json-schema-to-ts
awesome-jsonschema
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json-schema-to-ts | awesome-jsonschema | |
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5 | 70 | |
1,335 | 101 | |
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7.6 | 5.3 | |
about 2 months ago | 8 months ago | |
TypeScript | Handlebars | |
MIT License | Creative Commons Zero v1.0 Universal |
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json-schema-to-ts
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Fastify: Support for Auto Type Inference (similar to TRPC)
JSON Schema To TS
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Better Backend DX: JSON Schema + TypeScript + Swagger = ✨ Vol. 2
// First create a general "post" schema // Shared Schema export const postSchema = { $id: 'post', type: 'object', properties: { id: { type: 'number' }, title: { type: 'string' }, published: { type: 'boolean' }, content: { type: 'string' }, tags: { type: 'array', items: { type: 'string' } }, deleted: { type: 'boolean' } }, required: ['title', 'published', 'content', 'tags', 'deleted'] } as const // We don't need to create a separate "bodySchema". // But directly infer type from postSchema export type Body = FromSchema // Reply Schema // Check https://www.fastify.io/docs/latest/Reference/Validation-and-Serialization/#adding-a-shared-schema const replySchema = { type: 'object', properties: { posts: { type: 'array', items: { $ref: 'post#' } } }, additionalProperties: false } as const // Check https://github.com/ThomasAribart/json-schema-to-ts#references export type Reply = FromSchema< typeof replySchema, { references: [typeof postSchema] } > // Also make ReplyNotFound reusable for future use export const postNotFoundSchema = { $id: 'postNotFound', // add $id here type: 'object', required: ['error'], properties: { error: { type: 'string' } }, additionalProperties: false } as const export type PostNotFound = FromSchema
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Better Backend DX: JSON Schema + TypeScript + Swagger = ✨ Vol. 1
json-schema-to-ts comes to the rescue. 💪
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How do you handle runtime validation / API documentation?
https://github.com/ThomasAribart/json-schema-to-ts - Infers TS Types from raw JSON Schema object literals you embed in your code.
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6 importantes bibliotecas para AWS Serverless TypeScript
Fonte: https://github.com/ThomasAribart/json-schema-to-ts
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'
What are some alternatives?
aws-lambda-power-tuning - AWS Lambda Power Tuning is an open-source tool that can help you visualize and fine-tune the memory/power configuration of Lambda functions. It runs in your own AWS account - powered by AWS Step Functions - and it supports three optimization strategies: cost, speed, and balanced.
zod - TypeScript-first schema validation with static type inference
middy - 🛵 The stylish Node.js middleware engine for AWS Lambda 🛵
ajv - The fastest JSON schema Validator. Supports JSON Schema draft-04/06/07/2019-09/2020-12 and JSON Type Definition (RFC8927)
generate-runtypes - A code generator for Runtypes types. Perfect to create tooling to generate code for Runtypes!
JSON-Schema Faker - JSON-Schema + fake data generators
papr - MongoDB TypeScript-aware Models
fastify-swagger - Swagger documentation generator for Fastify
quicktype - Generate types and converters from JSON, Schema, and GraphQL
pydantic - Data validation using Python type hints
json-schema-to-typescript - Compile JSONSchema to TypeScript type declarations
Superstruct - A simple and composable way to validate data in JavaScript (and TypeScript).