Summary - Advanced strings

Combine split, RegExp and StringBuffer to write a CSV parser.

Summary - Advanced strings

In this group you saw four powerful string tools: split and join for string-list conversion, replaceAll for bulk replacement, trim and padLeft for formatting, RegExp for pattern search, StringBuffer for efficient building. Now we combine them all in a CSV parser.

A CSV line holds comma-separated fields. You split with split, clean spaces with trim, validate digits with RegExp and produce a new formatted output with StringBuffer. This is string tools working together on a real task.

Exercise Your turn: parse a CSV line

Split the line "anna, 28 , paris" on the comma, clean each part with trim and join them with StringBuffer using "|" as the separator. Print the result.

Show example solution

void main() {
  final line = "anna, 28 , paris";
  final parts = line.split(",").map((s) => s.trim()).toList();
  final sb = StringBuffer();
  for (var i = 0; i < parts.length; i++) {
    if (i > 0) sb.write("|");
    sb.write(parts[i]);
  }
  print(sb.toString());
}

Exercise Your turn: validate and format fields

Split "book, 120 , 2024", trim each part. Check the third part with RegExp(r"\d{4}") using hasMatch and print the result.

Show example solution

void main() {
  final line = "book, 120 , 2024";
  final parts = line.split(",").map((s) => s.trim()).toList();
  print(RegExp(r"\d{4}").hasMatch(parts[2]));
}

Test yourself

First step to extract fields from a CSV line?
```
final line = "anna,28,paris";
final fields = line._____(",");
```
- trim
- split
- join
- pad
Show answer

split — split turns the fields into a list.
Match the CSV tools

split(",")

splits the fields
trim()

cuts spaces
RegExp(r"\d+")

validates the age
StringBuffer

builds the output

Next lesson: Defining enums

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