JSON-Schema Faker VS datafaker

There’s also json-schema-faker which is pretty cool.

https://github.com/json-schema-faker/json-schema-faker

I built a CSV generator which I then use as a test data source for a dsv library on that principle and another API generator based on schema. Something that might be additionally helpful is json-schema-faker, as you can probably convert you primary record (DB schema) to json-schema then just generate tons of data.

I only know https://github.com/json-schema-faker/json-schema-faker for JS, not Java though.

Hell, i was using this one earlier today; just kills me that people think this is acceptable.

The payload object contains a reference to a JSON Schema object that describes the properties of the event. This allows the consumer to know exactly how to define the event when publishing or how to write code that consumes a subscribed event. There are even tools online that generate examples from JSON Schema (and vice versa).

The class-validator / class-transform looks really nice for formatting/validation but there is also joi. suretype is attractive since theoretically typeconv could generate jsonSchema for json-schema-faker and Open API docs.

I've been using Fake your JSON-Schemas! (json-schema-faker.js.org), but it does not consider if-then-else rules in its generation process.

Looks like that link doesn't actually go where it says, try this https://github.com/datafaker-net/datafaker

Give it a try https://github.com/datafaker-net/datafaker

Looks a lot like DataFaker Any pros and cons or differences compared to this?

Great library, and thanks for sharing. I maintain something add similar but different (https://www.datafaker.net), and it would be interesting to be able to use these libraries together for example.

For example, I run a project (https://www.datafaker.net), which is currently a Java application, but we'd like to extend it with a Kotlin module.

I'm running a project myself, https://www.datafaker.net, a project to generate real looking test data.