serial_csv #

High performance CSV encoder and decoder with retained types and nullability.

Introduction #

This package is intended to quickly encode and decode csv while keeping all type information.

The strict nature allows for high performance during encoding and decoding.

The following data types are supported and retained: String, int, double, bool, null.

Benchmark #

You can run the benchmark yourself with this code example.

CSV structure #

• string cells are always double-quoted
• numeric and boolean cells are not double-quoted
• null cells are encoded as empty strings
• double-quotes within cells are escaped with another double-quote
• cells are separated by commas
• every row must be terminated with \n (LF)

Usage #

You can decode with any library but be careful to encode with other libraries as you might get an invalid format.

So as long as you only use this library, you can be sure that the data types and their nullability are retained.

"a","b","c"
1,2.3,"3"
4,,true

String encoded = SerialCsv.encode([
  ['a', 'b', 'c'],
  [1, 2.3, '3'],
  ['4', null, true],
]);

List<List<dynamic>> decoded = SerialCsv.decode(encoded);

String s = decoded[0][0]; // 'a'
int i = decoded[1][0]; // 1
double d = decoded[1][1]; // 2.3
bool b = decoded[2][2]; // true
Object? n = decoded[2][1]; // null

API #

Encode #

Encode a list of rows into a csv string.

Example:

const rows = [
  ['a', 'b', 'c'],
  [1, 2, 3.2],
  ['4', null, true],
];
String encoded = SerialCsv.encode(rows);

Decode #

Decode a csv string into a list of rows.

Example:

const csv = '"a","b","c"\n1,2.3,"3"\n4,,true\n';
List<List<dynamic>> decoded = SerialCsv.decode(csv);