csv

     _   _           _        _____  _______      __
    | \ | |         | |      / ____|/ ____\ \    / /
    |  \| | ___   __| | ___ | |    | (___  \ \  / / 
    | . ` |/ _ \ / _` |/ _ \| |     \___ \  \ \/ /  
    | |\  | (_) | (_| |  __/| |____ ____) |  \  /   
    |_| \_|\___/ \__,_|\___| \_____|_____/    \/     New BSD License

This project provides CSV parsing and has been tested and used on a large source file (over 2Gb).

• Support delimiters, quotes and escape characters
• Line breaks discovery: line breaks in source are detected and reported to destination
• Data transformation
• Async and event based
• Support for large datasets
• Complete test coverage as sample and inspiration

Quick example

Using the library is a 4 steps process:

• Create a source
• Create a destination (optional)
• Transform the data (optional)
• Listen to events (optional)

Here is a example:

// node samples/sample.js
var csv = require('csv');

csv()
.fromPath(__dirname+'/sample.in')
.toPath(__dirname+'/sample.out')
.transform(function(data){
	data.unshift(data.pop());
	return data;
})
.on('data',function(data,index){
	console.log('#'+index+' '+JSON.stringify(data));
})
.on('end',function(count){
	console.log('Number of lines: '+count);
})
.on('error',function(error){
	console.log(error.message);
});

// Print sth like:
// #0 ["2000-01-01","20322051544","1979.0","8.8017226E7","ABC","45"]
// #1 ["2050-11-27","28392898392","1974.0","8.8392926E7","DEF","23"]
// Number of lines: 2

Installing

Via git (or downloaded tarball):

git clone http://github.com/wdavidw/node-csv-parser.git

Then, simply copy or link the ./lib/csv.js file into your $HOME/.node_libraries folder or inside a declared path folder.

Via npm:

npm install csv

Reading API

The following method are available:

• fromPath(data, options)
  Take a file path as first argument and optionally on object of options as a second argument.

• fromStream(readStream, options)
  Take a readable stream as first argument and optionally on object of options as a second argument.

• from(data, options)
  Take a string, a buffer, an array or an object as first argument and optionally some options as a second argument.

Options are:

• delimiter
  Set the field delimiter, one character only, defaults to comma.

• quote
  Set the field delimiter, one character only, defaults to double quotes.

• escape
  Set the field delimiter, one character only, defaults to double quotes.

• columns
  List of fields or true if autodiscovered in the first CSV line, impact the transform argument and the data event by providing an object instead of an array, order matters, see the transform and the columns sections below.

• encoding
  Defaults to 'utf8', applied when a readable stream is created.

• trim
  If true, ignore whitespace immediately around the delimiter, defaults to false.

• ltrim
  If true, ignore whitespace immediately following the delimiter (i.e. left-trim all fields), defaults to false.

• rtrim
  If true, ignore whitespace immediately preceding the delimiter (i.e. right-trim all fields), defaults to false.

Writing API

The following methods are available:

• write(data, preserve)
  Take a string, an array or an object, implementation of the StreamWriter API.

• end()
  Terminate the stream, implementation of the StreamWriter API.

• toPath(path, options)
  Take a file path as first argument and optionally on object of options as a second argument.

• toStream(writeStream, options)
  Take a readable stream as first argument and optionally on object of options as a second argument.

Options are:

• delimiter
  Defaults to the delimiter read option.

• quote
  Defaults to the quote read option.

• quoted
  Boolean, default to false, quote all the fields even if not required.

• escape
  Defaults to the escape read option.

• columns
  List of fields, applied when transform returns an object, order matters, see the transform and the columns sections below.

• encoding
  Defaults to 'utf8', applied when a writable stream is created.

• header Display the column names on the first line if the columns option is provided.

• lineBreaks
  String used to delimit record rows or a special value; special values are 'auto', 'unix', 'mac', 'windows', 'unicode'; defaults to 'auto' (discovered in source or 'unix' if no source is specified).

• flags
  Defaults to 'w', 'w' to create or overwrite an file, 'a' to append to a file. Applied when using the toPath method.

• bufferSize
  Internal buffer holding data before being flushed into a stream. Applied when destination is a stream.

• end
  Prevent calling end on the destination, so that destination is no longer writable, similar to passing {end: false} option in stream.pipe().

• newColumns If the columns option is not specified (which means columns will be taken from the reader options, will automatically append new columns if they are added during transform().

Transforming data

• transform(callback) User provided function call on each line to filter, enrich or modify the dataset. The callback is called asynchronously.

The contract is quite simple, you receive an array of fields for each record and return the transformed record. The return value may be an array, an associative array, a string or null. If null, the record will simply be skipped.

Unless you specify the columns read option, data are provided as arrays, otherwise they are objects with keys matching columns names.

When the returned value is an array, the fields are merged in order. When the returned value is an object, it will search for the columns property in the write or in the read options and smartly order the values. If no columns options are found, it will merge the values in their order of appearance. When the returned value is a string, it is directly sent to the destination source and it is your responsibility to delimit, quote, escape or define line breaks.

Example of transform returning a string

// node samples/transform.js
var csv = require('csv');

csv()
.fromPath(__dirname+'/transform.in')
.toStream(process.stdout)
.transform(function(data,index){
	return (index>0 ? ',' : '') + data[0] + ":" + data[2] + ' ' + data[1];
});

// Print sth like:
// 82:Zbigniew Preisner,94:Serge Gainsbourg

Events

By extending the Node EventEmitter class, the library provides a few useful events:

• data (function(data, index){}) Thrown when a new row is parsed after the transform callback and with the data being the value returned by transform. Note however that the event won't be called if transform return null since the record is skipped. The callback provide two arguments: data is the CSV line being processed (by default as an array) index is the index number of the line starting at zero

• end In case your redirecting the output to a file using the toPath method, the event will be called once the writing process is complete and the file closed.

• error Thrown whenever an error is captured.

Columns

Columns names may be provided or discovered in the first line with the read options columns. If defined as an array, the order must match the one of the input source. If set to true, the fields are expected to be present in the first line of the input source.

You can define a different order and even different columns in the read options and in the write options. If the columns is not defined in the write options, it will default to the one present in the read options.

When working with fields, the transform method and the data events receive their data parameter as an object instead of an array where the keys are the field names.

// node samples/column.js
var csv = require('csv');

csv()
.fromPath(__dirname+'/columns.in',{
	columns: true
})
.toStream(process.stdout,{
	columns: ['id', 'name']
})
.transform(function(data){
	data.name = data.firstname + ' ' + data.lastname
	return data;
});

// Print sth like:
// 82,Zbigniew Preisner
// 94,Serge Gainsbourg

Running the tests

Tests are executed with expresso. To install it, simple use npm install -g expresso.

To run the tests

expresso test

Contributors

• David Worms : https://github.com/wdavidw
• Will White : https://github.com/willwhite
• Justin Latimer : https://github.com/justinlatimer
• jonseymour : https://github.com/jonseymour
• pascalopitz : https://github.com/pascalopitz
• Josh Pschorr : https://github.com/jpschorr
• Elad Ben-Israel: https://github.com/eladb

Related projects

• Pavel Kolesnikov "ya-csv": http://github.com/koles/ya-csv
• Chris Williams "node-csv": http://github.com/voodootikigod/node-csv

Similar packages

Other packages similar to csv

papaparse

PapaParse is a robust and powerful CSV parser for JavaScript with a similar feature set to csv. It supports browser and server-side parsing, auto-detection of delimiters, and streaming large files. Compared to csv, PapaParse is known for its ease of use and strong browser-side capabilities.

fast-csv

fast-csv is another popular CSV parsing and formatting library for Node.js. It offers a simple API, flexible parsing options, and support for streams. While csv provides a comprehensive set of tools for various CSV operations, fast-csv focuses on performance and ease of use for common tasks.