csv-streamify

What is csv-streamify?

csv-streamify is an npm package that provides a streaming CSV parser. It allows you to parse CSV data in a streaming fashion, which is useful for handling large datasets without loading the entire dataset into memory.

What are csv-streamify's main functionalities?

Streaming CSV Parsing

This feature allows you to parse CSV data in a streaming manner. The code sample demonstrates how to read a CSV file and parse it row by row, logging each row to the console.

const fs = require('fs');
const csvStreamify = require('csv-streamify');

const parser = csvStreamify({ objectMode: true });

fs.createReadStream('data.csv')
  .pipe(parser)
  .on('data', (row) => {
    console.log(row);
  })
  .on('end', () => {
    console.log('CSV parsing completed.');
  });

Custom Delimiters

This feature allows you to specify custom delimiters for parsing CSV data. The code sample demonstrates how to parse a CSV file with a semicolon (;) delimiter.

const fs = require('fs');
const csvStreamify = require('csv-streamify');

const parser = csvStreamify({ delimiter: ';', objectMode: true });

fs.createReadStream('data.csv')
  .pipe(parser)
  .on('data', (row) => {
    console.log(row);
  })
  .on('end', () => {
    console.log('CSV parsing completed with custom delimiter.');
  });

Handling Headers

This feature allows you to handle CSV headers and map them to object keys. The code sample demonstrates how to parse a CSV file and convert each row into an object with keys corresponding to the headers.

const fs = require('fs');
const csvStreamify = require('csv-streamify');

const parser = csvStreamify({ objectMode: true, columns: true });

fs.createReadStream('data.csv')
  .pipe(parser)
  .on('data', (row) => {
    console.log(row);
  })
  .on('end', () => {
    console.log('CSV parsing completed with headers.');
  });

Other packages similar to csv-streamify

csv-parser

csv-parser is another streaming CSV parser for Node.js. It is similar to csv-streamify in that it allows for streaming parsing of CSV data. However, csv-parser is known for its simplicity and ease of use, making it a popular choice for many developers.

fast-csv

fast-csv is a comprehensive CSV parser and formatter for Node.js. It offers both streaming and non-streaming parsing, as well as CSV formatting capabilities. Compared to csv-streamify, fast-csv provides more features and flexibility, but it may be more complex to use.

papaparse

papaparse is a powerful CSV parser that works in both Node.js and the browser. It supports streaming, but it is more commonly used for its synchronous parsing capabilities. Compared to csv-streamify, papaparse offers a wider range of features, including support for web workers and large file parsing.

README

csv-streamify

Parses csv files. Accepts options. No coffee script, no weird APIs. Just streams. Tested against csv-spectrum and used in production. It is also "fast enough" (around 60,000 rows per second, but that varies with data obviously).

Works in node 0.12, 4, 5 and 6. Might work in node 0.10, but is not tested in it.

Installation

npm install csv-streamify

Usage

This module implements a simple node stream.Transform stream. You can write to it, read from it and use .pipe as you would expect.

const csv = require('csv-streamify')
const fs = require('fs')

const parser = csv()

// emits each line as a buffer or as a string representing an array of fields
parser.on('data', function (line) {
  console.log(line)
})

// now pipe some data into it
fs.createReadStream('/path/to/file.csv').pipe(parser)

with options and callback

The first argument can either be an options object (see below) or a callback function.

Note: If you pass a callback to csv-streamify it will buffer the parsed data for you and pass it to the callback when it's done. This behaviour can obviously lead to out of memory errors with very large csv files.

const csv = require('csv-streamify')
const fs = require('fs')

const parser = csv({ objectMode: true }, function (err, result) {
  if (err) throw err
  // our csv has been parsed succesfully
  result.forEach(function (line) { console.log(line) })
})

// now pipe some data into it
fs.createReadStream('/path/to/file.csv').pipe(parser)

Options

You can pass some options to the parser. All of them are optional.

The options are also passed to the underlying transform stream, so you can pass in any standard node core stream options.

{
  delimiter: ',', // comma, semicolon, whatever
  newline: '\n', // newline character (use \r\n for CRLF files)
  quote: '"', // what's considered a quote
  empty: '', // empty fields are replaced by this,

  // if true, emit arrays instead of stringified arrays or buffers
  objectMode: false,

  // if set to true, uses first row as keys -> [ { column1: value1, column2: value2 }, ...]
  columns: false
}

Also, take a look at iconv-lite (npm install iconv-lite --save), it provides pure javascript streaming character encoding conversion.

CLI

To use on the command line install it globally:

$ npm install csv-streamify -g

This should add the csv-streamify command to your $PATH.

Then, you either pipe data into it or give it a filename:

# pipe data in
$ cat some_data.csv | csv-streamify
# pass a filename
$ csv-streamify some_data.csv > output.json
# tell csv-streamify to read from + wait on stdin
$ csv-streamify -

Wishlist

• browser support
• better CLI

If you would like to contribute either of those just open an issue so we can discuss it further. :)

Contributors

Nicolas Hery (objectMode)