awesome-jsonschema
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awesome-jsonschema
- YAML or JSON files that are typed?
- Parse, Don't Validate (2019)
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The Last Breaking Change | JSON Schema Blog
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:
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How to use FastAPI for microservices in Python
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.
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How to handle forms in a good way?
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).
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A Brief Defense of XML
(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.
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On the seventh day of Enhancing: Forms
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.
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Server Sent UI Schema Driven UIs
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.
- Tool to document Firestore 'schema'
jc
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Xonsh: Python-powered, cross-platform, Unix-gazing shell
https://github.com/kellyjonbrazil/jc - "CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq and simplifying automation scripts."
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Gooey: Turn almost any Python command line program into a full GUI application
> I'd love to see programs communicate through a typed JSON/proto format that shed enough details to make this more independent, and get useful shell command structuring/completion or full blown GUIs from simply introspecting the expected input and output types.
You should try PowerShell. It's basically Microsoft's .NET ecosystem molded into an interactive command line. I'm not entirely sure if PoweShell can make full use of the static types that build up its core, but its ability to exchange objects in the command line is almost unmatched.
On Linux you can use `jc` (https://github.com/kellyjonbrazil/jc) combined with `jq` (https://jqlang.github.io/jq/) to glue together command lines.
- jc: Converts the output of popular command-line tools to JSON
- why does the proc directory exist?
- Open source python projecto to contribute to
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jq 1.7 Released
In addition to my previous comment about jq-like tools, I want to share a couple other interesting tools, which I use alongside jq are jo [0] and jc [1].
[0]: https://github.com/jpmens/jo
[1]: https://github.com/kellyjonbrazil/jc
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The Case for Nushell
> I wanted to write some wrappers for the standard commands that automatically did all this via `jq`.
If you're not already aware of it, you may wish to check out `jc`[0] which describes itself as a "CLI tool and python library that converts the output of popular command-line tools, file-types, and common strings to JSON, YAML, or Dictionaries. This allows piping of output to tools like jq..."
The `jc` documentation[1] & parser[2] for `ls` also demonstrates that reliable & cross-platform parsing of even "basic" commands can be non-trivial.
[0] https://github.com/kellyjonbrazil/jc
[1] https://kellyjonbrazil.github.io/jc/docs/parsers/ls
[2] https://github.com/kellyjonbrazil/jc/blob/4cd721be8595db52b6...
What are some alternatives?
zod - TypeScript-first schema validation with static type inference
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
ajv - The fastest JSON schema Validator. Supports JSON Schema draft-04/06/07/2019-09/2020-12 and JSON Type Definition (RFC8927)
jq - Command-line JSON processor
JSON-Schema Faker - JSON-Schema + fake data generators
murex - A smarter shell and scripting environment with advanced features designed for usability, safety and productivity (eg smarter DevOps tooling)
fastify-swagger - Swagger documentation generator for Fastify
jello - CLI tool to filter JSON and JSON Lines data with Python syntax. (Similar to jq)
pydantic - Data validation using Python type hints
babashka - A Clojure babushka for the grey areas of Bash (native fast-starting Clojure scripting environment) [Moved to: https://github.com/babashka/babashka]
Superstruct - A simple and composable way to validate data in JavaScript (and TypeScript).
Octo Pack - Creates Octopus-compatible NuGet packages