CSV tools for the native web platform
npm install @pawel-up/csv
Stop wrestling with CSVs! This lightweight, powerful TypeScript library makes parsing CSV data a breeze. Whether you're dealing with files or strings, complex data types, or custom formats, csv has you covered.
csv?* Effortless Parsing: Parse CSV data from files or strings with just a few lines of code.
* Automatic Data Type Detection: Intelligently detects strings, numbers (integers and decimals), booleans, dates, times, and datetimes. No more manual type casting!
* Flexible Output: Get your data as an array of arrays (rows and cells) or an array of objects (rows with named columns).
* Header Row Support: Easily handle CSVs with or without header rows.
* Customizable: Fine-tune the parsing process with options for delimiters, quote characters, comment characters, encoding, and date/time formats.
* Robust Error Handling: Gracefully handles malformed CSV data and provides informative error messages.
* TypeScript-First: Built from the ground up with TypeScript, providing excellent type safety and autocompletion.
* Lightweight: No dependencies and a small footprint, making it ideal for any project.
* Handles comments: Skips lines that start with a comment character.
* Handles max rows: Can limit the number of rows to parse.
* Well tested: The library is well tested and has a high code coverage.
``bash`
npm install @pawel-up/csv
or
`bash`
yarn add @pawel-up/csv
`typescript
import { CSVParser } from '@pawel-up/csv';
const csvString = "name,age,city\nJohn Doe,30,New York\nJane Smith,25,Los Angeles";
const parser = new CSVParser();
async function parseCSV() {
const result = await parser.parse(csvString);
console.log(result);
// Output:
// {
// format: [
// { name: 'name', type: 'string', index: 0 },
// { name: 'age', type: 'number', format: 'integer', index: 1 },
// { name: 'city', type: 'string', index: 2 }
// ],
// header: ['name', 'age', 'city'],
// values: [
// ['John Doe', 30, 'New York'],
// ['Jane Smith', 25, 'Los Angeles']
// ]
// }
}
parseCSV();
`
For large CSV files, you can use the streaming functionality to process data in chunks:
`typescript
import { CSVParser } from '@pawel-up/csv';
async function streamCSV() {
// Assuming you have a file input element:
const fileInput = document.getElementById('fileInput') as HTMLInputElement;
const file = fileInput.files[0];
const parser = new CSVParser();
const stream = await parser.streamFile(file);
const reader = stream.getReader();
while (true) {
const { done, value } = await reader.read();
if (done) {
break;
}
console.log('Chunk:', value);
// Process each chunk of data here
// Example:
// value.values.forEach(row => {
// console.log(row);
// });
}
}
streamCSV();
`
Mind that the headers structure may change witch every chunk as more data becomes available to check for data types.
`typescript
import { CSVParser, type ParseResult } from '@pawel-up/csv'
const response = await fetch("./data.csv")
const textStream = response.body!.pipeThrough(new TextDecoderStream())
const parser = new CSVParser()
const stream = parser.stream(textStream)
const reader = stream.getReader()
const chunks: ParseResult[] = []
while (true) {
const { done, value } = await reader.read()
if (done) break
chunks.push(value)
}
`
The CSVParser constructor accepts an optional CSVOptions object to customize the parsing behavior:
`typescript``
interface CSVOptions {
delimiter?: string; // Default: ','
quote?: string; // Default: '"'
comment?: string; // Default: ''
header?: boolean; // Default: true
encoding?: string; // Default: 'utf8'
maxRows?: number; // Default: Infinity
}