Simple C++ Serialization & Reflection.

Cista++ is a simple, open source (MIT license) C++17 compatible way of (de-)serializing C++ data structures. Developed and maintained by Felix Gündling.

Single header - no dependencies. No macros. No source code generation.

• Raw performance - use your native structs. Supports modification/resizing of deserialized data!
• Supports complex and cyclic data structures including cyclic references, recursive data structures, etc.
• Save 50% memory: serialize directly to the filesystem if needed, no intermediate buffer required.
• Fuzzing-checked though continuous fuzzing using LLVMs LibFuzzer.
• Comes with a serializable high-performance hash map and hash set implementation based on Google's Swiss Table.
• Reduce boilerplate code: automatic derivation of hash and equality functions.
• Built-in optional automatic data structure versioning through recursive type hashing.
• Optional check sum to prevent deserialization of corrupt data.
• Compatible with Clang, GCC, and MSVC

The underlying reflection mechanism can be used in other ways, too!

Installation:

Run:

$ npm i cista.cxx

And then include cista.h as follows:

#include "node_modules/cista.cxx/cista.h"

Examples:

Download the latest release and try it out.

Simple example writing to a buffer:

namespace data = cista::raw;
struct my_struct {  // Define your struct.
  int a_{0};
  struct inner {
      data::string b_;
  } j;
};

std::vector<unsigned char> buf;
{  // Serialize.
  my_struct obj{1, {data::string{"test"}}};
  buf = cista::serialize(obj);
}

// Deserialize.
auto deserialized = cista::deserialize<my_struct>(buf);
assert(deserialized->j.b_ == data::string{"test"});

Advanced example writing a hash map to a memory mapped file:

namespace data = cista::offset;
constexpr auto const MODE =  // opt. versioning + check sum
    cista::mode::WITH_VERSION | cista::mode::WITH_INTEGRITY;

struct pos { int x, y; };
using pos_map =  // Automatic deduction of hash & equality
    data::hash_map<data::vector<pos>,
                   data::hash_set<data::string>>;

{  // Serialize.
  auto positions =
      pos_map{{{{1, 2}, {3, 4}}, {"hello", "cista"}},
              {{{5, 6}, {7, 8}}, {"hello", "world"}}};
  cista::buf mmap{cista::mmap{"data"}};
  cista::serialize<MODE>(mmap, positions);
}

// Deserialize.
auto b = cista::mmap("data", cista::mmap::protection::READ);
auto positions = cista::deserialize<pos_map, MODE>(b);

Advanced example showing support for non-aggregate types like derived classes or classes with custom constructors:

namespace data = cista::offset;
constexpr auto MODE = cista::mode::WITH_VERSION;

struct parent {
  parent() = default;
  explicit parent(int a) : x_{a}, y_{a} {}
  auto cista_members() { return std::tie(x_, y_); }
  int x_, y_;
};
struct child : parent {
  child() = default;
  explicit child(int a) : parent{a}, z_{a} {}
  auto cista_members() {
    return std::tie(*static_cast<parent*>(this), z_);
  }
  int z_;
};

/*
 * Automatically defaulted for you:
 *   - de/serialization
 *   - hashing (use child in hash containers)
 *   - equality comparison
 *   - data structure version ("type hash")
 */
using t = data::hash_map<child, int>;

// ... usage, serialization as in the previous examples

Benchmarks

Have a look at the benchmark repository for more details.

| Library | Serialize | Deserialize | Fast Deserialize | Traverse | Deserialize & Traverse | Size | | :--- | ---: | ---: | ---: | ---: | ---: | ---: | | Cap’n Proto | 105 ms | 0.002 ms | 0.0 ms | 356 ms | 353 ms | 50.5M | | cereal | 239 ms | 197.000 ms | - | 125 ms | 322 ms | 37.8M | | Cista++ offset | 72 ms | 0.053 ms | 0.0 ms | 132 ms | 132 ms | 25.3M | | Cista++ raw | 3555 ms | 68.900 ms | 21.5 ms | 112 ms | 133 ms | 176.4M | | Flatbuffers | 2349 ms | 15.400 ms | 0.0 ms | 136 ms | 133 ms | 63.0M |

Use Cases

Reader and writer should have the same pointer width. Loading data on systems with a different byte order (endianess) is supported. Examples:

• Asset loading for all kinds of applications (i.e. game assets, GIS data, large graphs, etc.)
• Transferring data over network
• shared memory applications

Currently, only C++17 software can read/write data. But it should be possible to generate accessors for other programming languages, too.

Alternatives

If you need to be compatible with other programming languages or require protocol evolution (downward compatibility) you should look for another solution:

• Protocol Buffers
• Cap’n Proto
• Flatbuffers
• cereal
• Boost Serialization
• MessagePack
• tser
• ... many more

Documentation

• Installation and Usage
• Serialization Reference
• Custom (De-)Serialization Functions
• Data Structure Versioning
• Hash Containers
  • Hashing Framework
  • Equality Framework
  • Benchmark
• Security

Contribute

Feel free to contribute (bug reports, pull requests, etc.)!