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jquense avatar

jquense/yup

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23,673 stele·941 fork-uri·TypeScript·MIT·9 vizualizări

Yup

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 definitions to ensure type safety.

The framework covers broad capability areas including data coercion and casting, multi-language error handling for localized messages, and the definition of complex object shapes. It supports the creation of custom validation rules, the management of array elements, and the ability to strip unknown properties from objects.

Features

  • Data Validation Schemas - Provides a declarative system for defining data structures and enforcing validation rules on input data.
  • Runtime Value Validation - Checks if a value matches a schema and returns the result or throws detailed validation errors.
  • Schema Validation - Provides a comprehensive system for verifying data structures and object shapes against predefined schemas.
  • Data Coercion Utilities - Implements mechanisms for converting data between types during validation and processing pipelines.
  • Data Schemas - Creates immutable blueprints that specify the required shape, type, and constraints of data.
  • Data Type Coercion - Implements a pipeline of coercion rules to transform input data into the desired schema shape.
  • Coercion Pipelines - Transforms input data through a sequence of coercion rules before performing correctness assertions.
  • Schema Type Synchronization - Automatically generates shared TypeScript type definitions from runtime schemas to ensure consistency.
  • Data Validation Libraries - Ships a library for parsing and validating data structures against predefined schemas.
  • Conditional Validation Rules - Provides logic for enforcing field requirements based on the state or values of sibling fields.
  • Cross-Field Validators - Links fields so that the validation or casting of one field depends on the value of another.
  • Schema Validation Libraries - Provides a runtime data validation library for enforcing data structure integrity and validation rules.
  • Type Conversion and Casting - Provides a coercion engine to transform raw input values into desired types before validation.
  • Conditional Logic Engines - Evaluates runtime expressions to dynamically adjust schema rules based on input data.
  • Dynamic Validation Rules - Provides logic for performing runtime validation checks that adjust based on external context or sibling fields.
  • Custom Validation Rules - Allows the addition of user-defined test functions to the validation chain for complex logic.
  • Data Type Validation - Performs runtime type checking against schema definitions to ensure data conforms to expected structures.
  • Object Shape Validation - Enforces specific property requirements on objects to ensure they contain expected data fields and types.
  • Field Presence Constraints - Controls whether a field is required, optional, or allows null values to define data strictness.
  • Schema Validation Frameworks - Provides a lightweight library for validating data structures using functional composition.
  • TypeScript Type Definitions - Extracts static TypeScript interfaces from runtime schema definitions to ensure end-to-end type safety.
  • Schema-Driven Type Inference - Extracts static TypeScript interfaces from runtime schema definitions to ensure synchronization between validation and type safety.
  • Input Shape Manipulation - Supports custom manipulation functions to change the shape of an input during the casting process.
  • Error Message Metadata - Attaches configuration and descriptive keys to schemas to produce localized or custom validation messages.
  • Numeric Comparison Validators - Enforces numeric limits including minimum and maximum values through comparison validators.
  • Validation Integrations - Integrates with schema validation logic to ensure that parsed values maintain data integrity via tests.
  • Value Transformations - Allows the application of a sequence of custom functions to alter a value during the casting phase.
  • Fluent Interface Patterns - Implements a chainable method interface for building immutable validation blueprints.
  • Property Strictness - Ensures objects contain only specified keys by stripping unknown properties or throwing errors.
  • Array Schema Validation - Defines the required type for array elements and constrains array length and content.
  • Custom Validation Extensions - Adds custom methods to core schema types to create reusable, domain-specific validation logic.
  • Schema Default Values - Assigns fallback values when the casting process produces an undefined result.
  • Localized Error Feedback - Customizes default validation messages using dictionaries for multi-language support.
  • Localized Error Messages - Customizes and localizes validation error messages using dictionaries to support internationalized user interfaces.
  • Recursive Data Schemas - Creates schemas that evaluate at runtime to support polymorphic fields or recursive tree structures.
  • Recursive Schema Resolvers - Resolves schema references during execution to support polymorphic fields and recursive tree structures.
  • String Formatting Utilities - Enforces string requirements such as length, regex matches, and specific formats like email or UUID.
  • Validation Error Handlers - Provides utilities for defining and customizing validation error messages and feedback logic.
  • Additional Property Filtering - Removes fields from an object that are not explicitly defined in the validation schema.
  • Data Validation - Object schema validation library.
  • Data Validation - Minimalist object schema validation.
  • Form Validation - Schema builder for runtime value parsing and validation.
  • Type Checkers - JavaScript schema builder and validator.

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Întrebări frecvente

Ce face jquense/yup?

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.

Care sunt principalele funcționalități ale jquense/yup?

Principalele funcționalități ale jquense/yup sunt: Data Validation Schemas, Runtime Value Validation, Schema Validation, Data Coercion Utilities, Data Schemas, Data Type Coercion, Coercion Pipelines, Schema Type Synchronization.

Care sunt câteva alternative open-source pentru jquense/yup?

Alternativele open-source pentru jquense/yup includ: open-circle/valibot — Valibot is a modular, type-safe schema library for validating and parsing structural data in TypeScript environments. hapijs/joi — Joi is a JavaScript data validation library used to define schemas that validate, cast, and sanitize data objects. It… ajv-validator/ajv — Ajv is a high-performance data validation framework that compiles JSON schemas into optimized, standalone JavaScript… ianstormtaylor/superstruct — Superstruct is a JavaScript and TypeScript data validation library used to verify that data structures match defined… yiminghe/async-validator — async-validator is a JavaScript schema validation library and asynchronous data validation engine. It verifies complex… colinhacks/zod — Zod is a TypeScript-first schema declaration and validation library designed to ensure end-to-end data integrity. It…

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