Data & Text
YAML
JSON
Runs entirely in your browser — no data is sent anywhere.
A common-case YAML subset, not the full spec
The YAML specification is large, and a fully conformant parser has to handle anchors and aliases (&anchor / *alias), multiple documents in one stream, flow-style collections ({a: 1, b: 2} and [1, 2, 3]), and several string-quoting styles with subtly different escaping rules. This tool's hand-written parser covers the block-style YAML that makes up the overwhelming majority of real config files instead: nested maps and lists via indentation, plain/single/double-quoted strings, numbers, booleans, and null. If your YAML uses anchors, flow-style collections, or multi-document streams, expect this tool to fall short — it's built for typical docker-compose.yml, GitHub Actions workflow, or application-config shaped documents, not the full spec.
Why JSON can't always losslessly round-trip through YAML
Every JSON document is valid data that YAML can represent, since YAML is a superset of JSON's data model — but going YAML to JSON and back to YAML won't reproduce the original formatting: comments are discarded (JSON has no equivalent and this parser doesn't preserve them), and any YAML-specific style choices like multi-line block scalars (| or >) collapse down to a single JSON string, which this tool then re-serializes back to a plain quoted YAML string rather than reconstructing the block scalar syntax.
Where each format tends to show up
YAML dominates configuration: Kubernetes manifests, GitHub Actions and GitLab CI pipelines, Ansible playbooks, and Docker Compose files all use it, largely because it's easier for a human to hand-edit than JSON — no trailing-comma errors, no mandatory quoting of keys, and comments are actually possible. JSON dominates everywhere data crosses a wire: API request and response bodies, most datastores' native format, and anywhere a strict, unambiguous grammar matters more than human-editability. Converting a hand-maintained YAML config into JSON to feed an API, or the reverse when adapting a JSON API response into a config file, is the usual reason to reach for this tool.
Related tools
Once you have JSON, the JSON viewer is the better place to explore or pretty-print a large or deeply nested structure, and the CSV / JSON converter covers the other common structured-data pairing when the destination is a flat spreadsheet rather than YAML.