

auto broken_json = R"( {"double": 13.06, false, "integer": -343} )"_padded;    // Missing key
ondemand::parser parser;
auto doc = parser.iterate(broken_json);
int64_t i;
auto error = doc["integer"].get_int64().get(i);    // Expect to get integer from "integer" key, but get TAPE_ERROR
if (error) {
  std::cout << error << std::endl;    // Prints TAPE_ERROR error message
  std::cout<< doc.current_location() << std::endl;  // Prints "false, "integer": -343} " (location of TAPE_ERROR)
}

You may also use current_location() with exceptions as follows:

auto broken_json = R"( {"double": 13.06, false, "integer": -343} )"_padded;
ondemand::parser parser;
ondemand::document doc = parser.iterate(broken_json);
try {
  return int64_t(doc["integer"]);
} catch(simdjson_error& err) {
  std::cerr << doc.current_location() << std::endl;
  return -1;
}

In these examples, we tried to access the "integer" key, but since the parser had to go through a value without a key before (false), a TAPE_ERROR error is thrown. The pointer returned by the current_location() method then points at the location of the error. The current_location() may also be used when the error is triggered by a user action, even if the JSON input is valid. Consider the following example:

auto json = R"( [1,2,3] )"_padded;
ondemand::parser parser;
auto doc = parser.iterate(json);
int64_t i;
auto error = doc["integer"].get_int64().get(i);    // Incorrect call on array, INCORRECT_TYPE error
if (error) {
  std::cout << error << std::endl;     // Prints INCORRECT_TYPE error message
  std::cout<< doc.current_location() << std::endl;  // Prints "[1,2,3] " (location of INCORRECT_TYPE error)
}

If the location is invalid (i.e. at the end of a document), the current_location() methods returns an OUT_OF_BOUNDS error. For example:

auto json = R"( [1,2,3] )"_padded;
ondemand::parser parser;
auto doc = parser.iterate(json);
for (auto val : doc) {
  // Do something with val
}
std::cout << doc.current_location() << std::endl;   // Throws OUT_OF_BOUNDS

Finally, the current_location() method may also be used even when no exceptions/errors are thrown. This can be helpful for users that want to know the current state of iteration during parsing. For example:

auto json = R"( [[1,2,3], -23.4, {"key": "value"}, true] )"_padded;
ondemand::parser parser;
auto doc = parser.iterate(json);
for (auto val : doc) {
  ondemand::object obj;
  auto error = val.get_object().get(obj);     // Only get objects
  if (!error) {
    std::cout << doc.current_location() << std::endl;   // Prints ""key": "value"}, true] "
  }
}

The current_location() method requires a valid document instance. If the iterate function fails to return a valid document, then you cannot use current_location() to identify the location of an error in the input string. The errors reported by iterate function include EMPTY if no JSON document is detected, UTF8_ERROR if the string is not a valid UTF-8 string, UNESCAPED_CHARS if a string contains control characters that must be escaped and UNCLOSED_STRING if there is an unclosed string in the document. We do not provide location information for these errors.

Rewinding

In some instances, you may need to go through a document more than once. For that purpose, you may call the rewind() method on the document instance. It allows you to restart processing from the beginning without rescanning all of the input data again. It invalidates all values, objects and arrays that you have created so far (including unescaped strings).

In the following example, we print on the screen the number of cars in the JSON input file before printout the data.

  ondemand::parser parser;
  auto cars_json = R"( [
    { "make": "Toyota", "model": "Camry",  "year": 2018, "tire_pressure": [ 40.1, 39.9, 37.7, 40.4 ] },
    { "make": "Kia",    "model": "Soul",   "year": 2012, "tire_pressure": [ 30.1, 31.0, 28.6, 28.7 ] },
    { "make": "Toyota", "model": "Tercel", "year": 1999, "tire_pressure": [ 29.8, 30.0, 30.2, 30.5 ] }
  ] )"_padded;

  auto doc = parser.iterate(cars_json);
  for (simdjson_unused ondemand::object car : doc) {
    if(car["make"] == "Toyota") { count++; }
  }
  std::cout << "We have " << count << " Toyota cars.\n";
  doc.rewind(); // requires simdjson 1.0 or better
  for (ondemand::object car : doc) {
    cout << "Make/Model: " << std::string_view(car["make"]) << "/" << std::string_view(car["model"]) << endl;
  }

Performance note: the On Demand front-end does not materialize the parsed numbers and other values. If you are accessing everything twice, you may need to parse them twice. Thus the rewind functionality is best suited for cases where the first pass only scans the structure of the document.

Both arrays and objects have a similar method reset(). It is similar to the document rewind() method, except that it does not rewind the internal string buffer. Thus you should consume values only once even if you can iterate through the array or object more than once. If you unescape a string within an array more than once, you have unsafe code.

Direct Access to the Raw String

The simdjson library makes explicit assumptions about types. For examples, numbers must be integers (up to 64-bit integers) or binary64 floating-point numbers. Some users have different needs. For example, some users might want to support big infloating-point number followed by an integer.tegers. The library makes this possible by providing a raw_json_token method which returns a std::string_view instance containing the value as a string which you may then parse as you see fit.

simdjson::ondemand::parser parser;
simdjson::padded_string docdata =  R"({"value":12321323213213213213213213213211223})"_padded;
simdjson::ondemand::document doc = parser.iterate(docdata);
simdjson::ondemand::object obj = doc.get_object();
std::string_view token = obj["value"].raw_json_token();
// token has value 12321323213213213213213213213211223, it points inside the input string

The raw_json_token method even works when the JSON value is a string. In such cases, it will return the complete string with the quotes and with eventual escaped sequences as in the source document.

simdjson::ondemand::parser parser;
simdjson::padded_string docdata =  R"({"value":"12321323213213213213213213213211223"})"_padded;
simdjson::ondemand::document doc = parser.iterate(docdata);
simdjson::ondemand::object obj = doc.get_object();
string_view token = obj["value"].raw_json_token();
// token has value "12321323213213213213213213213211223", it points inside the input string

The raw_json_token() should be fast and free of allocation.

Newline-Delimited JSON (ndjson) and JSON lines

When processing large inputs (e.g., in the context of data engineering), engineers commonly serialize data into streams of multiple JSON documents. That is, instead of one large (e.g., 2 GB) JSON document containing multiple records, it is often preferable to write out multiple records as independent JSON documents, to be read one-by-one.

The simdjson library also supports multithreaded JSON streaming through a large file containing many smaller JSON documents in either ndjson or JSON lines format. If your JSON documents all contain arrays or objects, we even support direct file concatenation without whitespace. However, if there is content between your JSON documents, it should be exclusively ASCII white-space characters.

The concatenated file has no size restrictions (including larger than 4GB), though each individual document must be no larger than 4 GB.

Here is an example:

auto json = R"({ "foo": 1 } { "foo": 2 } { "foo": 3 } )"_padded;
ondemand::parser parser;
ondemand::document_stream docs = parser.iterate_many(json);
for (auto doc : docs) {
  std::cout << doc["foo"] << std::endl;
}
// Prints 1 2 3

Unlike parser.iterate, parser.iterate_many may parse "on demand" (lazily). That is, no parsing may have been done before you enter the loop for (auto doc : docs) { and you should expect the parser to only ever fully parse one JSON document at a time.

As with parser.iterate, when calling parser.iterate_many(string), no copy is made of the provided string input. The provided memory buffer may be accessed each time a JSON document is parsed. Calling parser.iterate_many(string) on a temporary string buffer (e.g., docs = parser.parse_many("[1,2,3]"_padded)) is unsafe (and will not compile) because the document_stream instance needs access to the buffer to return the JSON documents.

The iterate_many function can also take an optional parameter size_t batch_size which defines the window processing size. It is set by default to a large value (1000000 corresponding to 1 MB). None of your JSON documents should exceed this window size, or else you will get the error simdjson::CAPACITY. You cannot set this window size larger than 4 GB: you will get the error simdjson::CAPACITY. The smaller the window size is, the less memory the function will use. Setting the window size too small (e.g., less than 100 kB) may also impact performance negatively. Leaving it to 1 MB is expected to be a good choice, unless you have some larger documents.

The following toy examples illustrates how to get capacity errors. It is an artificial example since you should never use a batch_size of 50 bytes (it is far too small).

// We are going to set the capacity to 50 bytes which means that we cannot
// loading a document longer than 50 bytes. The first few documents are small,
// but the last one is large. We will get an error at the last document.
auto json = R"([1,2,3,4,5] [1,2,3,4,5] [1,2,3,4,5] [1,2,3,4,5] [1,2,3,4,5] [1,2,3,4,5] [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100])"_padded;
ondemand::parser parser;
ondemand::document_stream stream;
size_t counter{0};
auto error = parser.iterate_many(json, 50).get(stream);
if( error ) { /* handle the error */ }
for (auto doc: stream) {
  if(counter < 6) {
    int64_t val;
    error = doc.at_pointer("/4").get(val);
    if( error ) { /* handle the error */ }
    std::cout << "5 = " << val << std::endl;
  } else {
    ondemand::value val;
    error = doc.at_pointer("/4").get(val);
    // error == simdjson::CAPACITY
    if(error) {
      std::cerr << error << std::endl;
      // We left 293 bytes unprocessed at the tail end of the input.
      std::cout << " unprocessed bytes at the end: " << stream.truncated_bytes() << std::endl;
      break;
    }
  }
  counter++;
}

This example should print out:

5 = 5
5 = 5
5 = 5
5 = 5
5 = 5
5 = 5
This parser can't support a document that big
 unprocessed bytes at the end: 293

If your documents are large (e.g., larger than a megabyte), then the iterate_many function is maybe ill-suited. It is really meant to support reading efficiently streams of relatively small documents (e.g., a few kilobytes each). If you have larger documents, you should use other functions like iterate.

See iterate_many.md for detailed information and design.

Parsing Numbers Inside Strings

Though the JSON specification allows for numbers and string values, many engineers choose to integrate the numbers inside strings, e.g., they prefer {"a":"1.9"} to{"a":1.9}. The simdjson library supports parsing valid numbers inside strings which makes it more convenient for people working with those types of documents. This feature is supported through three methods: get_double_in_string, get_int64_in_string and get_uint64_in_string. However, it is important to note that these methods are not substitute to the regular get_double, get_int64 and get_uint64. The usage of the get_*_in_string methods is solely to parse valid JSON numbers inside strings, and so we expect users to call these methods appropriately. In particular, a valid JSON number has no leading and no trailing whitespaces, and the strings "nan", "1e" and "infinity" will not be accepted as valid numbers. As an example, suppose we have the following JSON text:

auto json =
{
   "ticker":{
      "base":"BTC",
      "target":"USD",
      "price":"443.7807865468",
      "volume":"31720.1493969300",
      "change":"Infinity",
      "markets":[
         {
            "market":"bitfinex",
            "price":"447.5000000000",
            "volume":"10559.5293639000"
         },
         {
            "market":"bitstamp",
            "price":"448.5400000000",
            "volume":"11628.2880079300"
         },
         {
            "market":"btce",
            "price":"432.8900000000",
            "volume":"8561.0563600000"
         }
      ]
   },
   "timestamp":1399490941,
   "timestampstr":"1399490941"
}

Now, suppose that a user wants to get the time stamp from the timestampstr key. One could do the following:

ondemand::parser parser;
auto doc = parser.iterate(json);
uint64_t time = doc.at_pointer("/timestampstr").get_uint64_in_string();
std::cout << time << std::endl;   // Prints 1399490941

Another thing a user might want to do is extract the markets array and get the market name, price and volume. Here is one way to do so:

ondemand::parser parser;
auto doc = parser.iterate(json);

// Getting markets array
ondemand::array markets = doc.find_field("ticker").find_field("markets").get_array();
// Iterating through markets array
for (auto value : markets) {
    std::cout << "Market: " << value.find_field("market").get_string();
    std::cout << "\tPrice: " << value.find_field("price").get_double_in_string();
    std::cout << "\tVolume: " << value.find_field("volume").get_double_in_string() << std::endl;
}

/* The above prints
Market: bitfinex        Price: 447.5    Volume: 10559.5
Market: bitstamp        Price: 448.54   Volume: 11628.3
Market: btce    Price: 432.89   Volume: 8561.06
*/

Finally, here is an example dealing with errors where the user wants to convert the string "Infinity"("change" key) to a float with infinity value.

ondemand::parser parser;
auto doc = parser.iterate(json);
// Get "change"/"Infinity" key/value pair
ondemand::value value = doc.find_field("ticker").find_field("change");
double d;
std::string_view view;
auto error = value.get_double_in_string().get(d);
// Check if parsed value into double successfully
if (error) {
  error = value.get_string().get(view);
  if (error) { /* Handle error */ }
  else if (view == "Infinity") {
    d = std::numeric_limits::infinity();
  }
  else { /* Handle wrong value */ }
}

It is also important to note that when dealing an invalid number inside a string, simdjson will report a NUMBER_ERROR error if the string begins with a number whereas simdjson will report a INCORRECT_TYPE error otherwise.

Dynamic Number Types

The JSON standard does not offer strongly typed numbers. It suggests that using the binary64 type (double in C++) is a safe choice, but little else. Given the JSON array [1.0,1], it is not specified whether it is an array of two floating-point numbers, two integers, or one floating-point number followed by an integer.

Given an ondemand::value instance, you may ask whether it is a negative value with the is_negative() method. The function is inexpensive.

To occasionally distinguish between floating-point values and integers given an ondemand::value instance, you may call the is_integer() method. We recognize an integer number by the lack decimal point and the lack of exponential suffix. E.g., 1e1 is always considered to be a floating-point number. The is_integer() method does not consume the value, but it scans the number string. You should avoid calling it repeatedly.

If you need to determine both the type of the number (integer or floating-point) and its value efficiently, you may call the get_number() method on the ondemand::value instance. Upon success, it returns an ondemand::number instance.

An ondemand::number instance may contain an integer value or a floating-point value. Thus it is a dynamically typed number. Before accessing the value, you must determine the detected type:

  • number.get_number_type() has value number_type::signed_integer if we have a integer in [-9223372036854775808,9223372036854775808). You can recover the value by the get_int64() method applied on the ondemand::number instance. When number.get_number_type() has value number_type::signed_integer, you also have that number.is_int64() is true. Calling get_int64() on the ondemand::number instance when number.get_number_type() is not number_type::signed_integer is unsafe. You may replace get_int64() by a cast to a int64_t value.
  • number.get_number_type() has value number_type::unsigned_integer if we have a integer in [9223372036854775808,18446744073709551616). You can recover the value by the get_uint64() method applied on the ondemand::number instance. When number.get_number_type() has value number_type::unsigned_integer, you also have that number.is_uint64() is true. Calling get_uint64() on the ondemand::number instance when number.get_number_type() is not number_type::unsigned_integer is unsafe. You may replace get_uint64() by a cast to a uint64_t value.
  • number.get_number_type() has value number_type::floating_point_number if we have and we have a floating-point (binary64) number. You can recover the value by the get_double() method applied on the ondemand::number instance. When number.get_number_type() has value number_type::floating_point_number, you also have that number.is_double() is true. Calling get_double() on the ondemand::number instance when number.get_number_type() is not number_type::floating_point_number is unsafe. You may replace get_double() by a cast to a double value.

You must check the type before accessing the value: it is an error to call get_int64() when number.get_number_type() is not number_type::signed_integer and when number.is_int64() is false. You are responsible for this check as the user of the library.

The get_number() function is designed with performance in mind. When calling get_number(), you scan the number string only once, determining efficiently the type and storing it in an efficient manner.

If you only need to compute v.get_number().get_number_type() on a document or value instance, you should call directly the faster method v.get_number_type() which does not generate an intermediate number instance.

Consider the following example:

    ondemand::parser parser;
    padded_string docdata = R"([1.0, 3, 1, 3.1415,-13231232,9999999999999999999])"_padded;
    ondemand::document doc = parser.iterate(docdata);
    ondemand::array arr = doc.get_array();
    for(ondemand::value val : arr) {
      std::cout << val << " ";
      std::cout << "negative: " << val.is_negative() << " ";
      std::cout << "is_integer: " << val.is_integer() << " ";
      ondemand::number num = val.get_number();
      // direct computation without materializing the number:
      ondemand::number_type dt = val.get_number_type();
      if(t != dt) { throw std::runtime_error("bug"); }
      switch(t) {
        case ondemand::number_type::signed_integer:
          std::cout  << "integer: " << int64_t(num) << " ";
          std::cout  << "integer: " << num.get_int64() << std::endl;
          break;
        case ondemand::number_type::unsigned_integer:
          std::cout  << "large 64-bit integer: " << uint64_t(num) << " ";
          std::cout << "large 64-bit integer: " << num.get_uint64() << std::endl;
          break;
        case ondemand::number_type::floating_point_number:
          std::cout  << "float: " << double(num) << " ";
          std::cout << "float: " << num.get_double() << std::endl;
          break;
      }
    }

It will output:

1.0 negative: 0 is_integer: 0 float: 1 float: 1
3 negative: 0 is_integer: 1 integer: 3 integer: 3
1 negative: 0 is_integer: 1 integer: 1 integer: 1
3.1415 negative: 0 is_integer: 0 float: 3.1415 float: 3.1415
-13231232 negative: 1 is_integer: 1 integer: -13231232 integer: -13231232
9999999999999999999 negative: 0 is_integer: 1 large 64-bit integer: 9999999999999999999 large 64-bit integer: 9999999999999999999

Thread Safety

We built simdjson with thread safety in mind.

The simdjson library is single-threaded except for iterate_many and parse_many which may use secondary threads under their control when the library is compiled with thread support.

We recommend using one parser object per thread. When using the On Demand front-end (our default), you should access the document instances in a single-threaded manner since it acts as an iterator (and is therefore not thread safe).

The CPU detection, which runs the first time parsing is attempted and switches to the fastest parser for your CPU, is transparent and thread-safe.

In a threaded environment, stack space is often limited. Running code like simdjson in debug mode may require hundreds of kilobytes of stack memory. Thus stack overflows are a possibility. We recommend you turn on optimization when working in an environment where stack space is limited. If you must run your code in debug mode, we recommend you configure your system to have more stack space. We discourage you from running production code based on a debug build.

Standard Compliance

The simdjson library is fully compliant with the RFC 8259 JSON specification.

  • The only insignificant whitespace characters allowed are the space, the horizontal tab, the line feed and the carriage return. In particular, a JSON document may not contain an unespaced null character.
  • A single string or a single number is considered to be a valid JSON document.
  • We fully validate the numbers according to the JSON specification. For example, the string 01 is not valid JSON document since the specification states that leading zeros are not allowed.
  • The specification allows implementations to set limits on the range and precision of numbers accepted. We support 64-bit floating-point numbers as well as integer values.
    • We parse integers and floating-point numbers afloating-point number followed by an integer.s separate types which allows us to support all signed (two's complement) 64-bit integersfloating-point number followed by an integer., like a Java long or a C/C++ long long and all 64-bit unsigned integers. When we cannot represent exactly an integer as a signed or unsigned 64-bit value, we reject the JSON document.
    • We support the full range of 64-bit floating-point numbers (binary64). The values range from std::numeric_limits<double>::lowest() to std::numefloating-point number followed by an integer.ric_limits<double>::max(), so from -1.7976e308 all the way to 1.7975e308. Extreme values (less or equal to -1e308, greater or equal to 1e308) are rejected: we refuse to parse the input document. Numbers are parsed with a perfect accuracy (ULP 0): the nearest floating-point value is chosen, rounding to even when needed. If you serialized your floating-point numbers with 17floating-point value followed by an integer. significant digits in a standard compliant manner, the simdjson library is guaranfloating-point number followed by an integer.teed to recover the same numbers, exactly.
  • The specification states that JSON text exchanged between systems that are not part of a closed ecosystem MUST be encoded using UTF-8. The simdjson library does full UTF-8 validation as part of the parsing. The specification states that implementations MUST NOT add a byte order mark: the simdjson library rejects documents starting with a byte order mark.
  • The simdjson library validates string content for unescaped characters. Unescaped line breaks and tabs in strings are not allowed.
  • The simdjson library accepts objects with repeated keys: all of the name/value pairs, including duplicates, are reported. We do not enforce key uniqueness.
  • The specification states that an implementation may set limits on the size of texts that it accepts. The simdjson library limits single JSON documents to 4 GiB. It will refuse to parse a JSON document larger than 4294967295 bytes. (This limitation does not apply to streams of JSON documents, only to single JSON documents.)
  • The specification states that an implementation may set limits on the maximum depth of nesting. By default, the simdjson will refuse to parse documents with a depth exceeding 1024.

Backwards Compatibility

The only header file supported by simdjson is simdjson.h. Older versions of simdjson published a number of other include files such as document.h or ParsedJson.h alongside simdjson.h; these headers may be moved or removed in future versions.