valibot-architecture

Valibot's data validation works by flowing input through a pipeline execution engine that processes schemas, actions, and datasets. This modular design dictates how components interact sequentially to validate data and generate issues for invalid inputs.

Valibot schemas and actions are core objects within the internal object model that define validation rules and transformations. Schemas establish the expected data structure, while actions execute specific validation logic during the pipeline execution.

To extend Valibot functionality for complex form validation, you interact with its modular design to create custom schemas and actions. Understanding the internal object model allows developers to inject custom validation logic directly into the pipeline execution engine.

Yes, you can use Valibot's architecture to build a TypeScript data validation system. The internal object model provides the necessary schemas, datasets, and configuration options to construct robust, type-safe validation pipelines for advanced applications.

You need to understand Valibot's datasets and issues configuration when debugging validation failures or building library extensions. Datasets hold the validation state, while issues provide detailed error information generated during the pipeline execution process.

Valibot uses a modular design for its schema validation components to allow granular control over the pipeline execution. This architecture separates schemas, actions, and datasets, enabling developers to extend functionality without modifying the core validation engine.