JavaScript npm module that finds JSON-like text within a string and then parses it on best effort basis
JSON.parse with context information on error
Parse JSON with more helpful errors
Parse partial JSON generated by LLM
JSON.parse with context information on error
Parse a JSON string that has git merge conflicts, resolving if possible
JSON parse with prototype poisoning protection
Parse JSON without risk of losing numeric information
Parse and stringify JSON with comments. It will retain comments even after saved!
Parse HTTP Content-Type header according to RFC 7231
Big-friendly JSON. Asynchronous streaming functions for large JSON data sets.
Parse, Resolve, and Dereference JSON Schema $ref pointers
JSON AST parser, tokenizer, printer, traverser.
Latin-script (natural language) parser
Parse json safely and at max speed
A super light and fast circular JSON parser.
Parse, Resolve, and Dereference JSON Schema $ref pointers
Parses well-formed HTML (meaning all tags closed) into an AST and back. quickly.
Repair broken JSON documents
Parse a github URL into an object.
Like read-package-json, but faster
hast utility to create an element from a simple CSS selector
A set of efficient utilities that extend the use of JSON (streaming, estimate size, NDJSON/JSONL, etc.)
Resole and parse `tsconfig.json`, replicating to TypeScript's behaviour
Workspace makes it a breeze to work with files and directories
like json, additionally, 麻绳2 parse your object as a struct.
A streaming JSON parser (generates SAX-like events) and "JSON Path" like implementation to parse small amount of data in a large JSON file.
Editrix is a gem for parsing Healthcare Eligibility Response (271) ASC X12 EDI data into painless formats like hash or a json.
This is a Ruby implementation for Rison that represents compact data in URIs. This module provides a parsing and dumping API like JSON module.
NiceHash creates hashes following certain patterns so your testing will be much easier. Parse and filter JSON. You can easily generate all the hashes you want following the criteria you specify. Many other features coming to Hash class like the methods 'bury' or select_key, access the keys like methods: my_hash.my_key.other_key. You will be able to generate thousands of different hashes just declaring one and test easily APIs based on JSON for example. Perfect to be used in test data factories
A ruby client for the gitter (https://gitter.im) API. Includes an `ActiveRecord`-like interface with models that are parsed from the responses, as well as a lower level request/json-response interface.
Roda, like other routing tree web frameworks, doesn't have the ability to introspect routes. roda-route_list offers a way to specify a json file containing the route metadata, which the route_list plugin will read. It also offers a roda-parse_routes binary that can parse routes out of roda app files, if those app files contain comments specifying the routes.
Interchange formats like json or xml are great to keep data visible, but due to their parse and pack complexity they aren't used in embedded applications. There are alternatives like msgpack or Google's protocol buffer, which allow a more binary representation of data, but these protcols are still heavy and developers tend to rather implement their own 'simple' binary protocols instead of porting or using the big ones.
yagni provides an easy way to access your hash values using its \ simple, method-like notation. Useful when parsing complex hashes, or loading YAML or JSON files (but not limited to that!) and being able to access your data in an elegant manner
punndit_youtube is a Ruby client for parsing the YouTube API v2 using JSON objects. This is a lot cleaner and simpler method than trying to use the XML data provided. This is for simple tasks involving YouTube like getting a Playlist(s), Channel, or single video information. This version does not currently support advances searches on the YouTube API.
Sumaki is a wrapper for structured data like JSON. Since Sumaki wraps the target data as it is, rather than parsing it using a schema, the original data can be referenced at any time. This makes it easy to add or modify definitions as needed while checking the target data. This feature may be useful when there is no document defining the structure of the data, or when the specification is complex and difficult to grasp, and the definition is written little by little starting from the obvious places.
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