/**
 prendre un CSV,
 examiner toutes les colonnes et leurs valeurs,
 garder en mémoire les valeurs uniques de chaque colonne
 faire un nouveau csv qui ne montre que les valeurs uniques pour chacune des colonnes
 et qui compte le nombre de valeurs
 **/
import utils from './mappings/utils'
import {parse} from 'csv'

const fs = require('fs')
const minimist = require('minimist')

let mini_arguments: any = minimist(process.argv.slice(2))

interface VarianceType {
    [key: string]: Array<string>
}

let csv_content = 'variance de dataset\n';
let separator = ';';
let data_variance: VarianceType = {};

// const inputPath = './etalab_data/toilettes/sanisettesparis_reworked.csv'
const inputPath = './etalab_data/small.csv'
if (mini_arguments['source']) {
    inputPath = mini_arguments['source']
}
let columns_headings: Array<string> = [];
let lines_count = 0;
let longest_variance_count = 0;

console.log('open file ', inputPath)
fs.readFile(inputPath, function (err: any, fileData: any) {

    if (err) {
        throw new Error(err)
    } else {
        parse(fileData, {columns: false, trim: true}, function (err: any, rows: any) {
            // Your CSV data is in an array of arrays passed to this callback as rows.

            if(err){
                throw new Error(err)
            }
            console.log('line ', lines_count)

            console.log('rows', rows)
            rows.forEach((row: Array<any>) => {


                if (lines_count === 0) {
                    // console.log('elem', row)
                    row.forEach((value: string) => {
                        // console.log('value', value)
                        columns_headings.push(value)
                        data_variance[value] = []
                    })
                    console.log('columns_headings.length', columns_headings.length)
                    lines_count++
                } else {
                    // lignes suivantes

                    let column_index = 0;


                    row.forEach((value: string) => {
                        value = value.trim()
                        // dans chaque colonne, vérifier que la valeur n'est pas déjà présente dans les index de variance
                        // si la valeur est nouvelle, l'ajouter
                        if (data_variance[columns_headings[column_index]].indexOf(value) < 0) {
                            data_variance[columns_headings[column_index]].push(value)
                            if (
                                data_variance[columns_headings[column_index]].length > longest_variance_count
                            ) {
                                longest_variance_count = data_variance[columns_headings[column_index]].length
                            }

                        }
                        column_index++
                    })
                    lines_count++
                }
            })

            console.log('longest_variance_count', longest_variance_count)

            utils.writeFile('variance.csv', writeCSVVariance())
            // console.log('data_variance', data_variance)

        })
    }

    console.log('parsing done')
    // console.log('data_variance', data_variance)
})

/**
 * écrit un csv avec les données de variance du dataset donné
 */
function writeCSVVariance() {

    let csv_content = ';variance de ' + inputPath + ';' + new Date() + '\n'
    let columns = Object.keys(data_variance);

    // add headings
    columns_headings.forEach((heading: string) => {
        csv_content = csv_content + separator + heading
    })
    csv_content = csv_content + '\n'
    // add max length of variance for each column
    let ii = 0
    columns.forEach((column: string) => {
        // console.log('column', column, data_variance[column].length)
        csv_content = csv_content + separator + data_variance[column].length
        ii++
    })

    csv_content = csv_content + '\n\n'
    // add content of values
    for (let ii = 0; ii < longest_variance_count; ii++) {
        csv_content = csv_content + '\n'
        columns.forEach((column: any) => {
            if (ii < data_variance[column].length) {

                let currentValue = data_variance[column][ii]
                csv_content = csv_content + separator + currentValue
            } else {
                csv_content = csv_content + separator
            }
        })
    }

    return csv_content;
}