The article explains why Spring Boot continues to use Jackson as its default JSON serializer, detailing the automatic ObjectMapper/JsonMapper creation, the HTTP message conversion process, Jackson’s balanced strengths, practical code samples, and how to switch to alternatives like Gson, JSON‑B, or Fastjson2.
This article walks through creating a minimal Java 17 RPC framework—from defining a simple binary protocol and using JDK serialization to implementing server loops, dynamic proxy‑based clients, and a runnable demo—while also highlighting the gaps that production‑grade solutions like Dubbo or gRPC must fill.
The article examines seven Python libraries—tenacity, attrs, structlog, DeepDiff, diskcache, watchdog, and msgspec—explaining when to adopt each, how they solve real‑world reliability, data‑modeling, logging, diffing, caching, file‑watching, and serialization problems, and when to replace them with heavier solutions.
A midnight payment outage caused a user to be charged three times because a Lombok‑generated @Data class ignored the superclass requestId in its equals method, breaking idempotency checks; the article explains the root cause, reproduces the bug, and offers concrete guidelines for safe Lombok usage.
The article explains that RPC outperforms traditional HTTP/1.1 + JSON because of a slimmer binary protocol, faster binary serialization, persistent long‑connection reuse, and an efficient NIO network model, while noting that HTTP/2 + gRPC narrows the gap.
The article explains why merely adding @Cacheable is insufficient and introduces four essential Redis design patterns—penetration protection, avalanche mitigation, serialization control, and consistency handling—plus client‑level considerations, each illustrated with concrete code and diagrams.
The article recounts a production incident where adding a trivial log statement caused a FastJSON NullPointerException, then explains the underlying serialization mechanism, the role of ASM-generated serializers, the methods invoked during serialization, and provides best‑practice guidelines to avoid similar bugs.
A performance bottleneck hidden in a fintech dashboard’s “coffee‑time” API was solved by profiling, discovering that 85% of latency came from JSON serialization, and replacing it with MessagePack, which reduced payload size by up to 74% and slashed end‑to‑end response time from 847 ms to 159 ms—a more than five‑fold improvement.
The article introduces nine lesser‑known Python packages—msgspec, glom, watchfiles, beartype, pyinstrument, duckdb, fakeredis, boltons, and returns—explaining how each tackles common prototyping pain points such as data serialization, file watching, runtime type safety, performance profiling, SQL querying without a server, mock Redis, utility functions, and explicit error handling, ultimately accelerating development by up to ten times.
json-io, a decade‑old Java JSON library known for zero‑config, circular‑reference support, and lightweight size, has added full TOON (Token‑Oriented Object Notation) read/write capabilities, a token‑efficient format designed for LLMs that can cut serialization costs by 30‑60% and integrates seamlessly with Spring Boot and Spring AI.
This article explains why remote procedure call (RPC) remains essential for microservice communication, detailing its historical roots, the limitations of HTTP, the multi‑step RPC workflow—including service discovery, serialization, network transmission, dynamic proxies, and governance—and how RPC and HTTP complement each other in modern architectures.
This article explains what MessagePack is, compares its size and speed to JSON in Node.js with real benchmarks, shows how to use the msgpackr library, and outlines the scenarios where its smaller binary payloads and native binary support outweigh its slower CPU serialization.
The article introduces Token‑Oriented Object Notation (TOON), a compact alternative to JSON designed for large language models, and demonstrates how its reduced syntax cuts token usage by up to 60%, speeds up parsing, and remains human‑readable.
The article explains how TCP provides reliable byte‑stream transport but lacks message boundaries, how HTTP adds structured semantics with headers like Content‑Length, and why RPC frameworks such as gRPC are introduced to make remote calls feel like local method invocations, especially in modern microservice architectures.
This article explains Python object injection, covering class basics, the pickle module's role in serialization, how untrusted data can lead to code execution, detection methods, and step‑by‑step creation of a malicious payload to demonstrate a real exploit.
This article explains the fundamentals of distributed communication, outlines essential elements such as serialization, transport protocols, service discovery, load balancing, security, and reliability, and reviews popular frameworks like gRPC, Dubbo, Thrift, and OpenFeign for building robust backend architectures.
This article explains how to control enum serialization and deserialization in Spring Boot 3, covering default output, @JsonFormat, @JsonValue, custom serializers and deserializers, as well as @JsonProperty, @JsonCreator, and practical code examples.
This article dissects Alibaba's Fastjson library, explaining its architecture, core modules, project structure, serialization and deserialization processes, ASM‑based performance optimizations, AutoType security mechanisms, and streaming API, while providing code examples and practical insights for Java developers.
This article provides a detailed comparison of Java 17 and Java 21 APIs, listing deprecated and removed features, suggested replacements, new I/O and serialization capabilities, enhanced reflection, Unicode emoji support, the preview foreign memory API, and the Generational ZGC, illustrated with real‑world code examples and usage scenarios.
Learn how to serialize LangChain components—including prompts, chains, and agents—using JSON and YAML, enabling reproducibility, collaboration, persistence, and decoupling, with step‑by‑step code examples for dumping objects to files and loading them back into executable LLM pipelines.
An unexpected NullPointerException occurs when adding a simple log line to a Java DTO, revealing that FastJSON’s serialization process invokes methods like isChinaName(), getXxx(), and isXxx() via ASM-generated serializers, and the article explains the underlying mechanism, common pitfalls, and best‑practice annotations to avoid such bugs.
This article explains how to handle JSON objects with unknown or dynamic fields in Java using Jackson's @JsonAnySetter to collect extra properties into a Map and @JsonAnyGetter to serialize them back as regular fields, complete with practical code examples and common pitfalls.
This article demonstrates how to use four lesser‑known Jackson annotations—@JsonAppend, @JsonNaming, @JsonPropertyDescription, and @JsonPOJOBuilder—to extend JSON serialization, customize property naming, enrich JSON Schema documentation, and deserialize immutable objects within Spring Boot 3 applications.
This article explains the core principles of Hessian, a Java‑optimized binary serialization protocol, covering object graph traversal, encoding formats, data‑block tags, repeated‑object reuse, small‑integer inlining, and integer compression, and shows why it offers higher efficiency and compression than text‑based alternatives.
This article explains Java I/O streams as the mechanism for reading and writing data, covering byte and character streams, their principles, usage steps, buffered and conversion streams, serialization, print streams, and compression streams with clear code examples.
The article explains that HSF’s default Hessian2 serializer cannot handle Java 9 immutable collections like Set.of() because it only serializes the writeReplace proxy object and skips the actual elements, leading to a null‑array InvalidObjectException during deserialization.
This guide explains how Msgpack provides a fast, compact binary serialization format for PHP, covering its core concepts, installation methods (PECL, manual compile, Composer), basic and advanced usage examples, performance tips, and important compatibility and security considerations.
This article provides a comprehensive guide to using Jackson for JSON processing in modern Java applications, covering typical scenarios such as object serialization, date formatting, nested structures, dynamic field filtering, tree model manipulation, a complete utility class, and best‑practice recommendations.
When an HSF service receives a parameter created with Java 9's immutable collection factories such as Set.of(), the default Hessian2 serializer drops the collection elements, causing a NullArray InvalidObjectException and resulting in a SERVER_SERIALIZE_ERROR on the server side, which can be avoided by using mutable collections or a compatible serializer.
This article explains how Java’s native serialization can expose plain‑text passwords, illustrates real‑world breaches, and shows how using the transient keyword together with encryption, library replacement, security frameworks, and penetration testing creates a five‑layer defense against serialization attacks.
This article explains how the Go dyno package lets you effortlessly read, modify, and serialize deeply‑nested JSON/YAML structures by providing Get, Set, Delete, Append and conversion utilities that work with map[string]interface{}, map[interface{}]interface{} and []interface{} without using reflection.
This article examines the challenges of using FastJson, FastJson2, Gson, and Kotlinx-serialization to parse Kotlin data classes in Android, explains why crashes occur due to reflection and null-safety issues, and provides step-by-step solutions—including code modifications, ProGuard rules, and library alternatives—to achieve reliable JSON handling.
This article explains why converting a YAML document containing both numeric and string keys (e.g., 1 and "1") to JSON fails in Go using yaml.v3, demonstrates the resulting errors, and shows how to resolve the issue with dyno.ConvertMapI2MapS or alternative libraries, while also comparing behavior in Python and JavaScript.
This guide introduces UltraJSON (ujson), a high‑performance C‑based JSON library for Python, covering why it outperforms the built‑in json module, installation steps, core API usage, advanced features, performance benchmarks, typical use cases, and best‑practice encapsulation for enterprise projects.
This article explains how to handle unknown or dynamic JSON properties in Java using Jackson's @JsonAnySetter to collect them into a Map and @JsonAnyGetter to serialize them back, complete with practical code examples and best‑practice tips.
This article explains how Jackson's @JsonAnySetter and @JsonAnyGetter annotations let Java classes gracefully handle unknown JSON properties by collecting them into a map during deserialization and emitting them as regular fields during serialization, complete with practical code examples and usage tips.
A recent deployment added a log line that caused FastJSON to invoke unexpected methods during serialization, leading to a NullPointerException; this article reconstructs the scenario, analyzes the FastJSON internals, and offers best‑practice annotations to prevent similar bugs.
This comprehensive guide explains what Protocol Buffers are, why they outperform JSON and XML, how to install and configure the library, the supported data types, code generation for multiple languages, practical C++ examples, and typical scenarios such as distributed systems, storage, and network communication.
This article explains how to handle JSON objects with unknown or changing fields in Java by using Jackson's @JsonAnySetter to collect them during deserialization and @JsonAnyGetter to serialize them back, complete with code examples, pitfalls, and a concise analogy.
This article explores Jackson's ObjectMapper in Spring Boot 3, covering basic serialization/deserialization, converting between objects, JSON strings, JsonNode, and collections, custom serializers/deserializers, handling unknown fields, and performance tuning with the Afterburner module and JMH benchmarks.
Java serialization, while convenient for persisting objects, suffers from versioning issues, hidden fields, mutable data snapshots, performance overhead, security vulnerabilities, singleton breaches, final field tampering, external dependencies, maintenance burdens, and format limitations, and the article recommends explicit serialVersionUID, custom methods, and JSON/Protobuf alternatives.
When a JSON payload contains unpredictable fields, Jackson’s @JsonAnySetter and @JsonAnyGetter let you capture those dynamic properties into a Map during deserialization and seamlessly emit them during serialization, eliminating the need for rigid POJOs.
This article explains Google Protocol Buffers' binary serialization, covering its advantages and drawbacks, the encoding mechanisms of tags, varints, ZigZag, embedded and repeated fields, and provides practical best‑practice guidelines for designing robust .proto schemas.
While JSON.parse() and JSON.stringify() are the default methods for JavaScript data serialization, they can become performance bottlenecks and lack support for special types, so this guide explores their limitations and presents strategies such as reviver functions, streaming parsers, binary formats, Web Workers, and incremental loading to improve deserialization efficiency.
This article introduces an open‑source Java JSON framework that uses recursive parsing and reflection to serialize and deserialize objects without third‑party libraries, supports generic and array types, and provides extensible features such as custom annotations, JsonPath, and HTML‑safe output.
This tutorial explains how Objenesis enables Java objects to be instantiated without invoking constructors, covering traditional object creation, the library’s internal mechanisms, Maven setup, usage examples with ObjenesisStd, ObjenesisSerializer, and ObjenesisHelper, advanced scenarios, best practices, and considerations for safe adoption.
This article explains how the json module's default parameter can be used to serialize unsupported Python objects, such as datetime, by providing a custom function or by subclassing JSONEncoder, and includes clear code examples demonstrating both approaches.
This article introduces Python's built‑in json module, explaining how to serialize Python objects to JSON strings and files, deserialize JSON back to Python, and demonstrates common tasks such as pretty‑printing, handling Unicode, working with lists and nested structures, custom encoders, and network responses.
Explore how Python’s built-in __dict__ attribute stores object attributes, enabling introspection, dynamic attribute manipulation, memoization, JSON serialization, custom descriptors, and debugging, while also learning its limitations with slots and built-in types for performance.
This article explains the fundamentals of Java object serialization, compares legacy and modern formats, outlines how to choose the right method, and details common issues such as static fields, transient modifiers, serialVersionUID mismatches, inheritance quirks, and custom serialization techniques with clear code examples.
Serialization in C++ bridges in‑memory objects and persistent or network formats, addressing challenges like byte order, data type compatibility, and complex structures, while the article reviews core principles, binary and text formats, major libraries such as Protobuf, Cereal, Cista++, ThorsSerializer, and offers guidance on selecting and using them effectively.
The article explains how Protocol Buffers (proto3) encode basic and composite types using varint, zigzag, fixed-size and IEEE‑754 formats, describes tag and length field structures, and presents optimization strategies such as selecting size‑efficient types, flattening nested messages, and delta‑encoding to significantly reduce serialized byte‑stream size.
This article explains how the Jackson @JsonView annotation can be used in Spring back‑end projects to selectively serialize object fields, reduce bandwidth, improve security, and handle nested associations by defining view interfaces and applying them on entity fields and controller methods.
This article explains how to use Jackson's @JsonView annotation in Spring Boot 3 to flexibly control JSON output for different REST scenarios, covering basic usage, programmatic view selection, view‑based MVC responses, deserialization restrictions, and default‑inclusion configuration with practical code examples.
This article walks through installing Pydantic, creating basic and nested models, handling validation errors, using default values, defining custom validators, loading settings from environment variables, and serializing models to dictionaries and JSON, demonstrating how Pydantic streamlines data validation in Python.
This article provides a comprehensive guide to using Python's json module for serializing Python objects to JSON format and deserializing JSON data back to Python objects, covering key methods, options, and best practices.
This article provides a comprehensive guide to Java I/O streams, covering the distinction between node (low‑level) and processing (high‑level) streams, byte versus character streams, their superclasses, common implementations, buffering techniques, object serialization, and practical code examples for reading and writing data.
This article explains how Java’s ArrayList uses the transient keyword during serialization to skip the underlying array, reducing redundant data, and details the custom writeObject and readObject methods that ensure only actual elements are stored and restored efficiently.
The article explains the requirements and usage of Jackson’s @JsonAnyGetter and @JsonAnySetter annotations, showing how to serialize dynamic properties into JSON and deserialize them back into a Java object, with complete code examples and step‑by‑step demonstrations.
The author recounts a two‑day investigation of a widespread FastJson failure caused by a Kotlin lambda mistakenly assigned to an Object field, detailing the mixed‑language project background, the puzzling symptoms, step‑by‑step debugging, the root‑cause analysis, and the final resolution.
The article explains serialization and deserialization fundamentals, highlights pitfalls such as ambiguous binary streams and platform‑dependent field sizes, then compares Java’s native ObjectOutputStream, JSON libraries, Hessian binary RPC, and Google’s Protobuf, guiding readers to select the appropriate format based on performance, payload size, and type‑safety needs.
This article explains how to expose a lightweight, dependency‑free client API for a Rust‑based database by defining a simple TCP‑based JSON serialization protocol, detailing non‑functional and functional requirements, the Message and Command structures, and providing a concrete Ping command implementation in Rust.
The article surveys the 22 most downloaded Python packages on PyPI, explaining each library's main purpose, typical use cases, download counts, and providing concise code examples to illustrate how they simplify tasks such as HTTP requests, compatibility, AWS interaction, data parsing, and encryption.
This tutorial walks through Python's built‑in json module, covering import, core concepts, serialization and deserialization of simple and complex structures, file I/O, and how to create custom JSONEncoder and JSONDecoder classes for advanced use cases.
This article provides practical Python code examples for various messaging and serialization tools—including Celery, RQ, Huey, ZeroMQ, kafka‑python, Pika, stomp.py, nats‑py, gRPC, Thrift, Protobuf, Avro, msgpack, and Flatbuffers—demonstrating how to set up producers, consumers, and services for asynchronous processing and data exchange.
This guide explains how to serialize and deserialize Python objects using the pickle, json, and xml.etree.ElementTree modules, and demonstrates practical API testing scenarios—including POST, GET, PUT, DELETE, and nested JSON handling—so you can choose the right format for your needs.
This article explains the fundamentals of JSON serialization and deserialization in Flutter, compares manual and automated approaches, introduces the json_serializable library and its annotations, demonstrates generic handling, custom converters, and tooling to streamline model generation for robust mobile app development.
This article provides a comprehensive guide to Jackson’s most frequently used annotations, core modules, and extension points in Spring Boot, illustrating each feature with concrete Java code examples that show how to customize serialization, deserialization, property handling, and polymorphic type processing.
This article explains five common serialization techniques—Java native serialization, Hessian, JSON, Google Protobuf, and Kryo—detailing their principles, performance characteristics, code examples, and when to choose each for Java backend systems.
After upgrading to JDK 11, a FastJSON serialization bug caused the amount field in Money objects to disappear, leading to failed refunds; this article details the investigation, from classloader quirks and ASM handling to dependency conflicts and the ultimate fix of removing a problematic jar.
The article details a senior architect's investigation of Fastjson problems, including a date format priority bug that behaved differently on Windows and Linux due to an outdated library version, and a circular reference serialization issue resolved by disabling specific serializer features, while offering broader insights on version management and feature control.
This report analyzes performance bottlenecks caused by serialization in a search‑recommendation system, presents detailed measurements of request latency, evaluates multiple optimization strategies—including Redis caching, lazy metric handling, and custom byte‑array serialization—and documents the resulting latency reductions and implementation considerations.
This article provides a thorough tutorial on Python file handling, covering how to open and close files, read and write data, work with absolute and relative paths, use different file modes, copy files, manipulate CSV files, and serialize data with JSON and pickle modules.
This tutorial explores Jackson's rich annotation set in Spring Boot 3.2.5, demonstrating how to serialize and deserialize JSON with built‑in annotations like @JsonAnyGetter, @JsonGetter, @JsonPropertyOrder, and @JsonIgnore, how to create custom annotations, and how to disable annotation processing for fine‑grained control.
During a recent iteration, adding a simple log statement triggered a system exception because Fastjson automatically invoked a custom getter that returned null, leading to an NPE; the article details the root cause, the serialization process, and practical solutions to prevent similar issues.
In Spring Boot you can customize JSON request and response handling by annotating fields with @JsonSerialize/@JsonDeserialize, registering a global ObjectMapper module, adding a PropertyEditor via @ControllerAdvice, creating a custom HttpMessageConverter, or using AOP interception, selecting the approach that matches your project’s complexity.
This article provides a comprehensive guide to Python's json.dumps function, covering basic serialization, formatting options, handling special data types, encoding considerations, performance tweaks, and real‑world usage examples to help developers serialize data efficiently and safely.
This article provides an in-depth review of common Java backend interview questions, covering alternative object creation methods, practical reflection scenarios, serialization techniques, garbage‑collection algorithms, I/O multiplexing mechanisms, network port listening, and troubleshooting tips for server‑client communication issues.
This article explains what Protocol Buffers are, how they work through .proto definitions and the protoc compiler, provides a simple example, shows how protobuf powers gRPC services with Go code, and compares its efficiency and type safety to JSON.
This article explains the principles and implementation of a Java RPC framework, covering service registration with Zookeeper, serialization, compression, network communication via Netty, dynamic proxy generation using reflection and Javassist, and performance considerations, providing extensive code examples for each component.
This article analyzes a FastJSON serialization issue where a getter method is unexpectedly invoked, explains the underlying ASM-generated serializer workflow, details which methods are considered during serialization, and provides best‑practice code annotations to prevent unwanted method execution.
This article surveys Java fundamentals, explaining OOP principles, differences from C++, polymorphism, static/final keywords, abstract classes versus interfaces, generics with type erasure, reflection, exception handling, core data structures, HashMap internals, serialization, key design patterns, and essential language constructs for developers.
This article explains Java deep copy, its differences from shallow copy, key use cases such as data safety and avoiding shared state, and demonstrates three implementation methods—using Cloneable, serialization, and third‑party libraries like Guava—complete with runnable code examples.
This article explains the fundamentals of TCP, why raw TCP communication faces issues like message boundary ambiguity, how HTTP and RPC are built on TCP as application‑layer protocols, and compares their use cases, performance, and evolution to help developers choose the right protocol for their systems.
When Dubbo RPC uses Protostuff serialization, DTO fields declared with ambiguous types that contain non‑standard collections such as subList results can trigger ClassNotFound or null errors during deserialization, so converting these to regular JDK collections (or switching to a more tolerant format like Hessian2/JSON) restores stability.
This article analyzes a FastJSON serialization issue where a getter method is unexpectedly called, explains the underlying ASM‑generated serializer mechanism, details which methods FastJSON invokes during serialization, and proposes using @JSONField(serialize = false) to explicitly exclude methods from the serialization process.
This article explores the fundamentals of TCP communication, explains why raw TCP lacks message boundaries, and compares HTTP and RPC protocols—covering their histories, use cases, service discovery, connection handling, serialization, and performance trade‑offs—to answer why both coexist in modern software architectures.
This newsletter curates recent developer-focused releases and articles, including the open‑source launch of Rolldown, TypeScript 5.4, Storybook 8, performance‑focused TypeScript tips, faster JSON alternatives, reactive front‑end development, a software engineering guide, Figma productivity tricks, and Canvas drawing optimizations.
This article explains why remote procedure call (RPC) is essential for modern distributed services, describes the evolution from monolithic to service‑oriented architectures, and details the core components, communication steps, serialization, service discovery, and full call flow of an RPC framework.
This article explains how to use Python's built‑in json module for serializing and deserializing data, demonstrates sending JSON payloads with the requests library, and covers advanced techniques such as data‑driven testing, JsonPath/JMESPath extraction, JSON Schema validation, and dynamic request body construction for API automation.
This article explains Java's built‑in serialization drawbacks, introduces the open‑source ChronicleWire library as a high‑performance alternative supporting multiple data formats, and provides step‑by‑step code examples for encoding, decoding, and compatibility handling in real‑world Java applications.
Fury is a JIT‑compiled, zero‑copy, multi‑language serialization framework that delivers up to 170× speed improvements over traditional serializers, supports Java, Python, C++, Go, JavaScript, Scala and Rust, and has recently been donated to the Apache Software Foundation after a successful open‑source journey.
This article explains what JSON format is, introduces Python's built‑in json module, and provides step‑by‑step code examples for converting JSON strings to Python objects and serializing Python data structures back to JSON strings.
This article walks Go beginners through designing and implementing a lightweight RPC framework called easyrpc, covering protocol design, message serialization, network communication, graceful server shutdown, client stub generation with reflect.MakeFunc, and concurrent request handling, with full source code on GitHub.
This article presents ten practical Python code examples demonstrating how to implement iteration and serialization magic methods, covering iterable objects, generators, indexed and sliced sequences, length, string and byte representations, as well as JSON, pickle, and XML serialization techniques.
This article presents a curated list of essential Java libraries—including JUnit, Mockito, Jackson, Gson, SLF4J, Log4j2, Apache Commons, Guava, JAXB, Xerces, Apache POI, JavaAssist, Cglib, Eclipse Collections, Trove, Jsoup, Apache MINA, Netty, Lombok, and Testcontainers—explaining their purposes and why senior developers should master them.
This guide presents a curated list of essential Java libraries—including testing, JSON, logging, utility, XML, Excel, bytecode, collections, HTML parsing, encryption, embedded databases, serialization, networking, Lombok, and Testcontainers—that can dramatically improve productivity and code quality for backend development.
This article explains what serialization and deserialization are, why Java classes must implement the Serializable interface, the role of serialVersionUID in version compatibility, and demonstrates with code how transient and static fields behave during object serialization and deserialization.
This article explains the fundamental differences between RPC and HTTP, covering their historical origins, design principles, serialization formats, protocol layers, network communication mechanisms, and appropriate usage scenarios in micro‑service architectures.
This article analyzes a Java serialization issue caused by FastJSON invoking a getter on a null field, explains the underlying ASM‑based serializer generation, and provides best‑practice code examples and annotations to prevent similar bugs in backend development.
