resetToDefaults = function(csvtext2, csvdelim=",", mustHaveField="", varName="csvdata") {
csv;
delimator;
rosarr;
jsarr;
csvMustHaveField;
rosVarName;
(viewof csvMustHaveField).value = mustHaveField;
(viewof csvMustHaveField).dispatchEvent(new Event('input', { bubbles: true }));
(viewof csv).value = csvtext2;
(viewof csv).dispatchEvent(new Event('input', { bubbles: true }));
(viewof delimator).value = csvdelim;
(viewof delimator).dispatchEvent(new Event('input', { bubbles: true }));
(viewof rosVarName).value = varName;
(viewof rosVarName).dispatchEvent(new Event('input', { bubbles: true }));
}
/* TEST ONLY - will cause undeserable side-effects if changes are made while NOT commented out below: */
// resetToDefaults(countriesCsv, ',', "", "countries")
// create a custom "CSV" parser based on the delimator selected (e.g. could be TSV or "semi-colon"-seperated-values)
semicsv = d3.dsvFormat(delimator)
// first we need to parse the data, using the "D3" DSV (aka a generic CSV) parser
jsarr = semicsv.parse(csv, csvFilter)
csvFilter = line => line[csvMustHaveField] != "" ? line : (csvMustHaveField == "" ? line : null)
// the core of the parsing is done here – essentially enumerating the parsed CSV/JS array to create script code to re-create the same array under RouterOS
rosarr = (`:global ${rosVarName} [:toarray ""];\n` + jsarr.map(line => {
let rv = `:set ${rosVarName} ($${rosVarName}, { {`
for (let k in line) {
//line[k].replace(/"/g,"'")
//k = k.replace(/"/g, "'")
rv += `"${k}"="${line[k]}";`
}
rv += "} })\n"
return rv
})).replace(/^,:/gm,":")
// an UNUSED alternative implementation that creates RouterOS "map array" with the outer array being index by one of the columns instead of numerically index
rosarrByIndex = (columnName) => (":global rosarr [:toarray \"\"];\n" + jsarr.map(line => {
let rv = `:set rosarr ($rosarr, { "${line[columnName]}"={`
for (let k in line) {
rv += `"${k}"="${line[k]}";`
}
rv += "} })\n"
return rv
})).replace(/,:/g,":")
sampleCsvSimple = `column1,column2
a1,a2
b1,b2`
// observablehq.com already has XLSX parsing built-in
// xlsx = require('https://bundle.run/xlsx@0.14.1')
table2rsc = (name, table) =>
(`:global ${name} [:toarray ""];\n` + table.map(line => {
let rv = `:set ${name} ($${name}, { {`
for (let k in line) {
//line[k].replace(/"/g,"'")
//k = k.replace(/"/g, "'")
rv += `"${k}"="${line[k]}";`
}
rv += "} })\n"
return rv
})).replace(/^,:/gm,":")
import {icon} from '@severo/fork-awesome-icons'
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Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
