Examples | Documentation

csv-stream-lite

A lightweight, memory-efficient, zero-dependency streaming CSV parser and stringifier written in TypeScript. Process large CSV files without loading them entirely into memory.

Features

• 🚀 Zero Dependencies - No external dependencies
• 💪 TypeScript First - Written in TypeScript with full type safety
• 🌊 Streaming Support - Process large CSV files without loading them into memory
• ⚡ High Performance - Efficient byte-level parsing
• 🔄 Dual Mode - Both synchronous and asynchronous APIs
• 🌐 Universal - Works in Node.js and browser environments
• 📝 Flexible - Support for custom delimiters, escape characters, and transformers
• ✅ Well Tested - Comprehensive test coverage

Installation

npm install csv-stream-lite
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yarn add csv-stream-lite
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pnpm add csv-stream-lite
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Quick Start

Parsing CSV

import { Csv } from 'csv-stream-lite'

// Parse CSV string
const csvData = `name,age,city
Alice,30,New York
Bob,25,Los Angeles`

const csv = new Csv(csvData, { readHeaders: true })

// Sync streaming
for (const row of csv.streamObjects()) {
    console.log(row) // { name: 'Alice', age: '30', city: 'New York' }
}

// Async streaming (for large files)
for await (const row of csv.streamObjectsAsync()) {
    console.log(row)
}
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Parsing with Type Transformers

import { Csv, CsvObjectShape } from 'csv-stream-lite'

interface User {
    name: string
    age: number
    active: boolean
}

const shape: CsvObjectShape<User> = {
    name: String,
    age: Number,
    active: Boolean,
}

const csv = new Csv<User>(fileStream, { shape })

for await (const user of csv.streamObjectsAsync()) {
    console.log(user.age) // Typed as number
}
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Stringifying to CSV

import { Csv } from 'csv-stream-lite'

const data = [
    { name: 'Alice', age: 30, city: 'New York' },
    { name: 'Bob', age: 25, city: 'Los Angeles' },
]

// Sync
for (const chunk of Csv.stringify(data, { headers: ['name', 'age', 'city'] })) {
    process.stdout.write(chunk)
}

// Async
for await (const chunk of Csv.stringifyAsync(data)) {
    process.stdout.write(chunk)
}

// Or get complete string
const csvString = new CsvStringify(data).toString()
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API Documentation

Full API documentation is available at https://jacobshirley.github.io/csv-stream-lite/v1

Advanced Usage

Reading from File Stream (Node.js)

import { createReadStream } from 'fs'
import { Csv } from 'csv-stream-lite'

const fileStream = createReadStream('large-file.csv')

const csv = new Csv(fileStream, { readHeaders: true })

for await (const row of csv.streamObjectsAsync()) {
    // Process each row without loading entire file into memory
    console.log(row)
}
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Custom Delimiters

// Tab-separated values
const csv = new Csv(tsvData, {
    separator: '\t',
    readHeaders: true,
})

// Semicolon-separated values
const csv = new Csv(csvData, {
    separator: ';',
    readHeaders: true,
})
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Strict Column Validation

import { Csv, TooManyColumnsError, TooFewColumnsError } from 'csv-stream-lite'

const csvData = `name,age,city
Alice,30,New York
Bob,25,Los Angeles,ExtraColumn`

const csv = new Csv(csvData, {
    headers: ['name', 'age', 'city'],
    strictColumns: true, // Throws error if column count doesn't match
})

try {
    for await (const row of csv.streamObjectsAsync()) {
        console.log(row)
    }
} catch (error) {
    if (error instanceof TooManyColumnsError) {
        console.error('Row has too many columns')
    } else if (error instanceof TooFewColumnsError) {
        console.error('Row has too few columns')
    }
}
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Row Transformation

const csv = new Csv(csvData, {
    readHeaders: true,
    transform: (row) => ({
        ...row,
        fullName: `${row.firstName} ${row.lastName}`,
        age: Number(row.age),
    }),
})
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Writing to File Stream (Node.js)

import { createWriteStream } from 'fs'
import { CsvStringify } from 'csv-stream-lite'

const writeStream = createWriteStream('output.csv')

const data = [
    { name: 'Alice', age: 30 },
    { name: 'Bob', age: 25 },
]

const stringifier = new CsvStringify(data, {
    headers: ['name', 'age'],
})

for await (const chunk of stringifier) {
    writeStream.write(chunk)
}

writeStream.end()
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Error Handling

The library provides specific error types for different scenarios:

• CsvStreamLiteError - Base error class
• NoMoreTokensError - Buffer is empty and more input is needed
• EofReachedError - End of file reached
• BufferSizeExceededError - Buffer size limit exceeded
• TooManyColumnsError - Row has more columns than expected (when strictColumns: true)
• TooFewColumnsError - Row has fewer columns than expected (when strictColumns: true)

Performance

csv-stream-lite is designed for memory efficiency and high performance:

• Streaming Architecture: Process files of any size with constant memory usage
• Lazy Evaluation: Data is only parsed as it's consumed
• Byte-Level Parsing: Efficient low-level parsing without intermediate string allocations
• Chunked Processing: Configurable chunk sizes for optimal performance

TypeScript Support

Full TypeScript support with comprehensive type definitions:

import { Csv, CsvObjectShape } from 'csv-stream-lite'

interface User {
    id: number
    name: string
    email: string
    active: boolean
}

const shape: CsvObjectShape<User> = {
    id: Number,
    name: String,
    email: String,
    active: Boolean,
}

const csv = new Csv<User>(data, { shape })

// Type-safe iteration
for await (const user of csv.streamObjectsAsync()) {
    console.log(user.id) // TypeScript knows this is a number
}
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Browser Support

csv-stream-lite works in modern browsers with support for:

• ReadableStream API
• AsyncIterable protocol
• ES2018+ features

Contributing

Contributions are welcome! Please read our Contributing Guide for details.

License

MIT © Jacob Shirley