This article explains the structure of Chinese citizen ID numbers and provides a PHP function that validates both 15‑digit and 18‑digit IDs by checking format, birthdate correctness, and computing the checksum according to ISO 7064, accompanied by example usage.
This article provides an extensive set of regular expressions for validating various numeric formats, character sets, special requirements such as email, URLs, phone numbers, dates, IP addresses, and other common patterns, accompanied by clear explanations and usage examples for developers.
This article introduces the PHP Composer package "jxlwqq/id-validator", detailing its capabilities to validate Chinese resident ID numbers, upgrade 15‑digit IDs to 18‑digit, generate synthetic IDs, retrieve detailed personal information, and explains installation, usage examples, and the structure of the returned data.
The article explains PHP's is_nan() function, its signature, parameters, return values, and provides a code example showing how it identifies non‑numeric results such as NaN and returns true, making it useful for backend validation.
This article demonstrates how to build an automatic address recognition feature for user input by combining Laravel backend controllers, repository services, and jQuery AJAX calls to parse, validate, and populate name, mobile, and detailed address fields.
An extensive compilation of regular expressions covering numeric, character, email, URL, phone, ID, password, date, IP, and other validation patterns, complete with examples and explanations, providing developers a ready reference for implementing robust input validation across various programming contexts.
This article provides a concise Laravel validation cheat sheet that explains the purpose of the Validation helper, shows common code examples for creating and extending validators, and lists the most frequently used validation rules with their syntax for quick reference.
This comprehensive guide explains Laravel's powerful form validation features, covering built‑in validation rules, quick validation examples, route and controller setup, handling validation errors, form request classes, custom error messages, conditional rules, array validation, and how to create custom validation rules using rule objects, closures, and extensions.
This article explains how to refactor Spring MVC controller code by introducing a unified response structure, handling String response issues with ResponseBodyAdvice, applying JSR‑303 validation, creating custom validation annotations, and implementing custom exceptions with global exception handling to produce cleaner, more maintainable backend services.
This article provides practical guidance on data cleaning, covering the importance of data wrangling, using assertions, handling incomplete records, checkpointing, testing on subsets, logging, optional raw data storage, and validating the cleaned dataset to ensure reliable downstream analysis.
This article demonstrates how to transform overly complex Spring Boot controllers—filled with repetitive try‑catch blocks and manual field checks—into clean, maintainable code by applying @Valid validation, reducing boilerplate, and implementing a centralized exception‑handling strategy.
This article explains how to build a clean, maintainable Controller layer in Java Spring by separating responsibilities, using unified response structures, applying ResponseBodyAdvice for automatic wrapping, implementing parameter validation with JSR‑303, and handling custom exceptions through centralized advice, illustrated with comprehensive code examples.
This article provides a comprehensive guide to standardizing the Spring Boot controller layer by explaining how to receive parameters, define unified status codes, apply validation annotations, wrap responses consistently, and handle exceptions globally, all illustrated with practical Java code examples.
This article explains how to structure a Spring Boot controller by describing the four parts of a request, demonstrating elegant parameter validation, implementing a unified response wrapper with status codes, and handling both validation and business exceptions through centralized advice and custom exception classes.
This article presents a step‑by‑step tutorial on building robust Spring Boot backend APIs, covering environment setup, parameter validation techniques, global exception handling, unified response structures, optional response wrapping, API versioning via path or header, and comprehensive security measures such as token authentication, timestamp checks, request signing, replay protection, and HTTPS.
This article provides a detailed tutorial on Spring Validation, covering basic dependency setup, requestBody and requestParam/PathVariable validation, advanced techniques such as group, nested, collection and custom validation, programmatic validation, fail‑fast mode, the difference between @Valid and @Validated, and the underlying implementation mechanisms within Spring MVC.
This article explains how to replace verbose manual if‑else checks with concise javax.validation annotations in Spring Boot, covering built‑in constraints, dependency setup, custom validators, validation groups, and global exception handling to create a unified, maintainable validation workflow.
This article explains how to structure a Spring Boot controller layer by separating URL, request method, request data, and response data, then introduces unified status‑code packaging with ResultVo, parameter validation using @Validated, and centralized exception handling with @RestControllerAdvice and AOP to produce consistent API responses.
The article explains how to simplify Spring MVC controller code by introducing a unified response wrapper, handling String return types with ResponseBodyAdvice, adjusting HttpMessageConverter order, applying JSR‑303 validation for @RequestParam, @PathVariable and @RequestBody, creating custom validation annotations, and implementing global exception handling for consistent API responses.
The article demonstrates how to transform overly complex Spring Boot controllers—filled with repetitive validation and business logic—into clean, maintainable code by using @Valid annotations, concise validation rules, and a centralized exception handler, effectively halving the code size and improving readability.