0 views collected around this technical thread.
This article provides a detailed tutorial on JSON fundamentals and demonstrates how to convert between Java objects, collections, maps, and JSON strings or objects using Alibaba's fastjson library, covering key‑value and array structures, code examples, and practical conversion scenarios.
This tutorial presents a thorough collection of Python JSON handling techniques, covering basic conversion, file read/write, data manipulation, merging, pretty printing, nested structures, custom serialization, batch processing, backup creation, performance optimization with ujson, API interaction, aggregation, error handling, and processing of commented JSON files.
This tutorial introduces PyYAML, explains how to install it, and provides twelve practical Python examples covering reading, writing, and manipulating YAML files, strings, lists, nested structures, complex data types, tags, anchors, streams, and environment variables.
This article reviews the most downloaded Python packages on PyPI over the last year, explaining each library's purpose, key features, usage examples, and why they are popular among developers, covering tools for HTTP, compatibility, AWS, data handling, security, and more.
This tutorial demonstrates how to encode Python objects to JSON strings, decode JSON back to Python, read and write JSON files, pretty‑print and sort JSON output, handle special types with custom encoders, preserve key order, manage non‑ASCII characters, and process binary JSON data using the built‑in json module.
This article examines how server‑side rendering can serialize normally non‑serializable data such as Promises, Dates, RegExp, and BigInt, comparing Remix’s defer‑based approach with Turbo‑Stream’s encode/decode method, and discusses their mechanisms, benefits, and challenges.
This article explains three common methods—eval, ast.literal_eval, and json.loads—for converting quoted Python strings into executable code or data structures, outlining their advantages, disadvantages, and appropriate use cases.
This article explains what Protocol Buffers (ProtoBuf) are, how they work, their key advantages over JSON and XML, practical usage patterns with code examples, compression mechanisms, real‑world applications, and best practices for maintaining compatibility in modern software systems.
This article introduces YAML as a human‑friendly data serialization format, explains its basic syntax such as key‑value pairs, indentation, lists, and multiline strings, outlines features like type inference and anchors, and offers best‑practice guidelines for secure and maintainable configuration files.
This article explains the fundamentals of JSON, its syntax rules, and demonstrates how PHP's json_encode and json_decode functions convert between arrays and JSON strings, including examples of sequential, non‑sequential, and multidimensional arrays, and the effect of the associative‑array option.
This article introduces Google Protocol Buffers, explains its binary encoding principles such as Tag‑Length‑Value, Varint and ZigZag, compares its efficiency with JSON/XML, and provides a step‑by‑step demo of building a Protobuf‑based WebSocket communication system using Node.js, protobufjs and a simple HTTP server.
Apache Avro is a high‑performance binary data serialization system originating from Hadoop that uses JSON‑defined schemas to enable compact storage, efficient network transfer, container file formats for MapReduce, and RPC communication without requiring code generation or explicit field numbers.
This article introduces Apache Thrift, explaining its open‑source RPC framework, IDL‑based code generation, protocol and transport layers, and its advantages for high‑performance data exchange in mobile advertising engines, while noting practical considerations such as static schema updates and usage of TFileTransport.
The article explains the Hermes data‑communication protocol built on MessagePack, detailing its lightweight design, language‑independent object serialization, binary format extensions, client‑server serialization workflows, object‑tree construction, and traversal strategies that together enable efficient data exchange for the Lest distributed cache system.