csv-generate

What is csv-generate?

The csv-generate package is a simple and powerful tool for generating CSV data programmatically. It is part of the CSV module suite for Node.js, designed to work with streams and provide a flexible means of generating CSV files with custom settings. This package can be particularly useful for testing, data generation, and simulation purposes.

What are csv-generate's main functionalities?

Synchronous Data Generation

Generate CSV data synchronously. This is useful for small datasets that can be generated and used on the fly without the need for asynchronous handling.

const generate = require('csv-generate');
let output = generate({length: 2});
console.log(output);

Asynchronous Stream Generation

Generate CSV data asynchronously using streams. This method is suitable for larger datasets or when the data generation process is part of a larger, asynchronous workflow.

const generate = require('csv-generate');
const generator = generate({length: 20, objectMode: true});
generator.on('readable', function(){
  let row;
  while ((row = generator.read()) !== null) {
    console.log(row);
  }
});

Custom Column Options

Customize the columns of the generated CSV data. This feature allows for specifying the type of data each column should contain, providing flexibility in the structure of the generated data.

const generate = require('csv-generate');
const output = generate({columns: ['int', 'bool'], length: 2});
console.log(output);

Other packages similar to csv-generate

csv-write-stream

A Node.js module for generating CSV files with a simple API. It differs from csv-generate by focusing more on the output stream aspect, allowing for easy writing of CSV data to files or other destinations.

fast-csv

This package provides comprehensive CSV parsing and formatting capabilities. While it includes functionality for generating CSV data, it also offers extensive support for parsing, transforming, and formatting CSV data, making it a more versatile choice compared to csv-generate.

README

CSV generator for Node.js and the web

The csv-generate package provides a flexible generator of random CSV strings and Javascript objects implementing the Node.js stream.Readable API. It is part of the CSV project.

Documentation

• Project homepage
• API
• Options
• Examples

Main features

• Scalable stream.Readable implementation
• random or pseudo-random seed based generation
• Idempotence with the "seed" option
• User-defined value generation
• Multiple types of values (integer, boolean, dates, ...)
• MIT License

Usage

Run npm install csv to install the full CSV module or run npm install csv-generate if you are only interested by the CSV generator.

Use the callback and sync APIs for simplicity or the stream based API for scalability.

Example

The API is available in multiple flavors. This example illustrates the stream API.

import { generate } from "csv-generate";
import assert from "assert";

const records = [];
// Initialize the generator
generate({
  seed: 1,
  objectMode: true,
  columns: 2,
  length: 2,
})
  // Use the readable stream api to consume generated records
  .on("readable", function () {
    let record;
    while ((record = this.read()) !== null) {
      records.push(record);
    }
  })
  // Catch any error
  .on("error", function (err) {
    console.error(err);
  })
  // Test that the generated records matched the expected records
  .on("end", function () {
    assert.deepEqual(records, [
      ["OMH", "ONKCHhJmjadoA"],
      ["D", "GeACHiN"],
    ]);
  });

Development

Tests are executed with Mocha. To install it, simple run npm install followed by npm test. It will install mocha and its dependencies in your project "node_modules" directory and run the test suite. The tests run against the CoffeeScript source files.

To generate the JavaScript files, run npm run coffee.

The test suite is run online with Travis. See the Travis definition file to view the tested Node.js version.

Contributors

The project is sponsored by Adaltas, an Big Data consulting firm based in Paris, France.

• David Worms: https://github.com/wdavidw