papaparse vs csv-stringify vs fast-csv vs json2csv
CSV Processing Libraries Comparison
3 Years
papaparsecsv-stringifyfast-csvjson2csvSimilar Packages:
What's CSV Processing Libraries?

CSV processing libraries are essential tools for handling comma-separated values (CSV) data in web development. They facilitate the conversion of data between different formats, such as JSON and CSV, enabling seamless data interchange between applications and services. These libraries offer various functionalities, including stringifying JSON objects into CSV format, parsing CSV files into JSON, and handling large datasets efficiently. By leveraging these libraries, developers can streamline data manipulation tasks, enhance performance, and improve the overall user experience when dealing with tabular data.

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
json2csv1,078,784
2,72651.2 kB173 years agoMIT
Feature Comparison: papaparse vs csv-stringify vs fast-csv vs json2csv

Performance

  • papaparse:

    PapaParse is highly performant and can handle large files due to its streaming capabilities. It also supports web workers for asynchronous parsing, which can significantly enhance performance in client-side applications.

  • csv-stringify:

    csv-stringify is optimized for performance and can handle large datasets efficiently. It provides options to control the output format and can be configured to minimize memory usage during the stringification process.

  • fast-csv:

    fast-csv is designed for high performance, particularly with large CSV files. It utilizes a streaming approach that allows for processing data in chunks, reducing memory consumption and improving speed, making it suitable for real-time applications.

  • json2csv:

    json2csv is efficient for smaller datasets and offers a straightforward API for quick conversions. However, it may not perform as well with very large datasets compared to streaming libraries like fast-csv.

Ease of Use

  • papaparse:

    PapaParse is very easy to use with a simple API and excellent documentation. It provides built-in features for handling edge cases, making it beginner-friendly.

  • csv-stringify:

    csv-stringify provides a flexible API that allows for extensive customization, but it may have a steeper learning curve for beginners due to its configuration options.

  • fast-csv:

    fast-csv is user-friendly with a clear API, making it easy to get started. Its documentation is comprehensive, which aids in understanding its features quickly.

  • json2csv:

    json2csv is known for its simplicity and ease of use, making it an excellent choice for developers who need quick JSON to CSV conversions without complex configurations.

Streaming Support

  • papaparse:

    PapaParse supports streaming for both parsing and stringifying, enabling it to handle large files efficiently and providing a responsive user experience in web applications.

  • csv-stringify:

    csv-stringify does not natively support streaming, which may limit its performance with very large datasets compared to streaming libraries.

  • fast-csv:

    fast-csv excels in streaming support, allowing for efficient processing of large CSV files without loading the entire file into memory, making it ideal for applications that require real-time data handling.

  • json2csv:

    json2csv does not support streaming, which can be a limitation for applications dealing with large datasets that require efficient processing.

Error Handling

  • papaparse:

    PapaParse provides excellent error handling, including the ability to manage malformed CSV data gracefully, making it a reliable choice for client-side applications that may encounter various data quality issues.

  • csv-stringify:

    csv-stringify provides basic error handling features, allowing developers to catch and manage errors during the stringification process, but it may require additional logic for complex scenarios.

  • fast-csv:

    fast-csv offers robust error handling capabilities, allowing developers to manage errors during parsing and stringification effectively, making it suitable for applications that require high reliability.

  • json2csv:

    json2csv has limited error handling features, which may require developers to implement custom error management for more complex use cases.

Community and Support

  • papaparse:

    PapaParse boasts a large community and extensive documentation, making it easy for developers to find help and resources, along with a variety of tutorials and examples.

  • csv-stringify:

    csv-stringify has a moderate community and support base, with documentation available but may not have as extensive community resources as some other libraries.

  • fast-csv:

    fast-csv has a growing community and good support, with active development and a wealth of documentation and examples available to assist developers.

  • json2csv:

    json2csv has a solid community and is widely used, which means there are many resources, tutorials, and examples available for developers.

How to Choose: papaparse vs csv-stringify vs fast-csv vs json2csv
  • papaparse:

    Use PapaParse if you need a versatile library that excels in both parsing and stringifying CSV data. It offers features like asynchronous parsing, support for large files, and the ability to handle malformed CSV data gracefully, making it an excellent choice for client-side applications.

  • csv-stringify:

    Choose csv-stringify if you need a robust solution for converting JSON data into CSV format with a focus on customization and configuration options. It is particularly useful for generating CSV files that require specific formatting or handling of complex data structures.

  • fast-csv:

    Select fast-csv for its speed and efficiency in both parsing and stringifying CSV data. It is ideal for projects that handle large CSV files or require real-time processing due to its streaming capabilities and low memory footprint.

  • json2csv:

    Opt for json2csv if you require a straightforward and easy-to-use library for converting JSON data to CSV. It is well-suited for simple use cases where quick conversions are needed without extensive configuration or customization.

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.