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Convert data between formats, beautify JSON, and generate type definitions — all in your browser.
Generate type definitions from JSON for your favorite language.
The Universal Data Converter is a comprehensive tool for transforming data between JSON, YAML, XML, CSV, and TOML formats. Data format conversion is a common task in modern development, whether you are consuming APIs that return JSON but need YAML for configuration files, or receiving CSV exports that must be converted to structured XML. This tool handles all these conversions with a single click, preserving data fidelity across formats.
To convert data, paste your input into the source panel and select the input format using auto-detect or manual selection. Choose the target format, and the converted output appears instantly in the result panel. The auto-detect feature intelligently identifies JSON, YAML, XML, CSV, and TOML based on content patterns, so you rarely need to specify the source format manually. This makes batch conversions particularly efficient.
Each format has its own considerations. YAML supports anchors, aliases, and multi-document streams. XML requires a root element and handles attributes versus elements. CSV is inherently tabular and only supports flat structures. The converter handles these differences intelligently: it flattens nested objects for CSV output and reconstructs nested structures when converting from CSV back to hierarchical formats. Arrays of objects map naturally to CSV rows and columns.
Beyond format conversion, this tool can generate strongly-typed language bindings from your JSON data. With a single click, you can produce Go struct definitions, TypeScript interfaces, or Rust struct definitions that match the shape of your data. The type generator handles nested objects, arrays, optional fields, and detects appropriate primitive types. This is invaluable when consuming a new API endpoint and needing to quickly scaffold your type definitions.
The converter also includes a diff view that highlights structural differences between two inputs. This is useful when comparing API responses, validating that a conversion preserved all data, or identifying changes between versions of a configuration file. The diff operates on the parsed data model rather than raw text, so it correctly identifies semantic equivalences even when formatting differs.
Best practice when converting data: always verify edge cases like null values, empty arrays, numeric precision, and special characters. YAML treats numeric strings differently from numbers. XML CDATA sections may need special handling. CSV escaping conventions vary by dialect. The converter handles these edge cases correctly, but it pays to inspect the output when working with complex data.
For most types yes, but some formats have inherent limitations. For example, YAML timestamps may not round-trip perfectly through JSON, which lacks a native date type. Numeric precision is preserved within JSON number range.
CSV is a flat format and does not support nested structures natively. The converter will flatten nested objects using dot notation for column headers. Converting back will reconstruct the original structure.
It generates idiomatic Go struct types with JSON tags. Nested objects become nested structs, arrays become slices, and the generator correctly handles optional fields with omitempty tags and pointer types.
Conversions are performed entirely in your browser with no server upload. The practical limit depends on your browser's memory allocation, typically 100-200 MB for most systems.