Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Papaparse | 11,818 | 1,982 | 1,449 | 4 months ago | 41 | March 23, 2023 | 181 | mit | JavaScript | |
Fast and powerful CSV (delimited text) parser that gracefully handles large files and malformed input | ||||||||||
Fast Csv | 1,545 | 1,948 | 656 | 3 months ago | 71 | December 04, 2020 | 41 | mit | TypeScript | |
CSV parser and formatter for node | ||||||||||
Filehelpers | 1,030 | 195 | 36 | 2 years ago | 21 | August 23, 2022 | 117 | mit | C# | |
The FileHelpers are a free and easy to use .NET library to read/write data from fixed length or delimited records in files, strings or streams | ||||||||||
Yobulkdev | 786 | 9 months ago | 55 | agpl-3.0 | JavaScript | |||||
🔥 🔥 🔥Open Source & AI driven Data Onboarding Platform:Free flatfile.com alternative | ||||||||||
React Papaparse | 326 | 2 | 28 | 6 months ago | 54 | October 13, 2023 | 47 | mit | TypeScript | |
react-papaparse is the fastest in-browser CSV (or delimited text) parser for React. It is full of useful features such as CSVReader, CSVDownloader, readString, jsonToCSV, readRemoteFile, ... etc. | ||||||||||
Csv | 128 | 2 | 3 | 8 months ago | 3 | August 24, 2023 | 2 | mit | C# | |
Fast C# CSV parser | ||||||||||
Csv Stream | 98 | 1,530 | 60 | 4 years ago | 22 | March 25, 2018 | 15 | other | JavaScript | |
:page_with_curl: Streaming CSV Parser for Node. Small and made entirely out of streams. | ||||||||||
Nest Csv Parser | 10 | 6 months ago | 20 | TypeScript | ||||||
CSV parser module for Nest framework (node.js) 🗄 | ||||||||||
Csv Rex | 7 | 4 | 10 months ago | 13 | May 30, 2023 | 4 | mit | JavaScript | ||
🦖 A tiny and fast CSV parser & formatter for JavaScript. | ||||||||||
Stream Csv As Json | 7 | 5 | 8 | 3 years ago | 5 | December 30, 2020 | 3 | other | JavaScript | |
Micro-library of Node stream components with minimal dependencies for creating custom data processors oriented on processing huge CSV files while requiring a minimal memory footprint. |