Pros and cons of pydantic compared to json schemas

As far as I understand Pydantic and Json Schemas provide similar functionality - both can be used for validating data outputs.

I am interested to understand the pros and cons of using each one. A few questions I am interested in:

• Are there any differences in accruacy between them?

• Which one is faster to implement in terms of development time?

• Is there any functionality difference between the two? i.e. features one supports, that the other doesn't?

These are only examples of questions I am thinking about, I would love to know more about the pros and cons also.

While both Pydantic and Json Schema are used to verify data adheres to a certain format they serve different use-cases:

• Json Schema: a tool for defining JSON structures independent of any implementation or programming language.
• Pydantic: a python specific tool for validating input data against a pydantic specific definition

You can find many implementations of Json Schema validator in many languages those are the tools that you might want to check out in a 1:1 comparison to pydantic. However, pydantic understands Json Schema: you can create pydantic code from Json Schema and also export a pydantic definition to Json Schema. They should be equivalent from a functional perspective. You can find a type mapping in the pedantic docs.

So, which should you use? Your use-case is important but most likely its not either/or. If you're python-only and prefer to define your schema in python directly definitely go for pydantic. If you need to exchange the schemas across languages or want to handle schemas generated somewhere else, you can add Json Schema on top and pydantic will be able to handle it.