SBE is an OSI layer 6 presentation for encoding and decoding binary application messages for low-latency financial applications. This repository contains the reference implementations in Java, C++, Golang, and C#. The Java and C++ SBE implementations are designed with work very efficiently with the Aeron messaging system for low-latency and high-throughput communications. The Java SBE implementation has a dependency on Agrona for its buffer implementations.
https://github.com/real-logic/simple-binary-encodingTags | codec c-plus-plus encoder-decoder serialization |
Implementation | Java |
License | Apache |
Platform | OS-Independent |
A compact encoder / decoder pair that uses a binary zero-fluff encoding scheme. The size of the encoded object will be the same or smaller than the size that the object takes up in memory in a running Rust program. In addition to exposing two simple functions (one that encodes to Vec<u8>, and one that decodes from &[u8]), binary-encode exposes a Reader/Writer API that makes it work perfectly with other stream-based apis such as rust files, network streams, and the flate2-rs compression library.
encoding binary serializationA compact encoder / decoder pair that uses a binary zero-fluff encoding scheme. The size of the encoded object will be the same or smaller than the size that the object takes up in memory in a running Rust program. In addition to exposing two simple functions (one that encodes to Vec<u8>, and one that decodes from &[u8]), binary-encode exposes a Reader/Writer API that makes it work perfectly with other stream-based APIs such as Rust files, network streams, and the flate2-rs compression library.
encoding binary serializationA compact encoder / decoder pair that uses a binary zero-fluff encoding scheme. The size of the encoded object will be the same or smaller than the size that the object takes up in memory in a running Rust program. In addition to exposing two simple functions (one that encodes to Vec<u8>, and one that decodes from &[u8]), binary-encode exposes a Reader/Writer API that makes it work perfectly with other stream-based APIs such as Rust files, network streams, and the flate2-rs compression library.
encoding serialization binaryA low-level, fast, ultra-lightweight (3KB gzipped) JavaScript library for decoding and encoding protocol buffers, a compact binary format for structured data serialization. Works both in Node and the browser. Supports lazy decoding and detailed customization of the reading/writing code.If you use webpack as your module bundler, you can use pbf-loader to load .proto files directly. It returns a compiled module ready to be used.
protocol-buffers pbf serialization encoding decoding format binary library fast protocol buffer protobuf encoder decoderPSON is a super efficient binary serialization format for JSON focused on minimal encoding size. A PSON.StaticPair contains the PSON encoder and decoder for a static (or empty) dictionary and can be shared between all connections. It's recommended for production.
net buffer serialization bytebuffer websocket webrtc json protobuf thriftbase64 is a robust base64 encoder/decoder that is fully compatible with atob() and btoa(), written in JavaScript. The base64-encoding and -decoding algorithms it uses are fully RFC 4648 compliant.A string representing the semantic version number.
codec decoder encoder base64 atob btoacereal is a header-only C++11 serialization library. cereal takes arbitrary data types and reversibly turns them into different representations, such as compact binary encodings, XML, or JSON. cereal was designed to be fast, light-weight, and easy to extend - it has no external dependencies and can be easily bundled with other code or used standalone. Looking for more information on how cereal works and its documentation? Visit cereal's web page to get the latest information.
cereal serialization c-plus-plusHPC cluster video encoder is a cluster application that provides near real-time encoding of video different formats and size. It's developed in C# using Microsoft Expression Encoder 3 object model, Microsoft Advanced VC-1 video codec and Microsoft HPC Pack 2008 SDK.
audio cluster codec directshowRecent generations of CPUs, and GPUs in particular, require data-parallel codes for full efficiency. Data parallelism requires that the same sequence of operations is applied to different input data. CPUs and GPUs can thus reduce the necessary hardware for instruction decoding and scheduling in favor of more arithmetic and logic units, which execute the same instructions synchronously. On CPU architectures this is implemented via SIMD registers and instructions. A single SIMD register can store N values and a single SIMD instruction can execute N operations on those values. On GPU architectures N threads run in perfect sync, fed by a single instruction decoder/scheduler. Each thread has local memory and a given index to calculate the offsets in memory for loads and stores. Current C++ compilers can do automatic transformation of scalar codes to SIMD instructions (auto-vectorization). However, the compiler must reconstruct an intrinsic property of the algorithm that was lost when the developer wrote a purely scalar implementation in C++. Consequently, C++ compilers cannot vectorize any given code to its most efficient data-parallel variant. Especially larger data-parallel loops, spanning over multiple functions or even translation units, will often not be transformed into efficient SIMD code.
vectorization parallel simd-vector simd-instructions simd avx c-plus-plus avx512 sse neon cpp portable cpp11 cpp14 cpp17 avx2 simd-programming data-parallel parallel-computingAkumuli is a time-series database for modern hardware. It can be used to capture, store and process time-series data in real-time. The word "akumuli" can be translated from Esperanto as "accumulate".
time-series database c-plus-plus tsdb time-series-database metrics column-oriented columnar-databaseFast Binary Encoding allows to describe any domain models, business objects, complex data structures, client/server requests & responses and generate native code for different programming languages and platforms. To use Fast Binary Encoding you should provide a domain model (aka business objects). A domain model is a set of enums, flags and structures that relate to each other and might be aggregated in some hierarchy.
kotlin serialization performance cpp binary protocol low-latencyutf8.js is a well-tested UTF-8 encoder/decoder written in JavaScript. Unlike many other JavaScript solutions, it is designed to be a proper UTF-8 encoder/decoder: it can encode/decode any scalar Unicode code point values, as per the Encoding Standard. Here’s an online demo.A string representing the semantic version number.
utf8 encoder decoder charset encoding unicodeCompare various data serialization libraries for C++. This project does not have any external library dependencies. All (boost, thrift etc.) needed libraries are downloaded and built automatically, but you need enough free disk space to build all components. To build this project you need a compiler that supports C++11 features. Project was tested with GCC 4.8.2 (Ubuntu 14.04).
cpp serialization protobuf capn-proto thrift flatbuffers cereal performance-testing boost msgpack avro apache-avro c-plus-plus yasHeader-only C++17 library provides static reflection for enums, work with any enum type without any macro or boilerplate code.
cplusplus cplusplus-17 c-plus-plus c-plus-plus-17 cpp cpp17 enum-to-string string-to-enum serialization reflection metaprogramming header-only single-file no-dependenciesHeader-only C++17 library provides nameof macros and functions to simply obtain the name of a variable, type, function, macro, and enum. Nameof returns std::string_view. If argument does not have name, returns empty string.
cplusplus cplusplus-17 c-plus-plus c-plus-plus-17 cpp cpp17 nameof nameof-operator enum-to-string serialization reflection metaprogramming header-only single-file no-dependenciesV1 replaced Boost with C++11. V2 added Lua bindings. V3 refactored to remove some warts, ease future development, and re-add serialisation. API is evolving. Ponder is a C++ multi-purpose reflection library. It provides an abstraction for most of the high-level concepts of C++: classes, enumerations, functions, properties.
c-plus-plus reflection library lua-binding serialization introspection cpp cpp11 cpp14 cpp-library reflection-library serialization-libraryAlfalfa is a VP8 encoder and decoder, implemented in explicit state-passing style and developed by the Systems and Networking Research group at Stanford University. It is the basis for the ExCamera and Salsify systems. Almost all the source files are licensed under the BSD 2-clause license. Alfalfa links against x264 to compute the SSIM (quality) of frames. Because this library is distributed under the GNU GPL 2+, so is Alfalfa's ssim.cc file, and the overall Alfalfa package.
encoder decoder vp8 videoThe codec package contains simple encoder and decoders for various formats such as Base64 and Hexadecimal. In addition to these widely used encoders and decoders, the codec package also maintains a collection of phonetic encoding utilities.
SGN is a polymorphic binary encoder for offensive security purposes such as generating statically undetecable binary payloads. It uses a additive feedback loop to encode given binary instructions similar to LSFR. This project is the reimplementation of the original Shikata ga nai in golang with many improvements. For offensive security community, the original implementation of shikata ga nai encoder is considered to be the best shellcode encoder(until now). But over the years security researchers found several pitfalls for statically detecing the encoder(related work FireEye article). The main motive for this project was to create a better encoder that encodes the given binary to the point it is identical with totally random data and not possible to detect the presence of a decoder. With the help of keystone assembler library following improvments are implemented.
CoDec is a Java package for encoding and decoding ASN.1 data structures. CoDec supports the Basic Encoding Rules (BER) as well as the Distinguished Encoding Rules (DER) and provides a library with data structures for many cryptographic standards.
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