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Full featured CSV parser with simple api and tested against large datasets.
JavaScript CoffeeScript
tag: v0.0.6

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lib
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test
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license.md
package.json
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readme.md

 _   _           _        _____  _______      __ _____  
| \ | |         | |      / ____|/ ____\ \    / /|  __ \  
|  \| | ___   __| | ___ | |    | (___  \ \  / / | |__) |_ _ _ __ ___  ___ _ __ 
| . ` |/ _ \ / _` |/ _ \| |     \___ \  \ \/ /  |  ___/ _` | '__/ __|/ _ \ '__|
| |\  | (_) | (_| |  __/| |____ ____) |  \  /   | |  | (_| | |  \__ \  __/ |  
|_| \_|\___/ \__,_|\___| \_____|_____/    \/    |_|   \__,_|_|  |___/\___|_|  

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

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

Quick example

Using the library is a 4 steps process:

  1. Create a source
  2. Create a destination (optional)
  3. Transform the data (optional)
  4. 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

Creating a source

Options are:

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

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

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

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

The following method are available:

  • fromPath
    Take a file path as first argument and optionnaly on object of options as a second arguments.

  • fromStream
    Take a readable stream as first argument and optionnaly on object of options as a second arguments.

  • from
    Take a string, a buffer, an array or an object as first argument and optionnaly some options as a second arguments.

Creating a destination

Options are:

  • delimiter
    Default to the delimiter read option.

  • quote
    Default to the quote read option.

  • escape
    Default to the escape read option.

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

  • encoding
    Default to 'utf8', apply when a writable stream is created.

  • lineBreaks
    String used to delimite record rows or a special value; special values are 'auto', 'unix', 'mac', 'windows', 'unicode'; default to 'auto' (discovered in source).

  • flag
    Default to 'w', 'w' to create or overwrite an file, 'a' to append to a file. Apply when using the toPath method.

  • bufferSize
    Internal buffer holding data before being flush into a stream. Apply when destination is a stream.

The following method are available:

  • toPath
    Take a file path as first argument and optionnaly on object of options as a second arguments.

  • toStream
    Take a readable stream as first argument and optionnaly on object of options as a second arguments.

Transforming data

You may provide a callback to the transform method. The contract is quite simple, you recieve 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 merge 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 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 provide a few usefull 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 call if transform return null since the record is skipped. The callback provide two arguements: 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 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 recieve 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 expresso.

To run the tests expresso -I lib test/*

To develop with the tests watching at your changes expresso -w -I lib test/*

To instrument the tests expresso -I lib --cov test/*

Contributors

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