node-csvtojson

CSVTOJSON

csvtojson module is a comprehensive nodejs csv parser to convert csv to json or column arrays. It can be used as node.js library / command line tool / or in browser. Below are some features:

• Strictly follow CSV definition RFC4180
• Work with millions of lines of CSV data
• Provide comprehensive parsing parameters
• Provide out of box CSV parsing tool for Command Line
• Blazing fast -- Focus on performance
• Give flexibility to developer with 'pre-defined' helpers
• Allow async / streaming parsing
• Provide a csv parser for both Node.JS and browsers
• Easy to use API

csvtojson online

Here is a free online csv to json convert service utilizing latest csvtojson module.

Upgrade to V2

csvtojson has released version 2.0.0.

• To upgrade to v2, please follow upgrading guide
• If you are looking for documentation for v1, open this page

It is still able to use v1 with [email protected]

// v1
const csvtojsonV1=require("csvtojson/v1");
// v2
const csvtojsonV2=require("csvtojson");
const csvtojsonV2=require("csvtojson/v2");

Menu

• Quick Start
• API
• Browser Usage
• Contribution

Quick Start

• As Library
• As Command Line Tool

Library

Installation

npm i --save csvtojson

From CSV File to JSON Array

/** csv file
a,b,c
1,2,3
4,5,6
*/
const csvFilePath='<path to csv file>'
const csv=require('csvtojson')
csv()
.fromFile(csvFilePath)
.then((jsonObj)=>{
	console.log(jsonObj);
	/**
	 * [
	 * 	{a:"1", b:"2", c:"3"},
	 * 	{a:"4", b:"5". c:"6"}
	 * ]
	 */ 
})

// Async / await usage
const jsonArray=await csv().fromFile(csvFilePath);

From CSV String to CSV Row

/**
csvStr:
1,2,3
4,5,6
7,8,9
*/
const csv=require('csvtojson')
csv({
	noheader:true,
	output: "csv"
})
.fromString(csvStr)
.then((csvRow)=>{ 
	console.log(csvRow) // => [["1","2","3"], ["4","5","6"], ["7","8","9"]]
})

Asynchronously process each line from csv url

const request=require('request')
const csv=require('csvtojson')

csv()
.fromStream(request.get('http://mywebsite.com/mycsvfile.csv'))
.subscribe((json)=>{
	return new Promise((resolve,reject)=>{
		// long operation for each json e.g. transform / write into database.
	})
},onError,onComplete);

Convert to CSV lines

/**
csvStr:
a,b,c
1,2,3
4,5,6
*/

const csv=require('csvtojson')
csv({output:"line"})
.fromString(csvStr)
.subscribe((csvLine)=>{ 
	// csvLine =>  "1,2,3" and "4,5,6"
})

Use Stream

const csv=require('csvtojson');

const readStream=require('fs').createReadStream(csvFilePath);

const writeStream=request.put('http://mysite.com/obj.json');

readStream.pipe(csv()).pipe(writeStream);

To find more detailed usage, please see API section

Command Line Usage

Installation

$ npm i -g csvtojson

Usage

$ csvtojson [options] <csv file path>

Example

Convert csv file and save result to json file:

$ csvtojson source.csv > converted.json

Pipe in csv data:

$ cat ./source.csv | csvtojson > converted.json

Print Help:

$ csvtojson

API

• Parameters
• Asynchronous Result Process
• Events
• Hook / Transform
• Nested JSON Structure
• Header Row
• Column Parser

Parameters

require('csvtojson') returns a constructor function which takes 2 arguments:

1. Parser parameters
2. Stream options

const csv=require('csvtojson')
const converter=csv(parserParameters, streamOptions)

Both arguments are optional.

For Stream Options please read Stream Option from Node.JS

parserParameters is a JSON object like:

const converter=csv({
	noheader:true,
	trim:true,
})

Following parameters are supported:

• output: The format to be converted to. "json" (default) -- convert csv to json. "csv" -- convert csv to csv row array. "line" -- convert csv to csv line string
• delimiter: delimiter used for separating columns. Use "auto" if delimiter is unknown in advance, in this case, delimiter will be auto-detected (by best attempt). Use an array to give a list of potential delimiters e.g. [",","|","$"]. default: ","
• quote: If a column contains delimiter, it is able to use quote character to surround the column content. e.g. "hello, world" won't be split into two columns while parsing. Set to "off" will ignore all quotes. default: " (double quote)
• trim: Indicate if parser trim off spaces surrounding column content. e.g. " content " will be trimmed to "content". Default: true
• checkType: This parameter turns on and off whether check field type. Default is false. (The default is true if version < 1.1.4)
• ignoreEmpty: Ignore the empty value in CSV columns. If a column value is not given, set this to true to skip them. Default: false.
• fork (experimental): Fork another process to parse the CSV stream. It is effective if many concurrent parsing sessions for large csv files. Default: false
• noheader:Indicating csv data has no header row and first row is data row. Default is false. See header row
• headers: An array to specify the headers of CSV data. If --noheader is false, this value will override CSV header row. Default: null. Example: ["my field","name"]. See header row
• flatKeys: Don't interpret dots (.) and square brackets in header fields as nested object or array identifiers at all (treat them like regular characters for JSON field identifiers). Default: false.
• maxRowLength: the max character a csv row could have. 0 means infinite. If max number exceeded, parser will emit "error" of "row_exceed". if a possibly corrupted csv data provided, give it a number like 65535 so the parser won't consume memory. default: 0
• checkColumn: whether check column number of a row is the same as headers. If column number mismatched headers number, an error of "mismatched_column" will be emitted.. default: false
• eol: End of line character. If omitted, parser will attempt to retrieve it from the first chunks of CSV data.
• escape: escape character used in quoted column. Default is double quote (") according to RFC4108. Change to back slash (\) or other chars for your own case.
• includeColumns: This parameter instructs the parser to include only those columns as specified by the regular expression. Example: /(name|age)/ will parse and include columns whose header contains "name" or "age"
• ignoreColumns: This parameter instructs the parser to ignore columns as specified by the regular expression. Example: /(name|age)/ will ignore columns whose header contains "name" or "age"
• colParser: Allows override parsing logic for a specific column. It accepts a JSON object with fields like: headName: <String | Function | ColParser> . e.g. {field1:'number'} will use built-in number parser to convert value of the field1 column to number. For more information See details below
• alwaysSplitAtEOL: Always interpret each line (as defined by eol like \n) as a row. This will prevent eol characters from being used within a row (even inside a quoted field). Default is false. Change to true if you are confident no inline line breaks (like line break in a cell which has multi line text).
• nullObject: How to parse if a csv cell contains "null". Default false will keep "null" as string. Change to true if a null object is needed.
• downstreamFormat: Option to set what JSON array format is needed by downstream. "line" is also called ndjson format. This format will write lines of JSON (without square brackets and commas) to downstream. "array" will write complete JSON array string to downstream (suitable for file writable stream etc). Default "line"
• needEmitAll: Parser will build JSON result if .then is called (or await is used). If this is not desired, set this to false. Default is true. All parameters can be used in Command Line tool.

Asynchronous Result Process

Since v2.0.0, asynchronous processing has been fully supported.

e.g. Process each JSON result asynchronously.

csv().fromFile(csvFile)
.subscribe((json)=>{
	return new Promise((resolve,reject)=>{
		// Async operation on the json
		// don't forget to call resolve and reject
	})
})

For more details please read:

• Add Promise and Async / Await support
• Add asynchronous line by line processing support
• Async Hooks Support

Events

Converter class defined a series of events.

header

header event is emitted for each CSV file once. It passes an array object which contains the names of the header row.

const csv=require('csvtojson')
csv()
.on('header',(header)=>{
	//header=> [header1, header2, header3]
})

header is always an array of strings without types.

data

data event is emitted for each parsed CSV line. It passes buffer of stringified JSON in ndjson format unless objectMode is set true in stream option.

const csv=require('csvtojson')
csv()
.on('data',(data)=>{
	//data is a buffer object
	const jsonStr= data.toString('utf8')
})

error

error event is emitted if any errors happened during parsing.

const csv=require('csvtojson')
csv()
.on('error',(err)=>{
	console.log(err)
})

Note that if error being emitted, the process will stop as node.js will automatically unpipe() upper-stream and chained down-stream1. This will cause end event never being emitted because end event is only emitted when all data being consumed 2. If need to know when parsing finished, use done event instead of end.

1. Node.JS Readable Stream
2. Writable end Event

done

done event is emitted either after parsing successfully finished or any error happens. This indicates the processor has stopped.

const csv=require('csvtojson')
csv()
.on('done',(error)=>{
	//do some stuff
})

if any error during parsing, it will be passed in callback.

Hook & Transform

Raw CSV Data Hook

the hook -- preRawData will be called with csv string passed to parser.

const csv=require('csvtojson')
// synchronous
csv()
.preRawData((csvRawData)=>{
	var newData=csvRawData.replace('some value','another value');
	return newData;
})

// asynchronous
csv()
.preRawData((csvRawData)=>{
	return new Promise((resolve,reject)=>{
		var newData=csvRawData.replace('some value','another value');
		resolve(newData);
	})
	
})

CSV File Line Hook

The function is called each time a file line has been parsed in csv stream. The lineIdx is the file line number in the file starting with 0.

const csv=require('csvtojson')
// synchronous
csv()
.preFileLine((fileLineString, lineIdx)=>{
	if (lineIdx === 2){
		return fileLineString.replace('some value','another value')
	}
	return fileLineString
})

// asynchronous
csv()
.preFileLine((fileLineString, lineIdx)=>{
	return new Promise((resolve,reject)=>{
			// async function pr