Working with CSV in TypeScript: Libraries and Code Examples

Working with CSV in TypeScript: A Complete Guide

CSV (Comma-Separated Values) is one of the most popular formats for exchanging tabular data. In TypeScript (and JavaScript), there are several powerful libraries for parsing, generating, and processing CSV files. In this article, we will look at the main tools, their capabilities, and provide practical examples.

Why use libraries for CSV?

Built-in JavaScript tools (e.g., split(',')) do not handle complex cases:

• Escaped quotes and commas within fields
• Different delimiters (semicolon, tab)
• Different encodings and BOM
• Multiline values
• Different line ending types (CRLF, LF)

Professional libraries solve all these problems and provide a convenient API for working with data.

1. csv-parse — CSV parsing in Node.js and the browser

csv-parse is part of the csv.js ecosystem, one of the most popular parsing libraries. It works both in Node.js and in the browser (via a bundler).

Installation

npm install csv-parse

Usage example with TypeScript

import { parse } from 'csv-parse/sync';import { readFileSync } from 'fs';

interface User {    id: number;    name: string;    email: string;}

const csvData = readFileSync('users.csv', 'utf-8');const records: User[] = parse(csvData, {    columns: true,          // first row is headers    skip_empty_lines: true,    delimiter: ',',    cast: (value, context) => {        if (context.column === 'id') return parseInt(value, 10);        return value;    }});

console.log(records);

2. PapaParse — universal parser for browser and Node.js

PapaParse is a library with excellent support for large files (streaming processing), automatic delimiter detection, and extensive configuration options.

Installation

npm install papaparse

Example with result typing

import Papa from 'papaparse';

interface Product {    sku: string;    price: number;    quantity: number;}

const csvString = `sku,price,quantityABC-001,29.99,100ABC-002,49.50,50`;

const result = Papa.parse<Product>(csvString, {    header: true,    dynamicTyping: true,  // automatic type conversion    skipEmptyLines: true});

if (result.errors.length > 0) {    console.error('Parsing errors:', result.errors);} else {    result.data.forEach(product => {        console.log(`Product ${product.sku}: ${product.price} RUB`);    });}

3. csv-stringify — generating CSV from data

For the reverse task — creating CSV from arrays of objects — use csv-stringify. It is also part of the csv.js ecosystem.

Installation

npm install csv-stringify

CSV generation example

import { stringify } from 'csv-stringify/sync';import { writeFileSync } from 'fs';

interface Order {    orderId: number;    customer: string;    total: number;}

const orders: Order[] = [    { orderId: 1001, customer: 'Ivan Petrov', total: 1500.50 },    { orderId: 1002, customer: 'Maria Sidorova', total: 2300.00 },    { orderId: 1003, customer: 'Alexey Ivanov', total: 890.75 }];

const csvOutput = stringify(orders, {    header: true,    columns: ['orderId', 'customer', 'total']});

writeFileSync('orders.csv', csvOutput, 'utf-8');console.log('CSV file created successfully');

4. Error handling and data validation

When working with CSV, it is important to handle errors correctly. Let's look at an example with data validation:

import Papa from 'papaparse';

interface ValidatedRow {    isValid: boolean;    errors: s