4 个仓库
JSON serialization that reuses buffers to avoid allocations during request and response processing.
Distinct from Zero-Allocation Buffer Encoders: Distinct from Zero-Allocation Buffer Encoders: focuses on JSON serialization for HTTP request/response processing, not general logging encoders.
Explore 4 awesome GitHub repositories matching software engineering & architecture · Buffer-Reusing Serializers. Refine with filters or upvote what's useful.
A light-weight REST API development framework for ASP.NET 8 and newer.
Reuses buffers during JSON serialization to avoid allocations in request and response processing.
MemoryPack 是一个用于 C# 和 Unity 的高性能二进制序列化库。它提供了一个零分配(Zero-allocation)数据流水线和模式演进框架,旨在最大限度地减少内存分配和编码开销。 该项目利用编译时源代码生成器来避免运行时反射,并实现了一种零编码二进制格式以实现最大吞吐量。它通过一种零分配方法脱颖而出,该方法重用对象实例以减少垃圾回收压力,并将非托管结构体的内存布局直接复制到二进制流中。 该库涵盖用于向后兼容的二进制模式版本控制,并支持针对大数据集的异步集合流式传输。它包括一个 TypeScript 类型生成器,用于在 C# 和 TypeScript 之间同步数据结构以进行跨语言数据交换。其他功能包括有效载荷压缩、自定义格式化程序实现和序列化回调。
Minimizes garbage collection pressure by reusing existing object instances during the deserialization process.
msgspec is a high-performance data modeling, serialization, and schema validation toolkit for Python. It serves as a type-safe serialization framework that integrates schema enforcement and data parsing into a single pass, functioning as both a data serialization library and a schema validation system based on standard Python type annotations. The project distinguishes itself through high-performance structural primitives, including compilation-based routine generation and zero-copy buffer parsing. It optimizes memory usage via garbage collection-aware layouts and reduces processing overhead
Reduces CPU and memory overhead by reusing encoder instances and writing into pre-allocated buffers.
This library is a high-performance JSON processing tool for Java designed to handle data serialization and deserialization with minimal resource consumption. It provides a framework for transforming complex object graphs into JSON strings and mapping raw input directly to typed class properties. The library distinguishes itself by utilizing compile-time code generation and reflection-free mapping to eliminate expensive runtime overhead. By employing iterator-based stream parsing and zero-allocation buffer management, it processes large or deeply nested data structures while reducing garbage c
Reuses internal memory buffers during the parsing process to reduce garbage collection pressure and improve performance.