Schema, validation and coercion

Say what each column should be, then check it or convert it.

Install#

dart pub add csv_plus

import 'package:csv_plus/csv_plus.dart';

Declare the columns#

final schema = CsvSchema(columns: [
  CsvColumnDef(name: 'email', type: String, required: true, pattern: r'@'),
  CsvColumnDef(name: 'age', type: int, nullable: false),
]);

Validate#

final errors = table.validate(schema); // List<CsvValidationException>
final ok = table.conformsTo(schema);   // bool

Coerce#

Validation tells you what is wrong. Coercion converts each column to its declared type, and fails loudly rather than guessing.

final typed = CsvCodec().decodeWithSchema('email,age\na@b.com,42', schema);
typed.rawData.first; // [a@b.com, 42]  (42 is an int, not "42")

final coerced = table.coerce(schema); // or coerce a table you already have

A value that will not convert, or a null in a column marked non-nullable, throws CsvParseException carrying the row and column, so the error names the cell rather than the file.

Supported types are int, double, num, bool, String and DateTime.

Strict parsing#

Schema checking is about the values. If you also want the structure checked, turn on strict mode so malformed CSV throws instead of being recovered:

final strict = CsvCodec(CsvConfig(strict: true));