Convert a single YAML document into formatted JSON. Inspect configuration data in a stricter format with explicit objects and arrays.
How to use
Paste YAML and generate JSON. Correct duplicate keys or unsupported values if conversion fails. Review the data types before importing elsewhere.
Example
enabled: true and a ports list become a JSON boolean and array rather than plain strings.
FAQ
Why are aliases or special tags rejected?
This converter accepts a restricted data subset. Duplicate keys, aliases, unknown tags, and nonfinite numbers are rejected instead of being guessed.
Related tools
A practical task
Check nesting before interpreting a conversion error as a data loss. A value indented under the wrong key can remain valid YAML but produce the wrong JSON object. Compare several meaningful paths in the output against the intended configuration.
Another useful question
Can it combine several YAML documents?
This conversion accepts a single document. Separate a multi document source and handle each document deliberately rather than silently merging unrelated configurations.
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. |