Simple C++ Serialization & Reflection.

Cista++ is a simple, open source (MIT license) C++17 compatible way of (de-)serializing C++ data structures.

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!

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);

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.)!