Format and validate JSON →
Find syntax errors, pretty-print a document, and inspect deeply nested values in an expandable JSON tree.
Tool collection
Format, validate, and compare JSON; convert CSV, Excel, and YAML; or generate TypeScript, Go, Python, and SQL code from sample data. Every operation runs locally in your browser.
Format, validate, and explore JSON in an interactive tree view.
Generate readable TypeScript types and interfaces from JSON.
Generate Go structs with nested types, pointers, and JSON tags.
Generate typed Python dataclasses from nested JSON data.
Export JSON as an XLSX workbook with a named worksheet and numeric or boolean cells.
Extract JSON from a selected XLSX worksheet, including dates and saved formula results.
Export JSON as delimited UTF-8 text with quoted fields and an optional download BOM.
Parse CSV or TSV into JSON, preserving text IDs or optionally converting value types.
Convert JSON objects into PostgreSQL, MySQL, or SQLite INSERT statements.
Convert common data-oriented YAML to JSON or JSON to readable YAML.
Compare two JSON documents structurally by object path and array index.
JSON appears in API responses, configuration files, logs, test fixtures, and data exports. A small syntax error or an unexpected field type can interrupt an otherwise simple development task, so this collection keeps validation, comparison, and code generation close together.
Use the JSON Formatter when you need to validate a document and explore nested objects or arrays. JSON Diff compares parsed values instead of literal whitespace, while the YAML converter moves portable data between two common configuration formats.
Choose JSON to Excel for an XLSX workbook with a named worksheet and typed cells, or JSON to CSV for delimited text imports. In the other direction, Excel to JSON lets you select a worksheet and header row, while CSV to JSON lets you configure delimiters and preserve text identifiers.
When sample JSON needs to become application code, the TypeScript, Go, and Python converters infer nested models from representative values. The SQL converter turns row-shaped objects into INSERT statements for PostgreSQL, MySQL, or SQLite. Generated output is a starting point: review names, numeric types, null handling, and validation rules before using it in production.
Find syntax errors, pretty-print a document, and inspect deeply nested values in an expandable JSON tree.
Ignore indentation and property order while identifying added, removed, and changed values by JSON path.
Convert representative JSON into TypeScript declarations, Go structs, or Python dataclasses for application code.
Export JSON records as delimited text with quoted fields and UTF-8 downloads.
Parse CSV with configurable headers, delimiters, and optional value conversion.
Preview JSON records as a table and download an XLSX spreadsheet.
Select an XLSX worksheet and header row, then export its records as JSON.
Create reviewable multi-row INSERT statements from one object or an array of row-shaped objects.