fast-csv

What is fast-csv?

The fast-csv npm package is a comprehensive library for working with CSV data in Node.js. It provides functionalities for parsing CSV files and strings, formatting data to CSV, and transforming data during the parse and format process.

What are fast-csv's main functionalities?

Parsing CSV

This feature allows you to parse CSV files or strings. The code sample demonstrates how to read a CSV file using a stream, parse it with headers, and log each row to the console.

const fs = require('fs');
const fastcsv = require('fast-csv');

fs.createReadStream('data.csv')
  .pipe(fastcsv.parse({ headers: true }))
  .on('data', row => console.log(row))
  .on('end', () => console.log('CSV file successfully processed'));

Formatting Data to CSV

This feature allows you to format JavaScript data arrays or streams to CSV. The code sample shows how to take an array of objects and write it to a CSV file with headers.

const fs = require('fs');
const fastcsv = require('fast-csv');

const data = [{ id: 1, name: 'John Doe' }, { id: 2, name: 'Jane Doe' }];

fastcsv
  .write(data, { headers: true })
  .pipe(fs.createWriteStream('out.csv'))
  .on('finish', () => console.log('Write to out.csv successfully!'));

Transforming Data

This feature allows you to transform data during the parse or format process. The code sample demonstrates how to read a CSV file, transform each row by combining first and last names into a full name, and then write the transformed data to a new CSV file.

const fs = require('fs');
const fastcsv = require('fast-csv');

fs.createReadStream('data.csv')
  .pipe(fastcsv.parse({ headers: true }))
  .transform(row => ({ fullName: row.firstName + ' ' + row.lastName }))
  .pipe(fastcsv.format({ headers: true }))
  .pipe(fs.createWriteStream('out.csv'))
  .on('finish', () => console.log('Transformed file successfully written.'));

Other packages similar to fast-csv

papaparse

PapaParse is a robust and powerful CSV parser for JavaScript with a similar feature set to fast-csv. It supports browser and server-side parsing, auto-detection of delimiters, and stream parsing. Compared to fast-csv, PapaParse has a stronger emphasis on browser-side parsing and provides a more user-friendly configuration for handling large files in the browser.

csv-parser

csv-parser is a Node.js module for parsing CSV data. It can handle large datasets and supports stream-based processing. While fast-csv offers both parsing and formatting capabilities, csv-parser focuses primarily on parsing CSV data and may be preferred for its simplicity when only parsing functionality is needed.

csv-writer

csv-writer is a CSV writing library for Node.js that provides functionality to serialize arrays and objects into CSV files. Unlike fast-csv, which offers both parsing and formatting, csv-writer is specialized for CSV output, making it a good choice if the primary requirement is to generate CSV files from data.

README

Fast-csv

This is a library is aimed at providing fast CSV parsing. It accomplishes this by not handling some of the more complex edge cases such as multi line rows. However it does support escaped values, embedded commas, double and single quotes.

Installation

npm install fast-csv

Usage

Parsing

All methods accept the following options

• headers=false: Ste to true if you expect the first line of your CSV to contain headers, alternatly you can specify an array of headers to use.
• ignoreEmpty=false: If you wish to ignore empty rows.
• delimiter=',': If your data uses an alternate delimiter such as ; or \t.
  • NOTE When specifying an alternate delimiter you may only pass in a single character delimeter
• The following are options for parsing only.
  • trim=false: If you want to trim all values parsed set to true.
  • rtrim=false: If you want to right trim all values parsed set to true.
  • ltrim=false: If you want to left trim all values parsed set to true.

events

parse-error: Emitted if there was an error parsing a row. record: Emitted when a record is parsed. data-invalid: Emitted if there was invalid row encounted, only emitted if the validate function is used. data: Emitted with the stringified version of a record.

([options])

If you use fast-csv as a function it returns a transform stream that can be piped into.

var stream = fs.createReadStream("my.csv");

var csvStream = csv()
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

stream.pipe(csvStream);

`.fromPath(path[, options])

This method parses a file from the specified path.

var csv = require("fast-csv");

csv
 .fromPath("my.csv")
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

`.fromString(string[, options])

This method parses a string

var csv = require("fast-csv");

var CSV_STRING = 'a,b\n' +
                 'a1,b1\n' +
                 'a2,b2\n';

csv
 .fromPath(CSV_STRING, {headers: true})
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

`.fromStream(stream[, options])

This accepted a readable stream to parse data from.

var stream = fs.createReadStream("my.csv");

csv()
 .fromStream(stream)
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

If you expect the first line your csv to headers you may pass a headers option in. Setting the headers option will cause change each row to an object rather than an array.

var stream = fs.createReadStream("my.csv");

csv()
 .fromStream(stream, {headers : true})
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

You may alternatively pass an array of header names which must match the order of each column in the csv, otherwise the data columns will not match.

var stream = fs.createReadStream("my.csv");

csv
 .fromStream(stream, {headers : ["firstName", "lastName", "address"]})
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

If your data may include empty rows, the sort Excel might include at the end of the file for instance, you can ignore these by including the ignoreEmpty option.

Any rows consisting of nothing but empty strings and/or commas will be skipped, without emitting a 'data' or 'error' event.

var stream = fs.createReadStream("my.csv");

csv
 .fromStream(stream, {ignoreEmpty: true})
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

Validating

You can validate each row in the csv by providing a validate handler. If a row is invalid then a data-invalid event will be emitted with the row and the index.

var stream = fs.createReadStream("my.csv");

csv(
 .fromStream(stream, {headers : true})
 .validate(function(data){
     return data.age < 50; //all persons must be under the age of 50
 })
 .on("data-invalid", function(data){
     //do something with invalid row
 })
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

Transforming

You can transform data by providing in a transform function. What is returned from the transform function will be provided to validate and emitted as a row.

var stream = fs.createReadStream("my.csv");

csv
 .fromStream(stream)
 .transform(function(data){
     return data.reverse(); //reverse each row.
 })
 .on("record", function(data){
     console.log(data):
 })
 .on("end", function(){
     console.log("done");
 });

Formatting

fast-csv also allows to you to create create a CSV from data.

In addition to the options for parsing you can specify the following additional options.

• quote='"': The character to use to escape values that contain a delimeter.
• escape='"': The character to use when escaping a value that is quoted and constains a quote character.
  • i.e: 'First,"Name"' => '"First,""name"""'

Writing Data

Each of the following methods accept an array of values to be written, however each value must be an array of arrays or objects.

write(arr[, options])

Create a readable stream to read data from.

var ws = fs.createWritableStream("my.csv");
csv
   .write([
       ["a", "b"],
       ["a1", "b1"],
       ["a2", "b2"]
   ], {headers: true})
   .pipe(ws);

var ws = fs.createWritableStream("my.csv");
csv
   .write([
       {a: "a1", b: "b1"},
       {a: "a2", b: "b2"}
   ], {headers: true})
   .pipe(ws);

writeToStream(stream,arr[, options])

Write an array of values to a WritableStream

csv
   .writeToStream(fs.createWritableStream("my.csv"), [
       ["a", "b"],
       ["a1", "b1"],
       ["a2", "b2"]
   ], {headers: true});

csv
   .writeToStream(fs.createWritableStream("my.csv"), [
       {a: "a1", b: "b1"},
       {a: "a2", b: "b2"}
   ], {headers: true})
   .pipe(ws);

writeToPath(arr[, options])

Write an array of values to the specified path

csv
   .writeToPath("my.csv", [
       ["a", "b"],
       ["a1", "b1"],
       ["a2", "b2"]
   ], {headers: true})
   .on("finish", function(){
       console.log("done!");
   });

csv
   .writeToStream("my.csv", [
       {a: "a1", b: "b1"},
       {a: "a2", b: "b2"}
   ], {headers: true})
   .on("finish", function(){
      console.log("done!");
   });

writeToString(arr[, options])

csv.writeToString([
   ["a", "b"],
   ["a1", "b1"],
   ["a2", "b2"]
], {headers: true}); //"a,b\na1,b1\na2,b2\n"

csv.writeToString([
   {a: "a1", b: "b1"},
   {a: "a2", b: "b2"}
], {headers: true}); //"a,b\na1,b1\na2,b2\n"

Benchmarks

Parsing 20000 records AVG over 3 runs

fast-csv: 198.67ms
csv:      525.33ms

Parsing 50000 records AVG over 3 runs

fast-csv: 441.33ms
csv:      1291ms

Parsing 100000 records AVG over 3 runs

fast-csv: 866ms
csv:      2773.33ms

Parsing 1000000 records AVG over 3 runs

fast-csv: 8562.67ms
csv:      30030.67ms

License

MIT https://github.com/C2FO/fast-csv/raw/master/LICENSE

##Meta

• Code: git clone git://github.com/C2FO/fast-csv.git
• Website: http://c2fo.com
• Twitter: http://twitter.com/c2fo - 877.465.4045

##Namespaces

##Classes

Changelog

v0.1.2

• Fixed issue with formatter handling undefined or null values.
• Changed formatter not not include a new line at the end of a CSV.
• Added pause and resume functionality to ParserStream