zod VS ajv

While Speakeasy also includes unit tests, they're organized at the root of the /tests directory with less granular separation. Its approach emphasizes documentation and type definitions, with extensive model documentation in /docs/models/. The SDK uses runtime validation through zod, which requires developers to carefully handle error objects when the API returns invalid data. This creates a different balance between compile-time and runtime type safety.

I used zod-bird to integrate Tinybird APIs (pipes and events) with Next.js. It's a wrapper around the Tinybird APIs that validates pipe results using zod schemas.

One of the most basic applications of ReScript Schema is parsing - Accepting unknown JavaScript data, validating it, and returning the result of your desired type. There are dozens of such libraries, and the most popular ones are Zod, Valibot, Runtypes, Arktype, Typia, Superstruct, Effect Schema, and more. Also, even though this is slightly different, validation libraries like Ajv, Yup, and others also stand really close.

…but that’s a lot of no fun, dangerous work. Better to use a library that has already solved this problem like Zod or ArkType. It’ll ensure the types match up, and if not, give you an error response that _somewhat_ gives you a clue as to why the decoding went wrong, way more thorough and verbose than JSON.parse’s not so great runtime error messages.

As you can see, encoding and decoding in TypeScript can make your code safer, reduce the amount of type narrowing you need to do, especially if you use Zod. For consumers of your code and api’s, it gives them the flexibility of utilizing your API’s while providing their own types which includes their own encoders and decoders in a type-safe way. TypeScript can safely ensure all erros are typesafe, and those error scenarios are handled in developers who use your code.

🔗 https://zod.dev/

Zod is a TypeScript-first library for schema declaration and validation, offering a simple API to define, parse, and validate data structures with runtime type safety. It supports detailed error handling, and is ideal for validating inputs, APIs, and complex data in modern applications.

This feature is a game-changer because it guarantees that the AI's response will match your specified format. No more hoping the AI will format things correctly or writing complex parsing logic—you define a schema, and OpenAI ensures the output matches it exactly. This not only simplifies downstream processing but also allows you to use libraries like Zod to validate and enforce the schema of your output.

Zod

One of the most basic applications of ReScript Schema is parsing - Accepting unknown JavaScript data, validating it, and returning the result of your desired type. There are dozens of such libraries, and the most popular ones are Zod, Valibot, Runtypes, Arktype, Typia, Superstruct, Effect Schema, and more. Also, even though this is slightly different, validation libraries like Ajv, Yup, and others also stand really close.

AJV for validating JSON responses from the speedtest cli

Tools like AJV (Another JSON Schema Validator) in JavaScript or the Python jsonschema library can help you validate JSON data against a schema.

Once your schema is ready, the AJV library can be used to apply it:

To simply validate a JSON Patch request body, the AJV library and a JSON schema can be used:

Speed and complete JSON schema compliance are the main priorities of AJV. Though it lacks the user-friendly APIs that Zod or VineJS has, it's great for validating JSON data, especially in APIs. But for tasks that require high efficiency, like validating huge JSON datasets, it's ideal.

To the article's point, many/most JavaScript projects are not optimised and better performance can be achieved with just JavaScript, and yes, JavaScript engines are becoming faster. However, no matter how much faster JavaScript can get, you can still always get faster with other system languages.

I work on high-performance stuff as a C++ engineer, currently working on an ultra fast JSON Schema validator. We are benchmarking against AJV (https://ajv.js.org), a project with a TON of VERY crazy optimisations to squeeze out as much performance as possible (REALLY well optimised compared to other JavaScript libraries), and we still get numbers like 200x faster than it with C++.

I'm not 100% sure, they most likely scraped the author emails of all NPM packages that (transitively) depend on ajv. Here's the GitHub issue from back then: https://github.com/ajv-validator/ajv/issues/1202

Ajv’s documentation is available here.