This article explains why C++ developers should adopt third‑party libraries like RapidJSON for high‑performance JSON handling and pugixml for lightweight XML processing, covering integration steps, core APIs, and detailed code examples for parsing, generating, and traversing data structures.
This guide explains what LuaRocks is, shows step‑by‑step commands to compile and install it with OpenResty, details configuration flags, resolves a common unzip error, and demonstrates installing and using the rapidjson Lua package.
The article benchmarks cjson, rapidjson, and yyjson JSON libraries on a 6‑core OpenResty setup, shows that combining rapidjson's encode with yyjson's decode reduces 500,000 mixed encode/decode operations to 11 seconds, and describes a Lua wrapper that adds schema validation and improves maintainability.
This article compares Python's built‑in json module with faster alternatives like ujson, rapidjson, and the Rust‑based orjson, showing benchmark results, installation steps, code examples, and a known ujson indentation bug to help developers choose the most efficient JSON library.
The article investigates why Python's built‑in json.dumps can be slow on large data structures, compares the performance of ujson, python‑rapidjson, simplejson, and the Rust‑based orjson, provides benchmark code, installation commands, and discusses a bug in ujson's indent handling.
This article explains a systematic process for evaluating and selecting the most suitable high‑performance JSON library for Python, covering the need assessment, benchmark definition, filtering by additional requirements, and detailed benchmark results that highlight orjson as the fastest option for small‑message encoding while discussing trade‑offs such as safety, customizability, and ecosystem support.
This article compares the performance of Python's built‑in json module with popular third‑party libraries ujson, rapidjson, and the Rust‑based orjson, showing benchmark results, installation tips, code examples, and known bugs to help developers choose the most efficient JSON serializer.
