Implement `parse-dsv`

[kgryte]

Delimiter-separated values. @stdlib/utils/parse-dsv.

Note that this package is not simple. The implementation should adhere as best as possible to the various CSV RFCs and pass standard CSV parsing tests.

Ideally, this implementation should be portable and/or share a code base with a streaming variant.

[labiej]

While googling around and deciding on a course of action I found this package on npm to test an implementation.

Testing the implementation of d3-dsv this way I run into some trouble. While the output is visibly the same a test for equality failed.

Turns out you need to use tape's deepEqual method in this case. And use the spread operator to create an array without a columns property.
For future reference, this is the code I used to test the implementation

'use strict';

const spectrum = require('csv-spectrum');
const d3DSV = require('d3-dsv');
const tape = require('tape');

tape( 'Test all cases', function test ( t ) {

    spectrum( function ( err, data ) {

        for ( let testCase of data ) {
            // Convert the data to a string
            let csvDataString = testCase.csv.toString( 'utf8' );

            // Create a new array without the columns property which breaks the equality test
            let parsed = [ ...d3DSV.csvParse( csvDataString ) ];
            let control = JSON.parse( testCase.json);

            // Test type of parsed objects
            t.equal( typeof parsed, typeof control, 'testing types of sample: ' + testCase.name );

            // Test equality by value
            t.deepEqual( parsed, control, 'testing sample: ' + testCase.name );
        }
    });

    t.end();
});

[kgryte]

@labiej Thanks for looking into this!

[kgryte]

Ref: https://github.com/d3/d3-dsv

[kgryte]

CSV-spectrum: https://github.com/maxogden/csv-spectrum

[kgryte]

Papaparse: https://github.com/mholt/PapaParse

[kgryte]

RFC: https://datatracker.ietf.org/doc/html/rfc4180

[kgryte]

Python built-in CSV API: https://docs.python.org/3/library/csv.html

PEP 305: https://peps.python.org/pep-0305/

[kgryte]

GoLang: https://pkg.go.dev/encoding/csv

[kgryte]

MATLAB: https://www.mathworks.com/help/matlab/ref/csvread.html and https://www.mathworks.com/help/matlab/ref/readmatrix.html

MATLAB's API is interesting insofar as it supports reading only sections of a CSV file.

[kgryte]

Pandas: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html

Has arguably the most complex CSV read API. Some interesting features.

• Select particular columns.
• Ability to provide custom converters for particular columns.
• Comment support.
• Custom separator support (decimals, thousands, etc).
• Dialects (as in native Python CSV API)
• Support for custom date parsing.
• Support for specifying a particular column as a column of row labels

[kgryte]

Streaming CSV parser for Node: https://github.com/mafintosh/csv-parser; however, issue tracker suggests some concerns with implementation.