node-csv - Full featured CSV parser with simple api and tested against large datasets.

  •        27

This project provides CSV generation, parsing, transformation and serialization for Node.js. It has been tested and used by a large community over the years and should be considered reliable. It provides every option you would expect from an advanced CSV parser and stringifier.


csv-generate : ^2.0.2
csv-parse : ^2.4.0
stream-transform : ^1.0.2
csv-stringify : ^3.0.0



Related Projects

node-csv-parse - CSV parsing implementing the Node.js `stream.Transform` API

  •    CoffeeScript

Part of the CSV module, this project is a parser converting CSV text input into arrays or objects. It implements the Node.js stream.Transform API. It also provides a simple callback-based API for convenience. It is both extremely easy to use and powerful. It was first released in 2010 and is used against big data sets by a large community. Documentation for the "csv-parse" package is available here.

CSV.js - A simple, blazing-fast CSV parser and encoder. Full RFC 4180 compliance.

  •    Javascript

Simple, blazing-fast CSV parsing/encoding in JavaScript. Full RFC 4180 compliance. Compatible with browsers (>IE8), AMD, and NodeJS.

csv-parser - Streaming csv parser inspired by binary-csv that aims to be faster than everyone else

  •    Javascript

csv-parser can convert CSV into JSON at at rate of around 90,000 rows per second (perf varies with data, try bench.js with your data).The data emitted is a normalized JSON object. Each header is used as the property name of the object.

readr - Read flat files (csv, tsv, fwf) into R

  •    R

The goal of readr is to provide a fast and friendly way to read rectangular data (like csv, tsv, and fwf). It is designed to flexibly parse many types of data found in the wild, while still cleanly failing when data unexpectedly changes. If you are new to readr, the best place to start is the data import chapter in R for data science. To accurately read a rectangular dataset with readr you combine two pieces: a function that parses the overall file, and a column specification. The column specification describes how each column should be converted from a character vector to the most appropriate data type, and in most cases it's not necessary because readr will guess it for you automatically.

posthtml - PostHTML is a tool to transform HTML/XML with JS plugins

  •    Javascript

PostHTML is a tool for transforming HTML/XML with JS plugins. PostHTML itself is very small. It includes only a HTML parser, a HTML node tree API and a node tree stringifier. All HTML transformations are made by plugins. And these plugins are just small plain JS functions, which receive a HTML node tree, transform it, and return a modified tree.

vroom - Fast reading of delimited files

  •    C++

The fastest delimited reader for R, 1.27 GB/sec. vroom doesn’t stop to actually read all of your data, it simply indexes where each record is located so it can be read later. The vectors returned use the Altrep framework to lazily load the data on-demand when it is accessed, so you only pay for what you use. This lazy access is done automatically, so no changes to your R data-manipulation code are needed.

csvutil - csvutil provides fast and idiomatic mapping between CSV and Go (golang) values.

  •    Go

Package csvutil provides fast and idiomatic mapping between CSV and Go values. This package does not provide a CSV parser itself, it is based on the Reader and Writer interfaces which are implemented by eg. std csv package. This gives a possibility of choosing any other CSV writer or reader which may be more performant.

php-export-data - PHP class to export data in CSV, TSV, or Excel XML (aka SpreadsheeML) format to a file or directly to the browser

  •    PHP

A simple library for exporting tabular data to Excel-friendly XML, CSV, or TSV. It supports streaming exported data to a file or directly to the browser as a download so it is suitable for exporting large datasets (you won't run out of memory). See the test/ directory for more examples.

stream-parser - ⚡ PHP7 / Laravel Multi-format Streaming Parser

  •    PHP

DOM loading: loads all the document, making it easy to navigate and parse, and as such provides maximum flexibility for developers. Streaming: implies iterating through the document, acts like a cursor and stops at each element in its way, thus avoiding memory overkill.

url-parse - Small footprint URL parser that works seamlessly across Node

  •    Javascript

The url-parse method exposes two different API interfaces. The url interface that you know from Node.js and the new URL interface that is available in the latest browsers.In version 0.1 we moved from a DOM based parsing solution, using the <a> element, to a full Regular Expression solution. The main reason for this was to make the URL parser available in different JavaScript environments as you don't always have access to the DOM. An example of such environment is the Worker interface. The RegExp based solution didn't work well as it required a lot of lookups causing major problems in FireFox. In version 1.0.0 we ditched the RegExp based solution in favor of a pure string parsing solution which chops up the URL into smaller pieces. This module still has a really small footprint as it has been designed to be used on the client side.

qs - A querystring parser with nesting support

  •    Javascript

A querystring parsing and stringifying library with some added security. The qs module was originally created and maintained by TJ Holowaychuk.

csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang

  •    Go

Similar to FASTA/Q format in field of Bioinformatics, CSV/TSV formats are basic and ubiquitous file formats in both Bioinformatics and data sicence. People usually use spreadsheet softwares like MS Excel to do process table data. However it's all by clicking and typing, which is not automatically and time-consuming to repeat, especially when we want to apply similar operations with different datasets or purposes.

TextQL - Execute SQL against structured text like CSV or TSV

  •    Go

TextQL allows you to easily execute SQL against structured text like CSV or TSV.

parse5 - HTML parsing/serialization toolset for Node

  •    Javascript

HTML parsing/serialization toolset for Node.js. WHATWG HTML Living Standard (aka HTML5)-compliant.parse5 provides nearly everything you may need when dealing with HTML. It's the fastest spec-compliant HTML parser for Node to date. It parses HTML the way the latest version of your browser does. It has proven itself reliable in such projects as jsdom, Angular2, Polymer and many more.

FlatPack - CSV/Tab Delimited and Fixed Length Parser and Writer

  •    Java

Simple Java delimited and fixed width file parser. Handles CSV, Excel CSV, Tab, Pipe delimiters, just to name a few. Maps column positions in the file to user friendly names via XML.

Opencsv - Easy-to-use CSV (comma-separated values) parser library for Java

  •    Java

Opencsv is an easy-to-use CSV (comma-separated values) parser library for Java. Opencsv supports all the basic CSV-type things like Arbitrary numbers of values per line, Ignoring commas in quoted elements, Configurable separator and quote characters and lot more.

textract - node

  •    HTML

A text extraction node module. In almost all cases above, what textract cares about is the mime type. So .html and .htm, both possessing the same mime type, will be extracted. Other extensions that share mime types with those above should also extract successfully. For example, application/ is the mime type for .xls, but also for 5 other file types.