sideway/joi
Joi
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 target schema type before validation.
The system handles various validation domains, including API request validation for HTTP bodies and parameters, configuration schema enforcement for environment variables, and user input sanitization. It generates detailed reports via rule-to-error mapping and uses stateless schema definitions to allow a single schema instance to process multiple data inputs.
Features
- Data Schema Validation - Implements a schema-based validation engine to enforce type safety and data consistency for JavaScript objects.
- Data Validation Schemas - Provides a system for validating data by comparing input values against predefined rule-based schemas and type requirements.
- Data Validation Libraries - Provides a comprehensive library for defining schemas to validate the structure and data types of JavaScript objects.
- Data Schema Definitions - Decouples rule configuration from execution through stateless schema definitions, allowing a single schema to process multiple inputs.
- Data Type Validation - Provides a validation engine that checks input data against a predefined tree of type requirements and logic rules.
- Object Schema Definitions - Provides a comprehensive system for defining required fields and data types to ensure object structure consistency.
- JavaScript Validators - Ensures JavaScript objects follow specific types and constraints before being processed by the application.
- Coercion Pipelines - Transforms input values into target schema types via a coercion pipeline before applying validation rules.
- Structural Data Validators - Validates complex, recursive data objects by ensuring every level of a nested schema meets its constraints.
- Error Mapping Strategies - Maps failed validation constraints to human-readable error messages to provide detailed reports for invalid data.
- Error Reporting - Generates human-readable reports by associating failed validation rules with specific error templates.
- Fluent Interfaces - Implements a fluent interface that allows validation rules to be chained together for more readable schema definitions.
- Data Structure Traversers - Traverses nested data structures recursively to ensure every leaf node meets its specific schema constraints.
- Request Validation - Validates incoming HTTP request bodies and parameters to prevent malformed data from reaching server logic.
- Data Validation - Object schema description and validation language.
