Flatten / unflatten JSON

Flatten nested JSON into a single-level object with dotted (or custom-separator) keys, e.g. "address.city", or reverse a flat object back into nested JSON objects and arrays. Runs entirely on your device.

Flatten / unflatten JSON collapses nested data to one level, each key built from its path and joined by separator, default a period. Unflatten reverses that, expanding a flat object into objects and arrays. An empty object or array survives as its own leaf value. A level rebuilds as an array only when every key is purely numeric.

Questions

What does flatten produce?

A single-level object whose keys are dotted paths, for example address.city, built from separator, default a period.

How are array indices represented?

As numeric path segments, the same as any object key, for example tags.0 and tags.1.

What happens to an empty object or array?

It is kept as its own leaf value at that path rather than disappearing.

How does unflatten decide between an object and an array?

A level whose keys are all purely numeric is rebuilt as an array; any other level becomes an object.

What input does unflatten require?

A flat JSON object at the top level; an array or scalar there is refused.

Can I use a custom separator?

Yes, set separator to anything other than the default period, on both the flatten and the matching unflatten call.

Compare

Tool	Runs on the CLI	Live as you type
Flatten / unflatten JSON	Yes	Yes
Query a SQLite database	Yes	No
Profile a CSV dataset	Yes	Yes
Diff two CSV datasets	Yes	No
JSONL processor	Yes	Yes
Filter / grep a log file	Yes	Yes

Related Data tools

1→1Query a SQLite databaseRun SQL against a .db / .sqlite file and read the answer as a table. The database never leaves your device.1→1Profile a CSV datasetPer column: null count, a heuristic majority type (integer/float/boolean/date/string, over non-empty cells), cardinality, and, for integer/float columns, min/max/mean/median/population stddev, or, for ISO-8601 date/timestamp columns, min/max. Read-only. Nothing is changed. Quote-aware. A record with a quoted field containing a literal newline counts as one record.n→1Diff two CSV datasetsCompare two CSVs. With a key column: report rows added, removed, and changed (by that key). Without one: a whole-row multiset diff, added/removed counts of exactly-equal rows, order-independent, duplicates counted. Read-only. Quote-aware: a record with a quoted field containing a literal newline is compared as one record.1→1JSONL processorValidate a JSON Lines file line by line, or convert it to/from a JSON array. validate never throws on a bad line, naming every one instead; the two convert modes refuse (naming the first bad line) rather than silently dropping or mangling a record.1→1Filter / grep a log fileKeep (or drop) lines matching a plain substring or a regex. Like every tool here the whole file is held in memory at once. A log genuinely in the multiple-GB range can exceed what a browser tab can hold; this does not stream from disk.