npm package: @krisdages/-csv-parser
Description: Streaming CSV parser that aims for maximum speed as well as compatibility with the csv-spectrum test suite
Author: mafintosh
Latest version: 3.0.0-get-map-value.1

[comment]: <> ([tests]: 	http://img.shields.io/travis/mafintosh/csv-parser.svg)

[comment]: <> ([tests-url]: http://travis-ci.org/mafintosh/csv-parser)

[comment]: <> ([cover]: https://codecov.io/gh/mafintosh/csv-parser/branch/master/graph/badge.svg)

[comment]: <> ([cover-url]: https://codecov.io/gh/mafintosh/csv-parser)

[comment]: <> ([size]: https://packagephobia.now.sh/badge?p=csv-parser)

[comment]: <> ([size-url]: https://packagephobia.now.sh/result?p=csv-parser)

# @krisdages/csv-parser

This is an unsupported fork of [csv-parser](https://github.com/mafintosh/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. 

TODO: Document, possibly PR

----

[comment]: <> ([![tests][tests]][tests-url])

[comment]: <> ([![cover][cover]][cover-url])

[comment]: <> ([![size][size]][size-url])

Streaming CSV parser that aims for maximum speed as well as compatibility with
the [csv-spectrum](https://npmjs.org/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](http://browserify.org/).

[comment]: <> ([neat-csv]&#40;https://github.com/sindresorhus/neat-csv&#41; can be used if a `Promise`)

[comment]: <> (based interface to `csv-parser` is needed.)

_Note: This module requires Node v8.16.0 or higher._

## Benchmarks

⚡️ `csv-parser` is greased-lightning fast

```console
→ npm run bench

  Filename                 Rows Parsed  Duration
  backtick.csv                       2     3.5ms
  bad-data.csv                       3    0.55ms
  basic.csv                          1    0.26ms
  comma-in-quote.csv                 1    0.29ms
  comment.csv                        2    0.40ms
  empty-columns.csv                  1    0.40ms
  escape-quotes.csv                  3    0.38ms
  geojson.csv                        3    0.46ms
  large-dataset.csv               7268      73ms
  newlines.csv                       3    0.35ms
  no-headers.csv                     3    0.26ms
  option-comment.csv                 2    0.24ms
  option-escape.csv                  3    0.25ms
  option-maxRowBytes.csv          4577      39ms
  option-newline.csv                 0    0.47ms
  option-quote-escape.csv            3    0.33ms
  option-quote-many.csv              3    0.38ms
  option-quote.csv                   2    0.22ms
  quotes+newlines.csv                3    0.20ms
  strict.csv                         3    0.22ms
  latin.csv                          2    0.38ms
  mac-newlines.csv                   2    0.28ms
  utf16-big.csv                      2    0.33ms
  utf16.csv                          2    0.26ms
  utf8.csv                           2    0.24ms
```

## Install

Using npm:

```console
$ npm install @krisdages/csv-parser
```

Using yarn:

```console
$ 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:

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

fs.createReadStream('data.csv')
  .pipe(csv())
  .on('data', (data) => results.push(data))
  .on('end', () => {
    console.log(results);
    // [
    //   { NAME: 'Daffy Duck', AGE: '24' },
    //   { NAME: 'Bugs Bunny', AGE: '22' }
    // ]
  });
```

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

```js
csv({ 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:

```js
csv(['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`<br>
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:

``` js
[
  { '0': 'Daffy Duck', '1': 24 },
  { '0': 'Bugs Bunny', '1': 22 }
]
```

_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. 

```js
csv({
  mapHeaders: ({ header, index }) => header.toLowerCase()
})
```

##### Parameters

**header** _String_ The current column header.<br/>
**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.

```js
csv({
  mapValues: ({ header, index, value }) => value.toLowerCase()
})
```

##### Parameters

**header** _String_ The current column header.<br/>
**index** _Number_ The current column index.<br/>
**value** _String_ The current column value (or content).

##### newline

Type: `String`<br>
Default: `\n`

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

#### quote

Type: `String`<br>
Default: `"`

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

#### raw

Type: `Boolean`<br>

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

#### separator

Type: `String`<br>
Default: `,`

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

#### skipComments

Type: `Boolean | String`<br>
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`<br>
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`<br>
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`<br>
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](#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.

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

### Readable Stream Events

Events available on Node built-in
[Readable Streams](https://nodejs.org/api/stream.html#stream_class_stream_readable)
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](http://ndjson.org/) 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`](https://www.npmjs.com/package/iconv-lite)
- [`iconv`](https://www.npmjs.com/package/iconv)

Or native [`iconv`](http://man7.org/linux/man-pages/man1/iconv.1.html) if part
of a pipeline.

## Byte Order Marks

Some CSV files may be generated with, or contain a leading [Byte Order Mark](https://en.wikipedia.org/wiki/Byte_order_mark#UTF-8). 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](https://github.com/sindresorhus/strip-bom-stream) in your pipeline:

```js
const fs = require('fs');

const csv = require('csv-parser');
const stripBom = require('strip-bom-stream');

fs.createReadStream('data.csv')
  .pipe(stripBom())
  .pipe(csv())
  ...
```

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

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

## Meta

[CONTRIBUTING](./.github/CONTRIBUTING)

[LICENSE (MIT)](./LICENSE)