Convert JSON into readable YAML for configuration examples and data exchange. Preserve nested objects, arrays, and Unicode strings.
How to use
Paste valid JSON and generate YAML. Review quoted strings and the receiving system's expected schema before copying the result.
Example
{"enabled":true,"ports":[80,443]} becomes YAML with a boolean enabled field and a ports sequence.
FAQ
Does conversion validate my configuration?
No. It converts the data format, not application rules. JavaScript number precision applies, so use strings for long identifiers.
Related tools
A practical task
After converting configuration, inspect values that look like booleans, dates, or numbers. The destination application's expected schema matters more than a tidy visual result. Keep the original JSON to compare exact string values when a later parser behaves differently.
Another useful question
Can comments be recovered from JSON?
No. JSON has no comment field in its syntax. YAML output cannot restore commentary that was not present as data in the source.
Details for interpreting the result
| Detail | Explanation |
|---|---|
| YAML indentation | YAML uses indentation to express nesting, so a visually small spacing change can move a value into another object. Review the generated object structure, not just how neatly the lines align. |
| Strict JSON syntax | JSON needs double quotes around keys and string values. Objects use braces and arrays use square brackets. Comments and trailing commas belong to other formats, so remove them before treating a source as JSON. |
| Strings and values | The JSON string "12" differs from the number 12, and "false" differs from false. Type changes affect comparisons and imports. Keep identifiers as strings when their leading zeros or exact digits matter. |
| Numeric precision | JavaScript numbers cannot represent every large integer exactly. Long account numbers, order identifiers, and arbitrary precision decimals should remain strings or use a suitable numeric library in the receiving application. |
| Syntax and schema | A document can be syntactically valid yet contain the wrong fields or types for an application. Syntax checks confirm the format; schema and business rules determine if the receiving system can use the data. |
| Empty and missing data | An empty string, a missing property, and null express different states in structured data. A flat table can merge some of those distinctions. Confirm how missing cells should be handled before converting records. |
| Source boundaries | A summary or rewrite works from the material you provide. A URL alone does not supply the full article in this interface. Include the relevant passage and keep citations attached to the claims they support. |