@fast-csv/parse

What is @fast-csv/parse?

@fast-csv/parse is a powerful and flexible CSV parsing library for Node.js. It allows you to read and parse CSV files or strings with ease, providing a variety of options to handle different CSV formats and use cases.

What are @fast-csv/parse's main functionalities?

Parsing CSV from a file

This feature allows you to parse a CSV file from the file system. The `headers: true` option indicates that the first row of the CSV file contains headers.

const fs = require('fs');
const { parse } = require('@fast-csv/parse');

fs.createReadStream('path/to/your.csv')
  .pipe(parse({ headers: true }))
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

Parsing CSV from a string

This feature allows you to parse a CSV string directly. The `headers: true` option indicates that the first row of the CSV string contains headers.

const { parseString } = require('@fast-csv/parse');

const csvString = 'header1,header2\nvalue1,value2\nvalue3,value4';

parseString(csvString, { headers: true })
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

Handling different delimiters

This feature allows you to parse CSV data with a custom delimiter. In this example, the delimiter is set to a semicolon (`;`).

const { parseString } = require('@fast-csv/parse');

const csvString = 'header1;header2\nvalue1;value2\nvalue3;value4';

parseString(csvString, { headers: true, delimiter: ';' })
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

Transforming data during parsing

This feature allows you to transform data during parsing. The `transform` function is applied to each row, allowing you to modify the data as it is being parsed.

const { parse } = require('@fast-csv/parse');

const transform = (row) => {
  return {
    ...row,
    transformed: true
  };
};

parse({ headers: true, transform })
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

Other packages similar to @fast-csv/parse

csv-parser

csv-parser is a simple and fast CSV parsing library for Node.js. It is similar to @fast-csv/parse in terms of functionality but is often praised for its simplicity and ease of use. However, it may not offer as many advanced features and customization options as @fast-csv/parse.

papaparse

PapaParse is a powerful CSV parsing library that works in both Node.js and the browser. It offers a wide range of features, including support for large files, web workers, and various parsing options. Compared to @fast-csv/parse, PapaParse is more versatile in terms of environment support but may have a steeper learning curve.

csv-parse

csv-parse is a part of the CSV module suite from the Node.js CSV project. It provides robust CSV parsing capabilities with a focus on performance and flexibility. While it offers similar functionality to @fast-csv/parse, it is part of a larger suite of CSV-related tools, which can be advantageous for more complex CSV handling needs.

README

@fast-csv/parse

fast-csv package to parse CSVs.

Installation

npm i -S @fast-csv/parse

Usage

To use fast-csv in javascript you can require the module

const csv = require('@fast-csv/parse');

To import with typescript

import * as format csv '@fast-csv/parse';

• Options
• Events
• Parsing Methods
  • csv.parse
  • csv.parseStream
  • csv.parseFile
  • csv.parseString
• Examples
  • JavaScript Examples
  • TypeScript Examples

Options

• objectMode: {boolean} = true: Ensure that data events have an object emitted rather than the stringified version set to false to have a stringified buffer.
• delimiter: {string} = ',': 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 delimiter
• quote: {string} = '"': The character to use to quote fields that contain a delimiter. If you set to null then all quoting will be ignored.
  • "first,name",last name
• escape: {string} = '"': The character to used tp escape quotes inside of a quoted field.
  • i.e: First,"Name"' => '"First,""Name"""
• headers: {boolean|string[]|(string[]) => string[])} = false:
  • If you want the first row to be treated as headers then set to true
  • If there is not a headers row and you want to provide one then set to a string[]
  • If you wish to discard the first row and use your own headers set to a string[] and set the renameHeaders option to true
  • If you wish to transform the headers you can provide a transform function.
    • NOTE This will always rename the headers
  • NOTE If you specify headers and there are more columns than headers an error WILL NOT be emitted unless strictColumnHandling is set to true
  • NOTE If headers either parsed, provided or transformed are NOT unique, then an error will be emitted and the stream will stop parsing.
• renameHeaders: {boolean} = false: If you want the first line of the file to be removed and replaced by the one provided in the headers option.
  • NOTE This option should only be used if the headers option is a string[]
  • NOTE If the headers option is a function then this option is always set to true.
• ignoreEmpty: {boolean} = false: If you wish to ignore empty rows.
  • NOTE this will discard columns that are all white space or delimiters.
• comment: {string} = null: If your CSV contains comments you can use this option to ignore lines that begin with the specified character (e.g. #).
• discardUnmappedColumns: {boolean} = false: If you want to discard columns that do not map to a header.
  • NOTE this is only valid in the case that there are headers and the number of fields parsed is greater than the number of header fields.
• strictColumnHandling: {boolean} = false: If you want to consider empty lines/lines with too few fields as invalid and emit a data-invalid event
  • NOTE This option is only considered when headers are present.
• trim: {boolean} = false: Set to true to trim all fields
• rtrim: {boolean} = false: Set to true to right trim all fields.
• ltrim: {boolean} = false: Set to true to left trim all fields.
• encoding: {string} = 'utf8': Passed to StringDecoder when decoding incoming buffers. Change if incoming content is not 'utf8' encoded.
• maxRows: {number} = 0: If number is > 0 the specified number of rows will be parsed.(e.g. 100 would return the first 100 rows of data).
• skipRows: {number} = 0: If number is > 0 the specified number of parsed rows will be skipped.
• skipLines: {number} = 0: If number is > 0 the specified number of lines will be skipped.

Events

• data: Emitted when a record is parsed.
  • If headers are present then all rows will be an object.
  • If headers are not present then all rows will be an array.
  • NOTE if objectMode is set to false then all rows will be a buffer with a JSON row.
• data-invalid: Emitted if there was invalid row encounted;
  • Emitted when a validate function is provided and an invalid row is encountered.
  • Emitted when strictColumnHandling is true and a row with a different number of fields than headers is encountered.

Methods

csv.parse([options]): CsvParserStream

Creates a Csv Parsing Stream that can be piped or written to.

This is the main entrypoint and is used by all the other parsing helpers.

//creates a stream you can pipe 
const stream = csv.parse()

stream
  .on('error', error => console.error(error))
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

To pipe to the stream from a file you can do the following.

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

fs.createReadStream('my.csv')
    .pipe(csv.parse())
    .on('error', error => console.error(error))
    .on('data', row => console.log(`ROW=${JSON.stringify(row)}`))
    .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

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

const fileStream = fs.createReadStream("my.csv");
const parser = csv.parse();

fileStream
    .pipe(parser)
    .on('error', error => console.error(error))
    .on('readable', () => {
       for (let row = parser.read(); row; row = parser.read()) {
            console.log(`ROW=${JSON.stringify(row)}`);
        }
    })
    .on('end', (rowCount) => console.log(`Parsed ${rowCount} rows`));

csv.parseStream(readableStream[, options]): CsvParserStream

Accepts a readable stream and pipes it to a CsvParserStream.

const stream = fs.createReadStream('./path/to/my.csv');

csv
  .parseStream(stream)
  .on('error', error => console.error(error))
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));
    

csv.parseFile(path[, options]): CsvParserStream

Parses a file from the specified path and returns the CsvParserStream.

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

csv
  .parseFile('./path/to/my.csv')
  .on('error', error => console.error(error))
  .on('data', row => console.log(row))
  .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

csv.parseString(string[, options]): CsvParserStream

This method parses a string and returns the CsvParserStream.

const { EOL } = require('os');
const csv = require('fast-csv');

const CSV_STRING = [
    'a,b',
    'a1,b1',
    'a2,b2',
].join(EOL);

csv
    .parseString(CSV_STRING, { headers: true })
    .on('error', error => console.error(error))
    .on('data', row => console.log(row))
    .on('end', rowCount => console.log(`Parsed ${rowCount} rows`));

Changelog

v4.0.1

• [FIXED] package.json homepage links
• [ADDED] version npm script