zod

To validate an incoming JSON payload, define a TypeScript schema and use safeParse() to catch validation errors early while ensuring data integrity. This method returns a result object instead of throwing, allowing graceful error handling for invalid API request bodies.

The best way to handle custom validation and data transformation is by implementing schema refinements and transforms. Refinements add custom validation rules to schemas, while transforms modify parsed data output, allowing you to distinguish input and output types for complex processing.

Type inference works by leveraging the z.infer utility to automatically generate TypeScript types from your schema definitions. This ensures your parsed data strictly matches the schema structure, distinguishing input and output types automatically when transforms are applied to the data.

Yes, you can use TypeScript schema validation for asynchronous validation and form error display. The library supports asynchronous validation rules and provides strategies for custom error messages, internationalization, and displaying user-friendly validation errors directly in form inputs.

You create reusable object schemas and recursive types by using schema composition techniques like intersections and discriminated unions. This approach allows you to build complex, nested data models, apply strict or strip modes for unknown keys, and manage partial updates efficiently.

Using z.any() in schema definitions severely limits type safety and data integrity by bypassing validation rules entirely. To maintain robust TypeScript validation and optimize both bundle size and validation speed, you should avoid z.any() and apply specific string validations and strict object modes.