awesome-repositories.com
Blog
MCP
awesome-repositories.com

Descubre los mejores repositorios open-source con nuestra búsqueda potenciada por IA.

ExplorarBúsquedas curadasAlternativas open-sourceSoftware autohospedableBlogMapa del sitio
ProyectoAcerca deCómo clasificamosPrensaServidor MCP
Aviso legalPrivacidadTérminos
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
dry-rb avatar

dry-rb/dry-validation

0
View on GitHub↗
1,422 estrellas·193 forks·Ruby·MIT·16 vistasdry-rb.org/gems/dry-validation↗

Dry Validation

Dry-validation es una biblioteca de Ruby diseñada para definir esquemas con seguridad de tipos y reglas de validación complejas para verificar y sanitizar estructuras de datos de entrada. Proporciona un framework formal para construir lógica de validación modular, asegurando que la información entrante cumpla con requisitos comerciales y formatos de datos específicos antes de ser procesada por una aplicación.

La biblioteca utiliza un lenguaje específico de dominio (DSL) para declarar reglas de validación, que luego se analizan en objetos ejecutables. Destaca por un sistema basado en macros que agrupa la lógica de validación común en atajos reutilizables, junto con un modelo de composición recursiva que permite a los desarrolladores anidar objetos de validación para construir estructuras complejas y jerárquicas. Este enfoque permite la creación de lógica consistente y modular que evita la duplicación de código en aplicaciones grandes.

Más allá de la definición de esquema central, la biblioteca incluye un pipeline de coerción de tipos que transforma la entrada bruta en formatos esperados y un sistema de agregación de errores estructurado que mapea las fallas a rutas de entrada específicas. Admite ganchos de configuración para la integración de dependencias externas y proporciona herramientas para sanitizar datos, lo que la hace adecuada para aplicar estándares en solicitudes de API entrantes y objetos de datos complejos.

Features

  • Data Validation Libraries - Provides a library for defining type-safe schemas and complex validation rules to verify and sanitize input data structures in Ruby.
  • Schema Definitions - Provides tools to define formal rules and schemas to verify that incoming information matches expected formats.
  • Data Schema Validation - Defines formal rules and schemas to verify that incoming information matches expected formats and business requirements.
  • Schema Definition Frameworks - Builds modular and composable validation logic that ensures incoming information meets specific business requirements.
  • Coercion Pipelines - Transforms raw input data into expected types during the validation process to ensure consistent downstream information.
  • Schema Validation Libraries - Allows developers to combine and nest multiple validation rules to create modular logic.
  • Reusable Rule Logic - Bundles common validation logic into reusable shortcuts to simplify the definition of repetitive business rules.
  • Complex Structure Validation - Supports defining detailed rules for nested or complicated data objects to ensure structural correctness.
  • Data Sanitization Utilities - Converts raw input into consistent types and formats while reporting clear error messages for invalid entries.
  • Data Validation and Sanitization - Cleans and converts raw input into consistent types and formats during the validation process.
  • Boolean Predicates - Executes atomic logic checks against input data by mapping field keys to a library of reusable boolean verification methods.
  • DSL-Driven Validations - Provides a domain-specific language to declare validation rules and data structures that are parsed into executable objects.
  • Validation Error Reporters - Reports validation errors with clear messages and custom details to help users understand input failures.
  • Validation Error Aggregators - Collects validation failures into a structured object that maps specific input paths to descriptive error messages.
  • Request Validation - Ensures that incoming data from external clients meets specific standards before it is accepted by backend services.
  • Schema Composition Libraries - Supports nesting validation objects within one another to build complex hierarchical structures from modular components.
  • Validation Logic Decoupling - Composes and nests reusable validation rules to keep code clean and prevent duplication.
  • Reusable Validators - Provides shared validation shortcuts that bundle common rules together for consistent application across the codebase.

Historial de estrellas

Gráfico del historial de estrellas de dry-rb/dry-validationGráfico del historial de estrellas de dry-rb/dry-validation

Búsqueda con IA

Explora más repositorios increíbles

Describe lo que necesitas en lenguaje sencillo: la IA clasifica miles de proyectos open-source curados por relevancia.

Start searching with AI

Colecciones destacadas con Dry Validation

Colecciones seleccionadas manualmente donde aparece Dry Validation.
  • Herramientas de validación de esquemas de datos
  • una librería para validación de atributos de modelos
  • librería para gestionar archivos de configuración de aplicaciones

Alternativas open-source a Dry Validation

Proyectos open-source similares, clasificados según cuántas características comparten con Dry Validation.
  • hapijs/joiAvatar de hapijs

    hapijs/joi

    21,192Ver en GitHub↗

    Joi is a JavaScript data validation library used to define schemas that validate, cast, and sanitize data objects. It functions as an object schema validator and parser, ensuring that input data matches specific types and formats before it is processed by an application. The library features a conditional validation engine capable of dynamic schema enforcement, where validation logic and dependencies change based on the values of other keys within an object. It also serves as a data casting and sanitization tool, transforming input values into target types and removing sensitive keys from the

    JavaScripthapijavascriptschema
    Ver en GitHub↗21,192
  • sideway/joiAvatar de sideway

    sideway/joi

    21,192Ver en GitHub↗

    Joi is a JavaScript data validation library used to define schemas that ensure the structure and data types of objects remain consistent. It functions as a schema-based validator and object schema definition tool, preventing invalid information from entering an application by checking data against predefined constraints and rules. The library employs a chainable fluent interface and a constraint-based validation engine to build complex validation pipelines. It utilizes recursive tree traversal to validate nested data structures and a type-coercion pipeline to transform input values into the t

    JavaScript
    Ver en GitHub↗21,192
  • elysiajs/elysiaAvatar de elysiajs

    elysiajs/elysia

    18,531Ver en GitHub↗

    Elysia is a high-performance TypeScript web framework designed for building type-safe backend services. It provides a modular, plugin-based architecture that allows developers to compose server logic, middleware, and validation schemas into scalable application instances. By leveraging native web standards, the framework ensures portability across diverse JavaScript runtimes, including Node.js, Deno, and various edge computing environments. The framework distinguishes itself through its focus on end-to-end type safety, automatically synchronizing request and response definitions between the s

    TypeScriptbunframeworkhttp
    Ver en GitHub↗18,531
  • jquense/yupAvatar de jquense

    jquense/yup

    23,673Ver en GitHub↗

    Yup is a JavaScript schema validation library used to define data shapes and validate runtime values. It functions as an object schema validator and a data coercion engine, allowing developers to transform raw input values into desired types before performing validation checks. The library is distinguished by its support for dynamic schema validation, where rules can be adjusted at runtime based on sibling field values or external context. It also enables recursive data structuring for polymorphic fields and provides a system for extracting static TypeScript interfaces from runtime schema def

    TypeScript
    Ver en GitHub↗23,673
Ver las 30 alternativas a Dry Validation→

Preguntas frecuentes

¿Qué hace dry-rb/dry-validation?

Dry-validation es una biblioteca de Ruby diseñada para definir esquemas con seguridad de tipos y reglas de validación complejas para verificar y sanitizar estructuras de datos de entrada. Proporciona un framework formal para construir lógica de validación modular, asegurando que la información entrante cumpla con requisitos comerciales y formatos de datos específicos antes de ser procesada por una aplicación.

¿Cuáles son las características principales de dry-rb/dry-validation?

Las características principales de dry-rb/dry-validation son: Data Validation Libraries, Schema Definitions, Data Schema Validation, Schema Definition Frameworks, Coercion Pipelines, Schema Validation Libraries, Reusable Rule Logic, Complex Structure Validation.

¿Qué alternativas de código abierto existen para dry-rb/dry-validation?

Las alternativas de código abierto para dry-rb/dry-validation incluyen: hapijs/joi — Joi is a JavaScript data validation library used to define schemas that validate, cast, and sanitize data objects. It… sideway/joi — Joi is a JavaScript data validation library used to define schemas that ensure the structure and data types of objects… elysiajs/elysia — Elysia is a high-performance TypeScript web framework designed for building type-safe backend services. It provides a… jquense/yup — Yup is a JavaScript schema validation library used to define data shapes and validate runtime values. It functions as… ianstormtaylor/superstruct — Superstruct is a JavaScript and TypeScript data validation library used to verify that data structures match defined… ajv-validator/ajv — Ajv is a high-performance data validation framework that compiles JSON schemas into optimized, standalone JavaScript…