Zod
A TypeScript-first schema validation library.
Define a schema once, parse unknown input, and infer the static type with z.infer.
Backend & APIs
What is the difference between Zod and Pydantic?
Both validate untrusted data at runtime and produce typed results: Zod is the TypeScript schema library, Pydantic is the Python model library behind FastAPI.
- Technologies
- 2
- Difference questions
- 50
What each one is
Pydantic
A Python data validation library using type hints on model classes.
BaseModel classes validate and coerce data, serialise to JSON and power FastAPI and settings management.
At a glance
| Aspect | Zod | Pydantic |
|---|---|---|
| Language | TypeScript | Python |
| Defines | Schemas | Model classes |
| Static types | Inferred from schema | From type hints |
| Coercion | Opt-in (z.coerce) | On by default (lax mode) |
| Common with | Next.js, tRPC, forms | FastAPI, settings, LLM output |
The 10 most-asked difference questions
Subjective questions 10
1What is the main difference between Zod and Pydantic?Asked almost every time
Both validate untrusted data at runtime and give you typed results. Zod is a TypeScript-first schema library where you build schemas with functions and infer static types from them; Pydantic is a Python library where you declare model classes with type hints and it validates and converts data into model instances.
2How do you get static types from each?Asked almost every time
In Zod, z.infer<typeof schema> derives the TypeScript type from the schema, so one definition serves both. In Pydantic, the model class itself is the type, and editors and type checkers understand its annotated fields.
3How does coercion differ by default?Asked almost every time
Zod is strict by default: a string '5' fails a z.number() unless you use z.coerce.number(). Pydantic's default lax mode converts compatible inputs, such as '5' to 5, unless you enable strict mode.
4Where is each commonly used?Asked almost every time
Zod is common in TypeScript apps: API input validation, Next.js Server Actions, tRPC, forms and environment variables. Pydantic powers FastAPI request and response models, settings management and validation of LLM structured output in Python.
5Why do both libraries exist if TypeScript and Python already have types?Asked almost every time
Static types are not checked at runtime: TypeScript types are erased and Python type hints are not enforced. Data from users, APIs and files must be validated when the program runs, which is what both libraries do.
6How do you validate data in each?Very often asked
Zod: schema.parse(data) returns typed data or throws a ZodError, and safeParse returns a success flag and result without throwing. Pydantic: Model(**data) or Model.model_validate(data) returns an instance or raises a ValidationError.
7How are errors reported?Very often asked
Zod's ZodError has an issues array with path, code and message per problem. Pydantic's ValidationError lists errors with location, type and message, and FastAPI turns them into 422 responses.
8How do you add custom validation rules?Very often asked
Zod uses refine and superRefine for custom checks and transform for converting values. Pydantic uses field_validator and model_validator decorators with before or after modes.
9How does serialisation differ?Very often asked
Pydantic models serialise with model_dump and model_dump_json, with aliases and exclusions. Zod focuses on parsing input; output shaping is usually plain objects or a separate schema.
10How does each generate JSON Schema?Very often asked
Pydantic generates JSON Schema with model_json_schema, used by FastAPI for OpenAPI. Zod can produce JSON Schema through its built-in conversion in newer versions or companion libraries.
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