Data formats
JSONL validator
Validate JSON Lines, see which lines fail, and collect valid rows into a JSON array.
JSON Lines (newline-delimited JSON) is one JSON value per line—popular for logs, NDJSON exports, and streaming pipelines. Paste your file: invalid lines are reported with line numbers; valid lines can be merged into a single JSON array for downstream tools.
Similar tools
Quick links to related utilities—same workflow, different input or output.
- Data formatsJSON formatterPretty-print or minify JSON for debugging, reviews, and smaller payloads.Open
- Data formatsYAML to JSONConvert YAML configs and manifests into JSON for tools that only speak JSON.Open
- Data formatsJSON to YAMLConvert JSON into YAML for configs, k8s manifests, and readable diffs.Open
FAQs
What is JSON Lines (JSONL)?›
Each line is a complete JSON value. Unlike a single JSON array file, you can append lines incrementally—handy for logs and large datasets.
Are blank lines allowed?›
Empty lines are typically skipped so sparse files still validate cleanly.
How is this different from JSON formatter?›
Formatter expects one JSON document. JSONL expects many small documents, one per line.
Can I fix broken lines here?›
The tool points to where parsing failed; you edit the source and re-run. It does not auto-repair malformed JSON.
General
Do these tools send my data to Exemplar’s servers?›
By default, conversion and formatting run entirely in your browser. Nothing is uploaded to Exemplar for normal paste-and-transform workflows. Tools that deliberately open an external service (for example, a third-party speed test) are called out on the page.
Do I need an account or install anything?›
No account is required. Everything runs in the browser—there is nothing to install for these utilities. They complement the Exemplar platform but work standalone.
Are these utilities open-source or the same as other sites?›
These pages are built for Exemplar’s audience (developers working with APIs, config, and ops data). Behavior may differ slightly from other online tools; always verify critical output in your own environment.
Are there size or performance limits?›
Very large inputs can slow down or crash the tab—especially for images, huge JSON, or multi‑MB HAR files. For production-scale data, prefer local CLI tools, streaming parsers, or your own pipelines.
Can I use output in production?›
Yes, when you have validated it. Parsers and formatters here aim to be helpful for everyday tasks but are not a substitute for tests, schema validation, or security review where it matters.
Where can I read more about privacy?›
See our Privacy policy at /privacy for how exemplar.dev handles site analytics and general data practices.