Dry Validation

Dry Validation - validate and sanitize data s… | Awesome Repos

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.

Open-source alternatives to Dry Validation

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hapijs/joi
hapijs/joi
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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
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sideway/joi
sideway/joi
21,192View on 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
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elysiajs/elysia
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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
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jquense/yup
jquense/yup
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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
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See all 30 alternatives to Dry Validation

dry-rbdry-validation

Features

Open-source alternatives to Dry Validation

hapijs/joi

sideway/joi

elysiajs/elysia

jquense/yup

Star history

Open-source alternatives to Dry Validation

hapijs/joi

sideway/joi

elysiajs/elysia

jquense/yup