@krisdages/csv-parser

This is an unsupported fork of csv-parser that adds a getMapValue option for specifying specific functions to use for mapping particular columns instead of a single mapValues function called for each value.

It now publishes both CommonJS and ES module formats, and unlike the original implementation, this no longer dependent on the NodeJS stream library or Buffer. By default, the faster binary Buffer implementation will be used on NodeJS, and other environments will parse from string.

Instead of a default export that creates a Node stream Transform, two factory functions are exported to support both Node and Web Streams APIs.

• csvParserNodeTransform
• csvParserWebTransformStream

Other exports:

• CsvParser: The stateful base implementation class that can be used directly or to implement a streaming parser.
• CsvParserWebTransformer: Implementation of the transformer interface used to initialize TransformStreams
• initializePlatform: Function to supply constructors for Node Transform or Web TransformStream when using Node streams in a browser environment (e.g. with stream-browserify) or the node:stream/web module in NodeJS.
• getPlatform: Returns booleans for whether node or web streams are supported. If false, initializePlatform({ nodeTransform?, webTransformStream? }) must be called with a polyfill constructor
  and the constructors used for Transform and TransformStream. If false,

TODO: Document, clean up loose TypeScript types and awkward code

---

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.

Note: This module requires Node v8.16.0 or higher.

Benchmarks

⚡️ csv-parser is greased-lightning fast

1→ npm run bench
2
3  Filename                 Rows Parsed  Duration
4  backtick.csv                       2     3.5ms
5  bad-data.csv                       3    0.55ms
6  basic.csv                          1    0.26ms
7  comma-in-quote.csv                 1    0.29ms
8  comment.csv                        2    0.40ms
9  empty-columns.csv                  1    0.40ms
10  escape-quotes.csv                  3    0.38ms
11  geojson.csv                        3    0.46ms
12  large-dataset.csv               7268      73ms
13  newlines.csv                       3    0.35ms
14  no-headers.csv                     3    0.26ms
15  option-comment.csv                 2    0.24ms
16  option-escape.csv                  3    0.25ms
17  option-maxRowBytes.csv          4577      39ms
18  option-newline.csv                 0    0.47ms
19  option-quote-escape.csv            3    0.33ms
20  option-quote-many.csv              3    0.38ms
21  option-quote.csv                   2    0.22ms
22  quotes+newlines.csv                3    0.20ms
23  strict.csv                         3    0.22ms
24  latin.csv                          2    0.38ms
25  mac-newlines.csv                   2    0.28ms
26  utf16-big.csv                      2    0.33ms
27  utf16.csv                          2    0.26ms
28  utf8.csv                           2    0.24ms

Install

Using npm:

1$ npm install @krisdages/csv-parser

Using yarn:

1$ yarn add @krisdages/csv-parser

Usage

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:

NAME,AGE
Daffy Duck,24
Bugs Bunny,22

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

1const { csv: csvParserNodeTransform } = require('csv-parser')
2const fs = require('fs')
3const results = [];
4
5fs.createReadStream('data.csv')
6  .pipe(csv())
7  .on('data', (data) => results.push(data))
8  .on('end', () => {
9    console.log(results);
10    // [
11    //   { NAME: 'Daffy Duck', AGE: '24' },
12    //   { NAME: 'Bugs Bunny', AGE: '22' }
13    // ]
14  });

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

1csv({ separator: '\t' });

API

csv([options | headers])

Returns: Array[Object]

options

Type: Object

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

1csv(['Name', 'Age']);

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

escape

Type: String
Default: "

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

headers

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 column index as the key for each column. Using headers: false with the same data.csv example from above would yield:

1[
2  { '0': 'Daffy Duck', '1': 24 },
3  { '0': 'Bugs Bunny', '1': 22 }
4]

Note: If using the headers for an operation on a file which contains headers on the first line, specify skipLines: 1 to skip over the row, or the headers row will appear as normal row data. Alternatively, use the mapHeaders option to manipulate existing headers in that scenario.

mapHeaders

Type: Function

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

1csv({
2  mapHeaders: ({ header, index }) => header.toLowerCase()
3})

Parameters

header String The current column header.
index Number The current column index.

mapValues

Type: Function

A function that can be used to modify the content of each column. The return value will replace the current column content.

1csv({
2  mapValues: ({ header, index, value }) => value.toLowerCase()
3})

Parameters

header String The current column header.
index Number The current column index.
value String The current column value (or content).

newline

Type: String
Default: \n

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

quote

Type: String
Default: "

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

raw

Type: Boolean

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

separator

Type: String
Default: ,

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

skipComments

Type: Boolean | String
Default: false

Instructs the parser to ignore lines which represent comments in a CSV file. Since there is no specification that dictates what a CSV comment looks like, comments should be considered non-standard. The "most common" character used to signify a comment in a CSV file is "#". If this option is set to true, lines which begin with # will be skipped. If a custom character is needed to denote a commented line, this option may be set to a string which represents the leading character(s) signifying a comment line.

skipLines

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.

maxRowBytes

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.

strict

Type: Boolean
Default: false

If true, instructs the parser that the number of columns in each row must match the number of headers specified or throws an exception. if false: the headers are mapped to the column index less columns: any missing column in the middle will result in a wrong property mapping! more columns: the aditional columns will create a "_"+index properties - eg. "_10":"value"

Events

The following events are emitted during parsing:

data

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

headers

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

1fs.createReadStream('data.csv')
2  .pipe(csv())
3  .on('headers', (headers) => {
4    console.log(`First header: ${headers[0]}`)
5  })

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.

CLI

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)
  --skipComments,-c   Skip CSV comments that begin with '#'. Set a value to change the comment character.
  --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'

Encoding

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

• iconv-lite
• iconv

Or native iconv if part of a pipeline.

Byte Order Marks

Some CSV files may be generated with, or contain a leading Byte Order Mark. This may cause issues parsing headers and/or data from your file. From Wikipedia:

The Unicode Standard permits the BOM in UTF-8, but does not require nor recommend its use. Byte order has no meaning in UTF-8.

To use this module with a file containing a BOM, please use a module like strip-bom-stream in your pipeline:

1const fs = require('fs');
2
3const csv = require('src/index');
4const stripBom = require('strip-bom-stream');
5
6fs.createReadStream('data.csv')
7  .pipe(stripBom())
8  .pipe(csv())
9...

When using the CLI, the BOM can be removed by first running:

1$ sed $'s/\xEF\xBB\xBF//g' data.csv

Meta

CONTRIBUTING

LICENSE (MIT)