data-validation

Validate API input by defining a schema using Zod, JSON Schema, or Pydantic, then check incoming payloads against it before processing. This prevents invalid or unsafe data from entering your system and provides structured error reporting for client feedback.

Sanitize and encode form inputs using validation and output encoding techniques to remove malicious scripts and unsafe content. Schema validation combined with sanitization blocks injection attacks while preserving legitimate user data.

Yes. Both Zod and Pydantic support type coercion to convert input types, apply default values, and remove unknown properties while validating against your schema, ensuring consistent data transformation across your application.

Schema validators like Zod and Pydantic generate comprehensive, structured error messages that map field paths to specific validation failures. Format and return these errors to clients so they understand exactly which fields failed and why.

Always validate on the backend as your security boundary, regardless of frontend validation. Backend validation prevents malicious or malformed data from entering your system; frontend validation improves user experience but cannot be trusted alone.

Yes. Schema validation applies across JSON payloads, form submissions, and API request bodies. A single schema library handles all formats, enabling consistent validation rules throughout your application.