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csv-parse
Advanced tools
Package description
The csv-parse package is a flexible Node.js library that provides a parser converting CSV text input into arrays or objects. It implements the Node.js stream.Transform API. It is also capable of converting large datasets and supports many advanced features such as streaming and asynchronous processing.
Parsing CSV to Arrays
This feature allows you to parse CSV data into arrays. Each row in the CSV data becomes an array.
const parse = require('csv-parse');
const assert = require('assert');
const input = 'a,b,c\nd,e,f';
parse(input, function(err, output){
assert.deepEqual(output, [['a', 'b', 'c'], ['d', 'e', 'f']]);
});
Parsing CSV with Column Mapping
This feature allows you to map CSV columns to object properties, so each row in the CSV data becomes an object with named properties.
const parse = require('csv-parse');
const assert = require('assert');
const input = 'a,b,c\nd,e,f';
const parser = parse({columns: true}, function(err, records){
assert.deepEqual(records, [{a: 'd', b: 'e', c: 'f'}]);
});
parser.write(input);
parser.end();
Asynchronous Iteration
This feature allows for asynchronous iteration over the parsed records, which is useful for handling large CSV files or streams.
const parse = require('csv-parse');
const fs = require('fs');
const parser = fs.createReadStream('/path/to/csv-file.csv').pipe(parse({columns: true}));
(async () => {
for await (const record of parser) {
// Work with each record
}
})();
Papa Parse is a powerful CSV parser that can handle large files and malformed input gracefully. It works in both browser and server environments. Compared to csv-parse, Papa Parse has a more user-friendly API and can automatically detect delimiters.
Fast-csv is another CSV parsing and formatting library for Node.js. It provides a simple API and supports both stream and callback-based processing. It is known for its speed and efficiency, but csv-parse offers more advanced features and customization options.
csvtojson is a full-featured CSV parser library that converts CSV to JSON. One of its main differences from csv-parse is that it focuses on the JSON output format, whereas csv-parse provides more flexibility in handling the parsed data.
Readme
The csv-parse
package is a parser converting CSV text input into arrays or objects. It is part of the CSV project.
It implements the Node.js stream.Transform
API. It also provides a simple callback-based API for convenience. It is both extremely easy to use and powerful. It was first released in 2010 and is used against big data sets by a large community.
Run npm install csv
to install the full CSV module or run npm install csv-parse
if you are only interested by the CSV parser.
Use the callback and sync APIs for simplicity or the stream based API for scalability.
The API is available in multiple flavors. This example illustrates the stream API.
import assert from 'assert';
import { parse } from 'csv-parse';
const records = [];
// Initialize the parser
const parser = parse({
delimiter: ':'
});
// Use the readable stream api to consume records
parser.on('readable', function(){
let record;
while ((record = parser.read()) !== null) {
records.push(record);
}
});
// Catch any error
parser.on('error', function(err){
console.error(err.message);
});
// Test that the parsed records matched the expected records
parser.on('end', function(){
assert.deepStrictEqual(
records,
[
[ 'root','x','0','0','root','/root','/bin/bash' ],
[ 'someone','x','1022','1022','','/home/someone','/bin/bash' ]
]
);
});
// Write data to the stream
parser.write("root:x:0:0:root:/root:/bin/bash\n");
parser.write("someone:x:1022:1022::/home/someone:/bin/bash\n");
// Close the readable stream
parser.end();
The project is sponsored by Adaltas, an Big Data consulting firm based in Paris, France.
FAQs
CSV parsing implementing the Node.js `stream.Transform` API
We found that csv-parse demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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