papaparse vs csv-stringify vs fast-csv vs csv-parser vs csvtojson vs node-csv
CSV Parsing and Stringifying Libraries Comparison
3 Years
papaparsecsv-stringifyfast-csvcsv-parsercsvtojsonnode-csvSimilar Packages:
What's CSV Parsing and Stringifying Libraries?

These libraries provide various functionalities for parsing CSV (Comma-Separated Values) data and converting it into usable formats, as well as stringifying objects into CSV format. They are essential for handling data in web applications, especially when dealing with data import/export functionalities, data manipulation, and integration with other systems. Each library has its own strengths, performance characteristics, and use cases, making it important to choose the right one based on specific project requirements.

Package Weekly Downloads Trend
Github Stars Ranking
Stat Detail
Package
Downloads
Stars
Size
Issues
Publish
License
papaparse4,154,695
13,153264 kB2083 months agoMIT
csv-stringify4,105,507
4,199917 kB54a month agoMIT
fast-csv3,096,628
1,7417.03 kB4917 days agoMIT
csv-parser1,609,360
1,47729.5 kB597 months agoMIT
csvtojson817,882
2,025-1286 years agoMIT
node-csv9,554
---14 years ago-
Feature Comparison: papaparse vs csv-stringify vs fast-csv vs csv-parser vs csvtojson vs node-csv

Performance

  • papaparse:

    papaparse is optimized for client-side performance, allowing for fast parsing of large CSV files without blocking the main thread, thanks to its use of web workers.

  • csv-stringify:

    csv-stringify is optimized for converting data to CSV quickly, making it suitable for applications that need to generate CSV files rapidly without sacrificing performance.

  • fast-csv:

    fast-csv is built for speed and can handle large datasets efficiently, both for parsing and stringifying, making it ideal for real-time data processing applications.

  • csv-parser:

    csv-parser is designed for high performance, especially with large files, as it streams data and processes it on-the-fly, minimizing memory usage and maximizing speed.

  • csvtojson:

    csvtojson is efficient in converting CSV to JSON, but its performance can vary based on the complexity of the CSV structure and the transformations applied during conversion.

  • node-csv:

    node-csv provides a balance of performance and flexibility, but may not be as fast as specialized libraries for specific tasks like streaming or bulk processing.

Streaming Support

  • papaparse:

    papaparse supports streaming for parsing large files, allowing you to handle data in chunks, which is beneficial for client-side applications.

  • csv-stringify:

    csv-stringify also supports streaming, enabling you to generate CSV output incrementally, which is useful for large datasets or when integrating with other data streams.

  • fast-csv:

    fast-csv provides robust streaming capabilities for both parsing and stringifying, making it an excellent choice for applications that require real-time data processing.

  • csv-parser:

    csv-parser supports streaming, allowing you to process large CSV files line by line without loading the entire file into memory, which is crucial for handling big data.

  • csvtojson:

    csvtojson supports streaming input, making it efficient for converting large CSV files to JSON format without excessive memory usage, but it does not support streaming output.

  • node-csv:

    node-csv supports both parsing and stringifying in a streaming manner, but it may require additional configuration to optimize for large datasets.

Ease of Use

  • papaparse:

    papaparse is known for its simplicity and ease of use, especially in client-side applications, making it a favorite among developers for quick implementations.

  • csv-stringify:

    csv-stringify offers a simple and intuitive API for converting data to CSV, making it easy to implement in projects without a steep learning curve.

  • fast-csv:

    fast-csv strikes a good balance between usability and functionality, offering a clear API that is easy to work with while still providing advanced features for more complex use cases.

  • csv-parser:

    csv-parser has a straightforward API that is easy to use for basic CSV parsing tasks, making it accessible for developers of all skill levels.

  • csvtojson:

    csvtojson provides a user-friendly interface for converting CSV to JSON, with options for customization that are easy to understand and apply.

  • node-csv:

    node-csv has a more extensive API that may require a bit more time to learn, but it offers great flexibility and control over CSV processing.

Feature Set

  • papaparse:

    papaparse offers a rich feature set for parsing, including support for headers, dynamic typing, and error handling, making it suitable for a variety of use cases.

  • csv-stringify:

    csv-stringify is dedicated to converting data to CSV format, providing a rich set of options for formatting and customizing the output.

  • fast-csv:

    fast-csv offers both parsing and stringifying capabilities, along with a variety of configuration options, making it a comprehensive solution for CSV handling.

  • csv-parser:

    csv-parser focuses on efficient parsing and does not include stringifying capabilities, making it specialized for reading CSV data.

  • csvtojson:

    csvtojson excels in converting CSV to JSON and includes features like custom delimiters and transformation functions, making it versatile for various data formats.

  • node-csv:

    node-csv provides a wide range of features for both parsing and stringifying, including support for custom delimiters and advanced parsing options, making it highly configurable.

Community and Support

  • papaparse:

    papaparse has a large community and extensive documentation, making it easy to find examples and support for various use cases.

  • csv-stringify:

    csv-stringify benefits from a strong community and extensive documentation, providing ample resources for developers.

  • fast-csv:

    fast-csv has an active community and is well-maintained, ensuring that developers can find help and updates as needed.

  • csv-parser:

    csv-parser has a growing community and is well-documented, making it easy to find support and resources for troubleshooting.

  • csvtojson:

    csvtojson has a decent community and documentation, but may not be as extensive as some of the more popular libraries.

  • node-csv:

    node-csv has a solid user base and documentation, but may not have as many active contributors as some other libraries.

How to Choose: papaparse vs csv-stringify vs fast-csv vs csv-parser vs csvtojson vs node-csv
  • papaparse:

    Choose papaparse for its versatility and ease of use, especially in client-side applications. It provides features like web worker support for parsing large files without blocking the UI.

  • csv-stringify:

    Select csv-stringify if you need to convert JavaScript objects or arrays into CSV format. It offers a straightforward API and is particularly useful for generating CSV files from data structures.

  • fast-csv:

    Use fast-csv for a balanced approach that offers both parsing and stringifying capabilities with a focus on performance. It is suitable for processing large CSV files in a streaming manner, making it efficient for real-time applications.

  • csv-parser:

    Choose csv-parser for its simplicity and performance when you need a fast and efficient way to parse CSV files into JavaScript objects. It is ideal for large datasets and streaming data processing.

  • csvtojson:

    Opt for csvtojson if you require a robust solution that can handle various CSV formats and convert them directly into JSON. It supports advanced features like custom delimiters and transformation functions.

  • node-csv:

    Consider node-csv if you need a comprehensive library that provides both parsing and stringifying functionalities along with extensive configuration options. It is well-suited for complex CSV handling scenarios.

README for papaparse

Parse CSV with JavaScript

Papa Parse is the fastest in-browser CSV (or delimited text) parser for JavaScript. It is reliable and correct according to RFC 4180, and it comes with these features:

  • Easy to use
  • Parse CSV files directly (local or over the network)
  • Fast mode
  • Stream large files (even via HTTP)
  • Reverse parsing (converts JSON to CSV)
  • Auto-detect delimiter
  • Worker threads to keep your web page reactive
  • Header row support
  • Pause, resume, abort
  • Can convert numbers and booleans to their types
  • Optional jQuery integration to get files from <input type="file"> elements
  • One of the only parsers that correctly handles line-breaks and quotations

Papa Parse has no dependencies - not even jQuery.

Install

papaparse is available on npm. It can be installed with the following command:

npm install papaparse

If you don't want to use npm, papaparse.min.js can be downloaded to your project source.

Usage

import Papa from 'papaparse';

Papa.parse(file, config);
    
const csv = Papa.unparse(data[, config]);

Homepage & Demo

To learn how to use Papa Parse:

The website is hosted on Github Pages. Its content is also included in the docs folder of this repository. If you want to contribute on it just clone the master of this repository and open a pull request.

Papa Parse for Node

Papa Parse can parse a Readable Stream instead of a File when used in Node.js environments (in addition to plain strings). In this mode, encoding must, if specified, be a Node-supported character encoding. The Papa.LocalChunkSize, Papa.RemoteChunkSize , download, withCredentials and worker config options are unavailable.

Papa Parse can also parse in a node streaming style which makes .pipe available. Simply pipe the Readable Stream to the stream returned from Papa.parse(Papa.NODE_STREAM_INPUT, options). The Papa.LocalChunkSize, Papa.RemoteChunkSize , download, withCredentials, worker, step, and complete config options are unavailable. To register a callback with the stream to process data, use the data event like so: stream.on('data', callback) and to signal the end of stream, use the 'end' event like so: stream.on('end', callback).

Get Started

For usage instructions, see the homepage and, for more detail, the documentation.

Tests

Papa Parse is under test. Download this repository, run npm install, then npm test to run the tests.

Contributing

To discuss a new feature or ask a question, open an issue. To fix a bug, submit a pull request to be credited with the contributors! Remember, a pull request, with test, is best. You may also discuss on Twitter with #PapaParse or directly to me, @mholt6.

If you contribute a patch, ensure the tests suite is running correctly. We run continuous integration on each pull request and will not accept a patch that breaks the tests.