JSON Converter
JavaScript Object Notation. JSON is a text data format with six value types, no comments, no trailing commas and no date type.
JSON is JavaScript Object Notation, standardised as RFC 8259 and ECMA-404. It has six value types: object, array, string, number, boolean and null. It has no comments, no trailing commas, no date type and no defined numeric precision, which is why large integers and timestamps need conventions agreed between sender and receiver.
33 conversions available
Convert JSON to another format
Every conversion that takes JSON as the input.
- JSON to YAMLConvert JSON to YAML instantly. Runs locally — your data is never uploaded.
- JSON to XMLConvert JSON to XML instantly. Runs locally — your data is never uploaded.
- JSON to CSVConvert JSON to CSV instantly. Runs locally — your data is never uploaded.
- JSON to TSVConvert JSON to TSV instantly. Runs locally — your data is never uploaded.
- JSON to TOMLConvert JSON to TOML instantly. Runs locally — your data is never uploaded.
- JSON to HTMLConvert JSON to HTML instantly. Runs locally — your data is never uploaded.
- JSON to MARKDOWNConvert JSON to Markdown instantly. Runs locally — your data is never uploaded.
- JSON to SQLConvert JSON to SQL instantly. Runs locally — your data is never uploaded.
- JSON to EXCELConvert JSON to Excel instantly. Runs locally — your data is never uploaded.
- JSON to TypeScript ConverterGenerate TypeScript interfaces, Zod schemas, Go structs, Python dataclasses or Rust structs from JSON.
- JSON to C# Model ConverterConvert JSON objects into strongly-typed C# Model definitions and data models.
- JSON to Dart Class ConverterConvert JSON objects into strongly-typed Dart Class definitions and data models.
- JSON to Go Struct ConverterConvert JSON objects into strongly-typed Go Struct definitions and data models.
- JSON to Java Class ConverterConvert JSON objects into strongly-typed Java Class definitions and data models.
- JSON to Kotlin Data Class ConverterConvert JSON objects into strongly-typed Kotlin Data Class definitions and data models.
- JSON to Mongoose Schema ConverterConvert JSON objects into strongly-typed Mongoose Schema definitions and data models.
- JSON to Prisma Model ConverterConvert JSON objects into strongly-typed Prisma Model definitions and data models.
- JSON to Python Dataclass ConverterConvert JSON objects into strongly-typed Python Dataclass definitions and data models.
- JSON to Rust Struct ConverterConvert JSON objects into strongly-typed Rust Struct definitions and data models.
- JSON to Swift Codable ConverterConvert JSON objects into strongly-typed Swift Codable definitions and data models.
- JSON to Zod Schema ConverterConvert JSON objects into strongly-typed Zod Schema definitions and data models.
Convert another format to JSON
Every conversion that produces JSON as the output.
- YAML to JSONConvert YAML to JSON instantly. Runs locally — your data is never uploaded.
- XML to JSONConvert XML to JSON instantly. Runs locally — your data is never uploaded.
- CSV to JSONConvert CSV to JSON instantly. Runs locally — your data is never uploaded.
- TSV to JSONConvert TSV to JSON instantly. Runs locally — your data is never uploaded.
- TOML to JSONConvert TOML to JSON instantly. Runs locally — your data is never uploaded.
- SQL to JSONConvert SQL to JSON instantly. Runs locally — your data is never uploaded.
- .env to JSON ConverterConvert .env files to JSON and back — for config migrations and CI variables.
- Excel to JSON ConverterConvert spreadsheet rows into a JSON array of objects.
- HTML to JSON ParserParse an HTML document into a structured JSON tree of tags, attributes and text.
- Markdown to JSON ConverterParse Markdown into a structured JSON document tree with headings, lists and tables.
- PDF to JSON ConverterExport a PDF as JSON — both the recovered document structure and the raw line geometry.
- Word to JSON ConverterParse a Word document into a structured JSON document tree.
Other tools that work with JSON
- Data Format ConverterConvert between JSON, YAML, XML, CSV, TSV and TOML in any direction, locally in your browser.
- JSON Formatter & ValidatorFormat, validate, repair and analyse JSON — with errors that point at the exact line.
- JSON ValidatorCheck whether JSON is valid, with the precise position of the error and what usually causes it.
- Mock Data GeneratorGenerate realistic fake test data in 14 formats from 100+ field types, with reproducible seeds.
- INI & Config File ParserParse INI, .conf, .cfg and .properties files into structured JSON, YAML or TOML.
- JSON DiffCompare two JSON documents and see exactly which keys were added, removed or changed.
- JSON FlattenerFlatten deeply nested JSON into dot-notation keys, or expand flat keys back into nested objects.
- JSON Key SorterSort object keys and arrays in a JSON document to make two versions comparable.
- JSON MergeDeep-merge several JSON documents, choosing how arrays and conflicts are resolved.
- JSONPath TesterRun JSONPath expressions against a document and see the matches instantly.
- Query String to JSON ConverterConvert URL query strings to JSON and build query strings from JSON objects.
- Sample JSON GeneratorTurn a JSON Schema into realistic sample documents, respecting types, enums, formats and constraints.
What a JSON file is
JSON is a text serialisation with six value types: object, array, string, number, boolean and null. RFC 8259 and ECMA-404 define the same grammar, and both are short enough to read in a sitting. Strings are Unicode and the specification recommends UTF-8 for interchange; escapes use \uXXXX and a character outside the basic multilingual plane is written as a surrogate pair.
The gaps matter more than the grammar. There are no comments and no trailing commas, which is why hand-edited config files so often fail to parse. There is no date type, so timestamps travel as strings, usually ISO 8601, by agreement rather than by rule. And numbers have no defined precision: an integer beyond 2^53 survives the file but not a round trip through a parser that maps numbers to IEEE-754 doubles, which is why large identifiers should be strings.
Converting JSON to a table also has a shape problem. Nested objects and arrays have no natural row-and-column equivalent, so anything that flattens JSON into CSV has to pick a convention for paths and for repeated elements.