fast_csv 0.2.5

Classic CSV parsers suitable for most use cases. Pretty fast parsing. With experimental event-based streaming parsing.

fast_csv

Classic CSV parsers suitable for most use cases. Pretty fast parsing. With experimental event-based streaming parsing.

Version: 0.2.5

Example of the parser usage

An example of a simple way to parse 1000K rows (53M UTF-16 code units) in chunks (by ~0.53M UTF-16 code units) using events without consuming a lot of memory (during parsing) and simultaneously saving this parsed data into a virtual database (by 10K rows per transaction).

import 'dart:async';

import 'package:fast_csv/csv_converter.dart';
import 'package:fast_csv/csv_parser.dart';

Future<void> main(List<String> args) async {
  _exampleParseString();
  await _exampleParseStreamWithEvents();
}

const _csv = '''
1997,Ford,E350,"ac, ""abs"", moon",3000.00
1999,Chevy,"Venture В«Extended EditionВ»","",4900.00
1996,Jeep,Grand Cherokee,"MUST SELL! air, moon roof, loaded",4799.00''';

Stream<String> _createStream() {
  // Create the stream with 1000000 rows
  const count = 1000 * 1000;
  final controller = StreamController<String>();
  final sink = controller.sink;
  const row = '1999,Chevy,"Venture В«Extended EditionВ»","",4900.00';
  const rowsInChunk = count ~/ 100;
  final chunk = List.generate(rowsInChunk, (i) => row).join('\n');
  print('Total data amount ${row.length * count} code units.');
  print('The data will arrive in ${chunk.length} code unit chunks.');
  var i = 0;
  Timer.periodic(Duration.zero, (timer) {
    sink.add(chunk);
    i += rowsInChunk;
    if (i < count) {
      sink.add('\n');
    }

    if (i >= count) {
      controller.close();
      timer.cancel();
    }
  });

  return controller.stream;
}

Future<void> _exampleParseStreamWithEvents() async {
  print('=========================');
  print('Start streaming parsing with events');
  // Get external data
  final stream = _createStream();
  final sw = Stopwatch();
  sw.start();
  final parser = _MyParser(() async {
    print('Saving to virtual database complete in ${sw.elapsed}');
    sw.stop();
  });

  await stream.transform(FastCsvConverter(parser: parser)).first;
}

void _exampleParseString() {
  print('=========================');
  print('Parsing string');
  final result = FastCsvConverter().convert(_csv);
  print(result.join('\n'));
  for (final row in result) {
    final car = row[1];
    final price = num.parse(row[4]);
    print('$car $price');
  }
}

class _MyParser extends CsvParser {
  final Future<void> Function()? onComplete;

  int _count = 0;

  int _totalCount = 0;

  int _transactionCount = 0;

  final List<List<String>> _rows = [];

  _MyParser([this.onComplete]);

  @override
  void beginEvent(CsvParserEvent event) {
    if (event == CsvParserEvent.startEvent) {
      _count = 0;
      _totalCount = 0;
      _transactionCount = 0;
      _rows.clear();
    }
  }

  @override
  R? endEvent<R>(CsvParserEvent event, R? result, bool ok) {
    void saveRows(bool isLast) {
      final rows = _rows.toList();
      _rows.clear();
      Timer.run(() async {
        // Asynchronous saving to the database.
        await _saveToDatabase(rows, isLast);
      });
    }

    if (ok) {
      switch (event) {
        case CsvParserEvent.rowEvent:
          final row = result as List<String>;
          _rows.add(row);
          if (_rows.length > 10000) {
            saveRows(false);
          }

          // Free memory
          result = const <String>[] as R;
          break;
        case CsvParserEvent.startEvent:
          saveRows(true);
          if (onComplete != null) {
            Timer.run(onComplete!);
          }

        default:
      }
    }

    return result;
  }

  Future<void> _saveToDatabase(List<List<String>> rows, bool isLast) async {
    _transactionCount++;
    _count += rows.length;
    _totalCount += rows.length;
    if (_count > 100000 || isLast) {
      print(
          'Saved to virtual database $_totalCount row(s) in $_transactionCount transaction(s)');
      _count = 0;
    }

    if (isLast) {
      print(
          'Totally saved to virtual database $_totalCount row(s) in $_transactionCount transaction(s)');
    }
  }
}

Output:

=========================
Parsing string
[1997, Ford, E350, ac, "abs", moon, 3000.00]
[1999, Chevy, Venture В«Extended EditionВ», , 4900.00]
[1996, Jeep, Grand Cherokee, MUST SELL! air, moon roof, loaded, 4799.00]
Ford 3000.0
Chevy 4900.0
Jeep 4799.0
=========================
Start streaming parsing with events
Total data amount 52000000 code units.
The data will arrive in 529999 code unit chunks.
Saved to virtual database 100010 row(s) in 10 transaction(s)
Saved to virtual database 200020 row(s) in 20 transaction(s)
Saved to virtual database 300030 row(s) in 30 transaction(s)
Saved to virtual database 400040 row(s) in 40 transaction(s)
Saved to virtual database 500050 row(s) in 50 transaction(s)
Saved to virtual database 600060 row(s) in 60 transaction(s)
Saved to virtual database 700070 row(s) in 70 transaction(s)
Saved to virtual database 800080 row(s) in 80 transaction(s)
Saved to virtual database 900090 row(s) in 90 transaction(s)
Saved to virtual database 1000000 row(s) in 100 transaction(s)
Totally saved to virtual database 1000000 row(s) in 100 transaction(s)
Saving to virtual database complete in 0:00:04.364904

About the implementation of parsers

Parsers are generated from PEG grammars.
Software used to generate parsers
Below is the source code for one of the grammars.

%%

const CsvParser();

%%

Start = v:Rows Eof ;

@inline
Chars = ($[^"]+ / '""' <String>{ $$ = '"'; })* ;

@inline
CloseQuote = '"' Spaces ;

@inline
Eof = !. ;

@inline
Eol = '\n' / '\r\n' / '\r' ;

@event
@inline
Field = String / Text ;

@inline
OpenQuote = Spaces '"' ;

@inline
RowEnding = Eol !Eof ;

@event
Row = @sepBy(Field, ',') ;

Rows = v:@sepBy(Row, RowEnding) Eol? ;

Spaces = [ \t]* ;

String
String = OpenQuote v:Chars CloseQuote { $$ = v.join(); } ;

Text = $[^,"\n\r]* ;

An example of using a configurable parser

This parser is slightly slower than the non-configurable parser.

The difference between using a normal parser and using a configurable parser is that you can specify a field separator.
Any value (such as a space or semicolon).

import 'package:fast_csv/fast_csv_ex.dart' as fast_csv_ex;

void main(List<String> args) {
  final result = fast_csv_ex.parse(_csv, separator: ';');
  print(result.join('\n'));
  for (final row in result) {
    final car = row[1];
    final price = num.parse(row[4]);
    print('$car $price');
  }
}

const _csv = '''
1997;Ford;E350;"ac, ""abs"", moon";3000.00
1999;Chevy;"Venture В«Extended EditionВ»";"";4900.00
1996;Jeep;Grand Cherokee;"MUST SELL! air, moon roof, loaded";4799.00
''';

About the implementation of parsers

Parsers are generated from PEG grammars.
Software used to generate parsers
Below is the source code for one of the grammars.

%%

const CsvParser();

%%

@event
Start = v:Rows Eof ;

@inline
Chars = ($[^"]+ / '""' <String>{ $$ = '"'; })* ;

@inline
CloseQuote = '"' Spaces ;

@inline
Eof = !. ;

Eol = '\n' / '\r\n' / '\r' ;

@event
@inline
Field = String / Text ;

@inline
OpenQuote = Spaces '"' ;

@inline
RowEnding = Eol !Eof ;

@event
Row = @sepBy(Field, ',') ;

Rows = v:@sepBy(Row, RowEnding) Eol? ;

Spaces = [ \t]* ;

String
String = OpenQuote v:Chars CloseQuote { $$ = v.join(); } ;

Text = $[^,"\n\r]* ;