How to Parse NDJSON Lines into a List in Python

Reads a JSON-lines (NDJSON) file line by line and converts each non-empty line into a Python object, returning a list.

Easy Python 3.9+ Aug 9, 2026 Files & data 13 views 0 copies

json ndjson file-io parsing data-processing

Python code

20 lines

Python 3.9+

import json
from pathlib import Path


def parse_ndjson(file_path: str) -> list:
    data = []
    with Path(file_path).open("r", encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if line:
                data.append(json.loads(line))
    return data


if __name__ == "__main__":
    sample = Path("sample.ndjson")
    sample.write_text('{"name": "Alice", "age": 30}\n{"name": "Bob", "age": 25}\n')
    result = parse_ndjson(sample)
    print(result)
    sample.unlink()

Output

stdout

[{'name': 'Alice', 'age': 30}, {'name': 'Bob', 'age': 25}]

How it works

Path.open() opens the file with a specified encoding and returns a file object that iterates line by line. Each line is stripped to remove newline and surrounding whitespace, and empty lines are skipped. json.loads() parses one JSON object per line, appending it to the data list. Since the file is opened in a context manager, it is automatically closed after the loop finishes. The result is a list of dictionaries, one per JSON object in the file.

Common mistakes

Using `json.load()` instead of `json.loads()` — `json.load()` expects a file object, not a string.
Not stripping the line before parsing, which can cause errors with trailing newlines.
Forgetting to skip empty lines, which causes `json.loads()` to fail on blank lines.
Missing the `encoding` parameter when the file contains non-ASCII characters.

Variations

Use `with open(file_path) as f:` instead of `Path(file_path).open()` for a more conventional approach.
Use a list comprehension with a generator expression: `[json.loads(line) for line in Path(file_path).read_text().splitlines() if line]`.

Real-world use cases

Loading bulk event logs or telemetry data exported in NDJSON format into memory for analysis.
Reading streaming data dump files from APIs like Elasticsearch or AWS S3 that use JSON lines for batching.
Preprocessing user activity logs written in NDJSON by data pipelines before inserting into a database.

How to Parse NDJSON Lines into a List in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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