modelvalidators

ModelValidators are components or services that enforce constraints on data models within software systems. They serve to ensure data integrity by validating inputs, applying business rules, and preventing invalid or inconsistent data from being saved, processed, or exposed through APIs.

Validators can operate at different levels. Field-level validators check individual attributes for formats, ranges, or required values. Cross-field validators enforce rules that involve multiple fields, such as a start date occurring before an end date. Referential and relational validators verify consistency across related models, for example, ensuring a referenced object exists. Validation can be declarative, using annotations or configuration, or imperative, implemented as custom code.

Common implementation approaches include attribute-based validation (annotations or decorators), dedicated validator classes, and schema-based validation (such as JSON Schema). Popular ecosystems supply built-in or extensible validation facilities: Python examples include pydantic with validators; Java commonly uses Bean Validation (JSR 380) with Hibernate Validator; Ruby on Rails offers ActiveModel::Validations; JSON-based schemas enable runtime validation of structured data.

ModelValidators are typically invoked during model lifecycle events, such as create or update operations, and may accumulate multiple errors before responding to the caller. They can raise exceptions, return error collections, or integrate with API error handling to provide user-friendly feedback. Good practice emphasizes avoiding duplication across layers and focusing validators on the model’s truth constraints rather than presentation concerns.

Related concepts include data validation, data integrity, and cross-field or relational validation.