awesome-jsonschema
gron
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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'
gron
- Show HN: Flatito, grep for YAML and JSON files
- Gron: Make JSON greppable
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Make JSON Greppable
It buffers all of its output statements in memory before writing to stdout:
- Ask HN: What are some unpopular technologies you wish people knew more about?
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Jaq – A jq clone focused on correctness, speed, and simplicity
Have you tried `gron`?
It converts your nested json into a line by line format which plays better with tools like `grep`
From the project's README:
▶ gron "https://api.github.com/repos/tomnomnom/gron/commits?per_page..." | fgrep "commit.author"
json[0].commit.author = {};
json[0].commit.author.date = "2016-07-02T10:51:21Z";
json[0].commit.author.email = "[email protected]";
json[0].commit.author.name = "Tom Hudson";
https://github.com/tomnomnom/gron
It was suggested to me in HN comments on an article I wrote about `jq`, and I have found myself using it a lot in my day to day workflow
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Interactive Examples for Learning Jq
> So all I want is a tool to go from json => line oriented and I will do the rest with the vast library of experience I already have at transformations on the command line.*
The tool for that is likely https://github.com/tomnomnom/gron
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Modern Linux Tools vs. Unix Classics: Which Would I Choose?
If JQ is too much, see GRON &| Miller
gron transforms JSON into discrete assignments to make it easier to grep for what you want https://github.com/tomnomnom/gron
Miller is like awk, sed, cut, join, and sort for data formats such as CSV, TSV, JSON, JSON https://github.com/johnkerl/miller
- XML is better than YAML
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jq 1.7 Released
And jless [1] and gron [2].
This is the first I'm hearing of gron, but adding here for completeness sake. Meanwhile, JSON seems to be becoming a standard for CLI tools. Ideal scenario would be if every CLI tool has a --json flag or something similar, so that jc is not needed anymore.
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Any crate you feel like you're missing, preferably for the 2d or 3d computer vision?
Other tools I am a big fan of are jq and gron, if those had XML counterparts many of the above tasks could be built using them. If your XML library could take Wasm extensions, then users could write their own predicates and you wouldn't need to implement your own language like jq did, it has its own internal bytecode based VM an jq language.
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)
jfq - JSONata on the command line
JSON-Schema Faker - JSON-Schema + fake data generators
xidel - Command line tool to download and extract data from HTML/XML pages or JSON-APIs, using CSS, XPath 3.0, XQuery 3.0, JSONiq or pattern matching. It can also create new or transformed XML/HTML/JSON documents.
fastify-swagger - Swagger documentation generator for Fastify
pup - Parsing HTML at the command line
pydantic - Data validation using Python type hints
JsonPath - Java JsonPath implementation
Superstruct - A simple and composable way to validate data in JavaScript (and TypeScript).
fx - Terminal JSON viewer & processor