Structured json response
A structuredClone polyfill
A super light and fast circular JSON parser.
A lightweight wrapper around fetch that always returns a structured JSON response, handling errors and network issues gracefully
An env-agnostic serializer and deserializer with recursion ability and types beyond JSON, based on the HTML structured clone algorithm.
A window.fetch polyfill.
Fun, full-featured, fully-local simulator for Cloudflare Workers
Build and manage the fast-json-stringify instances for the fastify framework
Creates an async iterator for a variety of inputs in the browser and node. Supports fetch, node-fetch, and cross-fetch
Like request, but smaller.
The document client simplifies working with items in Amazon DynamoDB by abstracting away the notion of attribute values.
Decompress a HTTP response if needed
This package provides the core HTTP request orchestration, response handling, and API call coordination.
A response-like object for mocking a Node.js HTTP response stream
Converts OpenAPI Schema Object to JSON Schema
JSON logger for Node.js and browser.
Shared TypeScript definitions for Octokit projects
Implementation of Structured Field Values for HTTP (RFC9651, RFC8941)
[](https://www.npmjs.com/package/contentful-resolve-response) [](https://github.com/c
Clone a Node.js HTTP response stream
A light-weight module that brings window.fetch to node.js
Convert Zod schemas to JSON schemas which are optionally compatible with OpenAI's structured outputs.
The missing standard library for TypeScript, for writing production-grade software.
A cross-environment fetch replacement
Rspec matchers for structured JSON responses. Compare expected keys, value types, or even match values against regular expressions.
A Rack Middleware to present structured JSON responses
Dynamically rescue errors and render a structured JSON response to client applications
Respondo standardizes JSON API responses across Rails applications. Every response gets success, data, message, and meta fields. Automatic pagination meta for Kaminari and Pagy collections. ActiveRecord serialization, error extraction, and flexible HTTP codes built in.
Use your own models' custom RABL templates and render JSON responses that follow the structure set out by JSON API (jsonapi.org).
Morphix provides a clear, expressive DSL for transforming data structures in Ruby. Perfect for API response normalization, JSON reshaping, and ETL pipelines.
Allows for matching data structures against given criteria. Very useful for testing JSON responses but may be used anywhere.
Define a specification of a json structure, as well as composing methods to verify its content. Then use this tool to recursively run through the data, and validate it matches your specification. We've used this extensively to verify json API responses at NRK.
json_data_extractor makes it easy to extract data from complex JSON structures, such as API responses or configuration files, using a schema that defines the path to the data and any necessary transformations. The schema is defined as a simple Ruby hash that maps keys to paths and optional modifiers.
Define schemas using a clean DSL and get both JSON Schema documents and runtime validations. Perfect for API request/response validation, LLM function definitions (OpenAI, Anthropic), and structured data modeling. Features Sorbet-style types, schema composition, pluggable validation adapters, and multiple error output formats (JSON:API, RFC 7807).
RedisRpc is the easiest to use RPC library in the world. (No small claim!). This version is a repackage that only has Ruby implementation. Redis is a powerful in-memory data structure server that is useful for building fast distributed systems. Redis implements message queue functionality with its use of list data structures and the `LPOP`, `BLPOP`, and `RPUSH` commands. RedisRpc implements a lightweight RPC mechanism using Redis message queues to temporarily hold RPC request and response messages. These messages are encoded as JSON strings for portability. Many other RPC mechanisms are either programming language specific (e.g. Java RMI) or require boiler-plate code for explicit typing (e.g. Thrift). RedisRpc was designed to be extremely easy to use by eliminating boiler-plate code while also being programming language neutral. High performance was not an initial goal of RedisRpc and other RPC libraries are likely to have better performance. Instead, RedisRpc has better programmer performance; it lets you get something working immediately.
RedisRPC is the easiest to use RPC library in the world. (No small claim!) It has implementations in Ruby, PHP, and Python. Redis is a powerful in-memory data structure server that is useful for building fast distributed systems. Redis implements message queue functionality with its use of list data structures and the `LPOP`, `BLPOP`, and `RPUSH` commands. RedisRPC implements a lightweight RPC mechanism using Redis message queues to temporarily hold RPC request and response messages. These messages are encoded as JSON strings for portability. Many other RPC mechanisms are either programming language specific (e.g. Java RMI) or require boiler-plate code for explicit typing (e.g. Thrift). RedisRPC was designed to be extremely easy to use by eliminating boiler-plate code while also being programming language neutral. High performance was not an initial goal of RedisRPC and other RPC libraries are likely to have better performance. Instead, RedisRPC has better programmer performance; it lets you get something working immediately.
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