Async and Practical

CSV Parse Lite

A tiny CSV reader is just split plus a loop. The first row is the header, the rest are data rows, and a collection-for zips header names to fields to build one map per row.

Program

Play the program to parse a 3-line CSV into records and summarize them.

csv_parse_lite.dart
Replay: real traced execution (multi-file project)
void main() {
  var csv = 'name,score\nAda,3\nLin,5';
  var lines = csv.split('\n');
  var headers = lines.first.split(',');
  var rows = <Map<String, String>>[];
  for (var line in lines.skip(1)) {
    var fields = line.split(',');
    var record = {
      for (var i = 0; i < headers.length; i++)
        headers[i]: fields[i],
    };
    rows.add(record);
  }
  var summary = rows
      .map((r) => '${r['name']}=${r['score']}')
      .join('|');
  print(summary);
}

  1. csv ← 3 lines

    1void main() {2  var csv = 'name,score\nAda,3\nLin,5';3  var lines = csv.split('\n');
    values this step3 linescsv

  2. lines ← 3 rows

    2var csv = 'name,score\nAda,3\nLin,5';3var lines = csv.split('\n');4var headers = lines.first.split(',');
    values this step3 rowslines

  3. headers ← [name, score]

    3var lines = csv.split('\n');4var headers = lines.first.split(',');5var rows = <Map<String, String>>[];
    values this step[name, score]headers

  4. rows ← []

    4var headers = lines.first.split(',');5var rows = <Map<String, String>>[];6for (var line in lines.skip(1)) {
    values this step[]rows

  5. loop ← skip header, parse rows

    5var rows = <Map<String, String>>[];6for (var line in lines.skip(1)) {7  var fields = line.split(',');
    values this stepskip header, parse rowsloop

  6. rows ← [{name:Ada,score:3}, {name:Lin,score:5}]

    11  };12  rows.add(record);13}
    values this step[{name:Ada,score:3}, {name:Lin,score:5}]rows

  7. summary ← Ada=3|Lin=5

    15    .map((r) => '${r['name']}=${r['score']}')16    .join('|');17print(summary);
    values this stepAda=3|Lin=5summary

  8. print(summary);

    16      .join('|');17  print(summary);18}
    outputAda=3|Lin=5
    values this stepAda=3|Lin=5summary
split lines `csv.split('\n')` yields one string per line; the first is the header row.
skip header `lines.skip(1)` advances past the header so the loop sees only data rows.
zip to map A collection-`for` over `headers` pairs each header name with the matching field.