JSON to JSONLines — Free Online JSONL / NDJSON Converter

What Is JSONLines?

JSONLines (also called JSONL, NDJSON, or Newline-Delimited JSON) is a text format where each line contains a single valid JSON value. There is no wrapping array or outer structure.

{"name": "Alice", "age": 30}
{"name": "Bob", "age": 25}
{"name": "Charlie", "age": 35}

The format is defined at jsonlines.org and is sometimes referred to as:

JSON vs. JSONLines

Why Convert JSON to JSONLines?

Platforms That Consume JSONLines

Core Features

1. Dual Input Modes

• File Upload: Drag and drop or select a .json file.

• Code Editor: Paste or type raw JSON with syntax highlighting and real-time validation.

2. Parse JSON

Description: Intelligently parse JSON strings embedded in cells into structured objects.

When enabled, the tool detects string values that contain valid JSON and parses them into proper JSON objects before converting to JSONL.

Example — Parse JSON disabled:

{"id": 1, "data": "{\"x\": 10, \"y\": 20}"}

Example — Parse JSON enabled:

{"id": 1, "data": {"x": 10, "y": 20}}

Use this when your source JSON contains escaped JSON strings (common in database exports, API responses that serialize nested objects as strings, or log aggregation pipelines).

3. Data Format

Choose the format of each JSONLine entry. Controls how the output is structured per line.

4. Privacy by Design

All processing runs entirely in your browser. No data is uploaded to any server.

How to Use This JSON to JSONLines Converter？

Step 1: Provide Your JSON Data

Choose one of two input methods:

• Upload a file: Click "Choose File" and select a .json file, or drag it into the upload area.

• Paste data: Click "Enter Data" to switch to the code editor. Paste your JSON array. A "Valid JSON" badge confirms correct formatting.

Important: The tool expects a JSON array. Each array element becomes one line in the output.

Step 2: Configure Options

Use the Properties panel on the right:

1. Parse JSON: Enable to parse embedded JSON strings into objects.

2. Data Format: Choose the output format for each line.

Step 3: Convert

Click Convert. The JSONLines output appears in the "Output Data" panel.

Step 4: Copy or Download

• Click Copy to Clipboard to paste into a .jsonl file.

• Premium users can click Download File to save.

Complete Example

Example — Sample

Input JSON:

[
   {"name": "Alice", "age": 30, "city": "New York"},
   {"name": "Bob", "age": 25, "city": "London"},
   {"name": "Charlie", "age": 35, "city": "Tokyo"}
]

Configuration:

• Parse JSON: Off

• Data Format: (default)

Output:

{"name": "Alice", "age": 30, "city": "New York"}
{"name": "Bob", "age": 25, "city": "London"}
{"name": "Charlie", "age": 35, "city": "Tokyo"}

Example — Nested JSON Strings

Input JSON:

[
   {"id": 1, "payload": "{\"temperature\": 23.5, \"unit\": \"celsius\"}"},
   {"id": 2, "payload": "{\"temperature\": 19.8, \"unit\": \"celsius\"}"}
]

Configuration:

• Parse JSON: On

Output:

{"id": 1, "payload": {"temperature": 23.5, "unit": "celsius"}}
{"id": 2, "payload": {"temperature": 19.8, "unit": "celsius"}}

Example — BigQuery Import

Input JSON:

[
   {"order_id": "ORD-001", "total": 149.99, "items": 3, "status": "shipped"},
   {"order_id": "ORD-002", "total": 59.50, "items": 1, "status": "pending"},
   {"order_id": "ORD-003", "total": 224.00, "items": 5, "status": "shipped"}
]

Output (saved as orders.jsonl):

{"order_id": "ORD-001", "total": 149.99, "items": 3, "status": "shipped"}
{"order_id": "ORD-002", "total": 59.50, "items": 1, "status": "pending"}
{"order_id": "ORD-003", "total": 224.00, "items": 5, "status": "shipped"}

BigQuery load command:

bq load --source_format=NEWLINE_DELIMITED_JSON \my_dataset.orders \gs://my-bucket/orders.jsonl

Example — Elasticsearch Bulk API

Output (with action metadata lines):

{"index": {"_index": "users", "_id": "1"}}
{"name": "Alice", "age": 30, "city": "New York"}
{"index": {"_index": "users", "_id": "2"}}
{"name": "Bob", "age": 25, "city": "London"}

Elasticsearch _bulk API requires alternating action and data lines in NDJSON format.

Example — OpenAI Fine-tuning

{
   "messages": [
       {"role": "system", "content": "You are a helpful assistant."},
       {"role": "user", "content": "What is 2+2?"},
       {"role": "assistant", "content": "4"}
   ]
}
{
   "messages": [
       {"role": "system", "content": "You are a helpful assistant."},
       {"role": "user", "content": "Capital of France?"},
       {"role": "assistant", "content": "Paris"}
   ]
}

OpenAI fine-tuning data must be submitted as a .jsonl file.

JSONLines Specification Summary

From jsonlines.org:

1. UTF-8 encoding — each file must be valid UTF-8

2. One JSON value per line — each line is a complete, valid JSON value

3. Line separator — \n (0x0A) — \r\n is also accepted

4. No trailing comma — each line ends at } or ]

5. No blank lines — every line must contain a JSON value (except the final newline)

Frequently Asked Questions (FAQ)

• Does the tool upload my data?

  No. All conversion happens locally in your browser using JavaScript. Your data never leaves your device.

• What is JSONLines?

  JSONLines (JSONL / NDJSON) is a format where each line of a file contains a separate, valid JSON object. There is no wrapping array. It is used for streaming, log files, and bulk data imports.

• What is the difference between JSON and JSONLines?

  JSON wraps multiple records in a [...] array with comma separators. JSONLines puts each record on its own line with no commas or brackets. JSONLines supports line-by-line processing, appending, and error isolation.

• What does "Parse JSON" do?

  It detects string values in your JSON data that contain embedded JSON (e.g., "{\"x\": 1}") and parses them into proper JSON objects (e.g., {"x": 1}). Enable this when your source data has escaped JSON strings inside string fields.

• What platforms accept JSONLines files?

  BigQuery, Elasticsearch, Snowflake, Redshift, Apache Spark, MongoDB, Hugging Face, OpenAI (fine-tuning), Logstash, and many more.

• What file extension should I use?

  Use .jsonl or .ndjson. Both are widely recognized. BigQuery documentation uses .jsonl. Elasticsearch documentation uses .ndjson.

• Is there a file size limit?

  The tool processes data entirely in your browser. Files up to 10 MB typically convert without issues on modern hardware.

• Can I use this on mobile?

  Yes. The tool is responsive and works on smartphones and tablets.