JSON Validator & Formatter

JSON: strict format defined by ECMA-404, double quotes required, no comments, no trailing commas, no unquoted keys. JSON5: relaxed superset, allows single quotes, supports comments (// and /* */), permits trailing commas, allows unquoted keys (if valid identifiers), supports more number formats (hex, Infinity, NaN). Example valid JSON5 but invalid JSON: {unquoted: 'single quotes', trailing: true, /* comment */}. When to use: JSON for APIs and data interchange (universal support), JSON5 for config files (better human readability), JSONC (JSON with comments) for VS Code settings. Most APIs require strict JSON; use JSON5 only when explicitly supported.

JSON Schema defines structure/validation rules. Define schema: {"type":"object","properties":{"name":{"type":"string"},"age":{"type":"number","minimum":0}},"required":["name"]}. Validation libraries: JavaScript: ajv, jsonschema. Python: jsonschema. PHP: justinrainbow/json-schema. Java: everit-org/json-schema. Common validators: type (string, number, boolean, object, array, null), required fields, min/max values, string patterns (regex), enum (allowed values), nested objects/arrays. Use cases: API request validation, config file validation, form validation, data integrity. Validation errors show: field path, constraint violated, expected vs actual value. This basic tool validates syntax; use schema validators for structural validation.

Formatting standards: Indentation: 2 spaces (most common) or 4 spaces, never tabs. Spacing: space after colon "key": "value", no space before colon, space after comma. Line breaks: each property on new line for readability, arrays can be inline if short. Key ordering: alphabetical or logical grouping for consistency. Minified JSON: no whitespace, smallest size for APIs. Pretty JSON: indented, readable for humans. When to minify: production APIs (save bandwidth), when to pretty: development, debugging, config files, documentation. Tools: JSON.stringify(obj, null, 2) for pretty, JSON.stringify(obj) for minified. This tool offers both beautify and minify modes with customizable indentation.

Challenges: browser memory limits (~100MB-1GB depending on RAM), parse time increases with size, UI freezes during processing. Solutions: Streaming: parse incrementally, don't load entire file, Node.js: JSONStream, oboe.js, clarinet. Browser: chunked reading with FileReader. Pagination: load data in chunks, virtual scrolling for display, lazy loading on demand. Server-side: process large JSON server-side, return paginated results, use database for querying. Compression: gzip reduces size 70-90%, serve as .json.gz, decompress server-side. Alternative formats: CSV for tabular data, binary formats (Protocol Buffers, MessagePack) for efficiency. This browser tool handles ~10MB comfortably; use command-line tools (jq) for larger files.

JSON.parse(): converts JSON string to JavaScript object. Input: string '{"name":"John"}', output: object {name:"John"}. Throws SyntaxError on invalid JSON. Optional reviver parameter for custom parsing. Use: deserialize API responses, read stored JSON, process JSON files. JSON.stringify(): converts JavaScript object to JSON string. Input: object {name:"John"}, output: string '{"name":"John"}'. Optional replacer for filtering/transforming, optional space parameter for pretty printing. Handles: undefined (omitted), functions (omitted), Date objects (converted to ISO string), circular references (throws error). Use: send data to APIs, store objects in localStorage, create JSON files. Round-trip: JSON.parse(JSON.stringify(obj)) clones objects (loses functions/undefined).

Security considerations: JSON.parse is safe (doesn't execute code), unlike eval (never use eval for JSON!). Attacks to prevent: (1) Large JSON (DoS): limit file size before parsing, set memory limits, timeout long parsing. (2) Deep nesting (stack overflow): validate depth before parsing, limit recursion. (3) Prototype pollution: validate object keys, avoid __proto__, constructor, prototype. Validation steps: check content-type header (application/json), limit request size (e.g., 1MB), try-catch parse errors, validate against schema, sanitize data before use, rate limit API endpoints. Never: use eval(), trust parsed data implicitly, allow arbitrary key names without validation. This tool helps identify malformed JSON before processing in applications.

JSON use cases: REST APIs (request/response bodies), config files (package.json, settings), data storage (NoSQL databases, localStorage), data interchange (between services), mobile apps (API communication), web applications (AJAX responses). Alternatives: XML (more verbose, better for documents), YAML (human-readable, for configs), TOML (simple configs), Protocol Buffers (binary, efficient), MessagePack (binary JSON), CSV (tabular data), JSON Lines (JSONL) (streaming logs). Choose JSON for: APIs (universal support), JavaScript applications (native support), human-readable data exchange. Choose alternatives for: large datasets (CSV, Parquet), high performance (Protocol Buffers), config readability (YAML, TOML), streaming (JSON Lines). JSON remains most popular for APIs due to simplicity and ubiquity.