JSON Lines (NDJSON) Viewer
JSON Lines / NDJSON is one JSON object per line, used by streaming logs, ML datasets, and tail-friendly pipelines. This viewer parses every line independently — so a single malformed line doesn't poison the whole file — and surfaces both the parsed table and the bad lines with their JSON error message. A `field:value` filter narrows by content (top-level key or `nested.path` are both supported), and a column picker keeps only the fields you care about for the re-export. Everything runs in the browser; nothing is uploaded.
How to use
- Paste lines or drop a `.jsonl` / `.ndjson` file. The table shows automatically.
- Filter with `field:value` (substring match) or plain text (matches anywhere in the JSON).
- Pick columns in the second box to keep — leave blank to show all keys discovered.
Frequently asked questions
- What happens to malformed lines?
- They're listed at the bottom with their line number and the JSON parse error. Valid lines on either side of a bad one are still parsed and displayed normally.
- Can I filter on nested fields?
- Yes — use dotted paths like `user.email:alice` or `events.0.type:login`. The path walks both objects and arrays.
- Why do logs and datasets use JSON Lines instead of a JSON array?
- Because a file of one object per line can be appended to, split and read with ordinary line tools without parsing the whole document. It also fails gracefully: a crash in the middle of a write damages the last line only, while a truncated JSON array is unreadable from the first byte. That is exactly what you want from a log or a training set that grows all day.
- The table shows columns that most of my records do not have. Is that right?
- Yes. Records in a JSON Lines file are independent of each other, so the table is the union of every key seen and a record without a key shows an empty cell. That shape is normal for event logs whose fields changed over time — and it means filtering or sorting on a field only reaches the records that actually carry it.
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