Streaming csv parser inspired by binary-csv that aims to be faster than everyone else
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Streaming CSV parser that aims for maximum speed as well as compatibility with the csv-spectrum CSV acid test suite.

csv-parser can convert CSV into JSON at at rate of around 90,000 rows per second. Performance varies with the data used; try bin/bench.js <your file> to benchmark your data.

csv-parser can be used in the browser with browserify.

neat-csv can be used if a Promise based interface to csv-parser is needed.

Note: This module requires Node v6.14.0 or higher.


⚡️ csv-parser is greased-lightning fast

→ npm run bench

  Filename                                   Rows Parsed  Duration
  comma_in_quotes.csv                                  1     4.8ms
  custom_escape_character.csv                          3    0.69ms
  custom_quote_and_escape_character.csv                3    0.85ms
  custom_quote_character.csv                           2    0.71ms
  custom_quote_character_default_escape.csv            3    0.78ms
  dummy.csv                                            1    0.75ms
  escaped_quotes.csv                                   3    0.77ms
  empty_columns.csv                                    1    0.83ms
  junk_rows.csv                                        3    0.83ms
  mac_newlines.csv                                     2    0.67ms
  newlines.csv                                         3    0.61ms
  process_all_rows.csv                              7268      78ms
  quotes_and_newlines.csv                              3     1.1ms
  test_geojson.csv                                     3     2.6ms
  test_latin1.csv                                      2    0.76ms
  test_strict.csv                                      3    0.70ms
  test_utf16_big.csv                                   2     1.0ms
  test_utf16_little.csv                                2    0.59ms
  test_utf8.csv                                        2    0.59ms


Using npm:

$ npm install csv-parser

Using yarn:

$ yarn add csv-parser


To use the module, create a readable stream to a desired CSV file, instantiate csv, and pipe the stream to csv.

Suppose you have a CSV file data.csv which contains the data:

Daffy Duck,24
Bugs Bunny,22

It could then be parsed, and results shown like so:

const csv = require('csv-parser')
const fs = require('fs')
const results = [];

  .on('data', (data) => results.push(data))
  .on('end', () => {
    // [
    //   { NAME: 'Daffy Duck', AGE: '24' },
    //   { NAME: 'Bugs Bunny', AGE: '22' }
    // ]

To specify options for csv, pass an object argument to the function. For example:

csv({ separator: '\t' });



Returns: Array[object]


Type: object

As an alternative to passing an options object, you may pass an Array[String] which specifies the headers to use. For example:

csv(['Name', 'Age']);

If you need to specify options and headers, please use the the object notation with the headers property as shown below.


Type: String
Default: "

A single-character string used to specify the character used to escape strings in a CSV row.


Type: Array[String]|boolean

Specifies the headers to use. Headers define the property key for each value in a CSV row. If no headers option is provided, csv-parser will use the first line in a CSV file as the header specification.

If false, specifies that the first row in a data file does not contain headers, and instructs the parser to use the row index as the key for each row. Using headers: false with the same data.csv example from above would yield:

  { '0': 'Daffy Duck', '1': 24 },
  { '0': 'Bugs Bunny', '1': 22 }

Type: Function

A function that can be used to modify the values of each header. Return null to remove the header, and it's column, from the results.

  mapHeaders: ({ header, index }) => header.toLowerCase();

Type: Function

A function that can be used to modify the value of each column value.

  mapValues: ({ header, index, value }) => value.toLowerCase();

Type: String
Default: \n

Specifies a single-character string to denote the end of a line in a CSV file.


Type: String
Default: "

Specifies a single-character string to denote a quoted string.


Type: Boolean

If true, instructs the parser not to decode UTF-8 strings.


Type: String
Default: ,

Specifies a single-character string to use as the column separator for each row.


Type: Number
Default: 0

Specifies the number of lines at the beginning of a data file that the parser should skip over, prior to parsing headers.


Type: Number
Default: Number.MAX_SAFE_INTEGER

Maximum number of bytes per row. An error is thrown if a line exeeds this value. The default value is on 8 peta byte.


Type: Boolean

If true, instructs the parser that the number of columns in each row must match the number of headers specified.


The following events are emitted during parsing:


Emitted for each row of data parsed with the notable exception of the header row. Please see Usage for an example.


Emitted after the header row is parsed. The first parameter of the event callback is an Array[String] containing the header names.

  .on('headers', (headers) => {
    console.log(`First header: ${headers[0]}`)

Readable Stream Events

Events available on Node built-in Readable Streams are also emitted. The end event should be used to detect the end of parsing.


This module also provides a CLI which will convert CSV to newline-delimited JSON. The following CLI flags can be used to control how input is parsed:

Usage: csv-parser [filename?] [options]

  --escape,-e         Set the escape character (defaults to quote value)
  --headers,-h        Explicitly specify csv headers as a comma separated list
  --help              Show this help
  --output,-o         Set output file. Defaults to stdout
  --quote,-q          Set the quote character ('"' by default)
  --remove            Remove columns from output by header name
  --separator,-s      Set the separator character ("," by default)
  --skipLines,-l      Set the number of lines to skip to before parsing headers
  --strict            Require column length match headers length
  --version,-v        Print out the installed version

For example; to parse a TSV file:

cat data.tsv | csv-parser -s $'\t'


Users may encounter issues with the encoding of a CSV file. Transcoding the source stream can be done neatly with a modules such as:

Or native iconv if part of a pipeline.