Question 1

What is JSON formatting?

Accepted Answer

JSON formatting (pretty-printing) adds indentation, line breaks, and spacing to make JSON human-readable. Converts: {"name":"John","age":30} to multi-line indented format. Preserves data, improves readability. Used for: debugging API responses, reviewing config files, code documentation. Minification reverses process - removes whitespace for smaller file size. Most IDEs auto-format JSON. Online tools useful for: large files, comparing versions, sharing formatted data.

Question 2

How to validate JSON syntax?

Accepted Answer

JSON validation checks structure against specification (RFC 8259). Common errors: missing quotes, trailing commas, unescaped characters, duplicate keys, invalid Unicode. Valid JSON requires: double quotes (not single), no trailing commas, escaped special chars (\n, \t, \"), UTF-8 encoding. Tools: JSON.parse() (JavaScript), json.loads() (Python), online validators. Error messages show: line/column number, error type, context. Fix errors before using JSON in production.

Question 3

What are common JSON errors?

Accepted Answer

Common JSON errors: 1) Trailing commas - {"a":1,} (invalid). 2) Single quotes - {'name':'John'} (use double quotes). 3) Unescaped characters - {"path":"C:\folder"} (need \\). 4) Missing commas/brackets - syntax errors. 5) Duplicate keys - {name:a, name:b} (last wins). 6) Comments - JSON does not support // or /* */ comments. 7) NaN/Infinity - use null instead. 8) Leading zeros - 0123 invalid (use 123).

Question 4

How to minify JSON?

Accepted Answer

Minification removes all unnecessary whitespace, line breaks, and formatting. Reduces file size by 20-50% for transmission/storage. Example: {"name": "John"} → {"name":"John"}. Use for: API responses, config deployment, bandwidth optimization. Trade-off: harder to debug. Process: remove spaces around {, :, [, remove line breaks, preserve string content. Tools: uglify-js, online minifiers. Production APIs: minify responses, keep source formatted. Use gzip compression for additional 60-80% reduction.

Question 5

What is JSON Schema validation?

Accepted Answer

JSON Schema defines JSON structure, types, constraints. Validates: data types (string, number, object), required fields, value ranges, regex patterns, enum values, nested structures. Example schema: {"type":"object","properties":{"age":{"type":"number","minimum":0}}}. Used for: API contract validation, config file validation, form validation. Tools: ajv (JavaScript), jsonschema (Python). Provides: detailed validation errors, documentation, auto-completion in IDEs. Version: Draft 2020-12 latest.

Question 6

How to compare two JSON files?

Accepted Answer

JSON comparison (diff) identifies differences between files. Approaches: 1) Structural comparison - compare parsed objects, ignore formatting. 2) Text diff - line-by-line comparison (affected by formatting). 3) Deep comparison - recursive object comparison. Challenges: key order ({"a":1,"b":2} vs {"b":2,"a":1}), formatting differences, array order. Tools: jq (command-line), jsondiffpatch, online comparators. Use cases: config changes, API version differences, debugging. Normalize before comparing (sort keys, format).

Question 7

What is JSONPath?

Accepted Answer

JSONPath queries JSON structures similar to XPath for XML. Syntax: $ (root), . (child), .. (recursive), * (wildcard), [] (array subscript). Examples: $.store.book[*].author (all authors), $..price (all prices). Used for: extracting data from nested JSON, API response filtering, config queries. Implementations: JavaScript (jsonpath), Python (jsonpath-ng), command-line (jq). Alternative: jq filter language (more powerful). Use for complex JSON parsing without full parsing.

Question 8

How to handle large JSON files?

Accepted Answer

Large JSON files (100MB+) require streaming/specialized tools. Techniques: 1) Streaming parsers - process chunks without loading entire file. 2) jq (command-line) - efficiently filters large files. 3) MongoDB/databases - import JSON, query efficiently. 4) Compression - gzip reduces size 70-90%. 5) Split into smaller files. 6) Use NDJSON (newline-delimited) for streaming. Avoid: JSON.parse() on large files (memory issues), browser-based tools (crash). Use: jq, Python ijson library.

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Key Security Terms

JSON (JavaScript Object Notation)

CSV (Comma-Separated Values)

JSON Schema

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