schematic VS awesome-jsonschema

schematic: Last updated in 2021. "It can be thought of as a subset of JSON Schema", "Schematic schemas can be exported to json-schema".

Thanks for Cap'n Proto. I think the article is clearly indicating the issues that a wider community of conventional type systems in their mainstream languages is not fully aware of. And I disagree with your comments. Firstly, I don't like that you are labelling the author of the article as a "PL design theorist who doesn't have a clue":

> his article appears to be written by a programming language design theorist who, unfortunately, does not understand (or, perhaps, does not value) practical software engineering.

I'm not the author, but they mention their prior industrial experience at Google with protobufs.

I'm not a PL theorist either, and I see that you don't fully understand the problems of composability, compatibility, and versioning and are too eager to dismiss them based on your prior experience with inferior type suystems. And here's why I think it is:

> > This is especially true when it comes to protocols, because in a distributed system, you cannot update both sides of a protocol simultaneously. I have found that type theorists tend to promote "version negotiation" schemes where the two sides agree on one rigid protocol to follow, but this is extremely painful in practice: you end up needing to maintain parallel code paths, leading to ugly and hard-to-test code. Inevitably, developers are pushed towards hacks in order to avoid protocol changes, which makes things worse.

You are conflating your experience with particular conventional tooling with the general availability of superior type systems and toolings out there. There's a high demand in utilising their properties in protocol design today.

Version negotiation is not the only option available to a protocol designer. It is possible to implicitly migrate and up/down-cast schemas in semi-automated way. Example [1]

> This seems to miss the point of optional fields. Optional fields are not primarily about nullability but about compatibility. Protobuf's single most important feature is the ability to add new fields over time while maintaining compatibility.

There are at least two ways to achieve compatibility, and the optional fields that expand a domain type to the least common denominator of all encompassing possibilities is the wrong solution to this. Schema evolition via unions and versioning is the proper approach that allows for automatic resolution of compatibility issues.

> Real-world practice has also shown that quite often, fields that originally seemed to be "required" turn out to be optional over time, hence the "required considered harmful" manifesto. In practice, you want to declare all fields optional to give yourself maximum flexibility for change.

This is false. In practice I want a schema versioning and deprecation policies, and not ever-growing domain expansion to the blob of all-optional data.

> It's that way because the "oneof" pattern long-predates the "oneof" language construct. A "oneof" is actually syntax sugar for a bunch of "optional" fields where exactly one is expected to be filled in.

this is not true either, and it doesn't matter what pattern predates which other pattern. Tagged unions are neither a language construct nor a syntax sugar, it's a property of Type Algebra where you have union- and product-compositions. Languages that implement Type Algebra don't do it to just add another fancy construct, they do it to benefit from mathematical foundations of these concepts.

> How do you make this change without breaking compatibility?

you version it, and migrate over time at your own pace without bothering your clients too often [1]

[1] https://github.com/typeable/schematic#migrations

Truth. Zod is comparable to JSON Schema plus AJV, and it doesn't compare well at all. Your Zod code is all locked inside TypeScript so not only can it not be shared to any other language in your stack but it also cannot be serialized, which introduces many limitations. You also miss out on all the JSON Schema ecosystem tooling. (1, 2) For example the intellisense you get in VS Code for config files is powered by JSON Schema and schemastore.

The very first line of text below the header on the json-schema.org homepage is:

The framework's official website mentions a number of pros of FastAPI. In my opinion, the most useful features from a microservice perspective are: the simplicity of code (easy to use and avoid boilerplate), high operational capacity thanks to Starlette and Pydantic and compatibility with industry standards - OpenAPI and JSON Schema.

I've used Felte to reduce form boilerplate. Felte supports several different validation libraries like Zod. I actually used a custom validation function with ajv (which uses JSON schema).

(There is already a JSON Schema definition at https://json-schema.org/)

Like you said - standard XML isn't terrible. Adding on an XSD isn't terrible, because now you can enforce structure and datatypes on files provided by outside parties. Creating an XSLT is much more of a mental challenge, and probably should be left to tools to define.

Anything beyond those technologies is someone polishing up their resume.

While the aws-sdk is being installed to simulate DynamoDB locally, let me explain a few things about this command. First Comment will be the name of the model the scaffold creates. This model will be codified under app/models/schemas/comment.mjs as a JSON Schema object. Each of the parameters after Comment will be split into a property name and type (e.g. property name “subject”, property type “string”). This JSON Schema document will be used to validate the form data both on the client and server sides.

What you are looking is called Json-schema. Have a look at the implementations page, which will give you an idea of what you can do with json-schema, which also includes UI rendering.