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Flexible automatic date extracting from strings in any formats.

Datify makes it easy to extract dates from strings in (nearly) any formats.

You will need only to parse the date string with Datify, and it's all good.

The date formats supported by Datify are the following:

  • Day first digit-only dates: 20.02.2020, 09/07/2000, 9-1-2005;
  • Month first digit-only dates: 02 22 2020, 09.07.2000, 1.9/2005;
  • Dates in the general date format: 2020-04-15;
  • Alphanumeric dates in different languages: 11th of July 2020; 6 липня 2021; 31 декабря, 2021.

See the Formats section for the detailed information about the supported formats.

The behavior of Datify can be configured with DatifyConfig - see Configuration section.

Month name languages supported by default:

  • x English
  • x Ukrainian
  • x Russian

Documentation link


See the example/datify_example.dart for the full example.

String handleRequest(SearchRequest searchRequest) {
  final dateQuery = searchRequest['date'];

  // Datify handles all the parsing inside freeing
  // you from even thinking about it!
  final res = Datify

  // make the search request
  final response =
      Events.query(year: res.year, month: res.month, day: res.day) ?? 'No events found for this query 👀';

  return response;

void main() {
  // define dates in different formats
  const dates = [
    '31.12.2021',     // common digit-only date format
    '2022-02-23',     // another commonly-used date format
    '23-02/2022',     // the supported separators can be combined in the string
    '20 of January',  // date is incomplete but still correctly parsed
    'May',            // just a month name
    '14 лютого 2022', // Ukrainian date which stands for 14.02.2022
    'not a date',     // not a date at all

  // 'request' all the dates
  for (var date in dates) {
    print('$date: ${handleRequest({'date': date})}');

/// Database emulation for the example.
/// This class stored dates and the corresponding event descriptions and provides the method for
/// record requesting from the storage.
abstract class Events {
  /// Stores the dates and the corresponding event descriptions.
  static const _records = {
    Date(year: 2021, month: 12, day: 31): 'New Year party 🎄',
    Date(year: 2022, month: 1, day: 20): 'Birthday celebration 🎁',
    Date(year: 2022, month: 2, day: 14): 'St. Valentines Day 💖',
    Date(year: 2022, month: 2, day: 23): 'The cinema attendance 📽',
    Date(year: 2022, month: 5, day: 23): 'A long-awaited Moment 🔥',

  /// Returns an event descriptions based on the provided date parts.
  /// If no date parts are provided or no corresponding event description is found, the method returns
  /// null.
  static String? query({int? year, int? month, int? day}) {
    // handle empty requests
    if (year == null && month == null && day == null) {
      return null;

    // find the first event corresponding to the given date
    final res = _records.entries
            (record) =>
            record.key.satisfies(year: year, month: month, day: day),
        orElse: () => MapEntry(Date.empty(), ''))
    return (res.isEmpty ? null : res);

The output of the example above:

31.12.2021: New Year party 🎄
2022-02-23: The cinema attendance 📽
23-02/2022: The cinema attendance 📽
20 of January: Birthday celebration 🎁
May: A long-awaited Moment 🔥
14 лютого 2022: St. Valentines Day 💖
not a date: No events found for this query 👀

Uncritical code was omitted.

Data parsing

To extract a date from a string, use the .parse constructor of the Datify class. The constructor takes a nullable input string and optional parameters year, month, and day.

After that the input string will be parsed. If the optional parameters were given, the respective object fields will have the provided values.

Datify class has the .fromValues constructor that takes only optional parameters year, month, and day to create the instance of the class without parsing, and .empty constructor that will create a Datify object with all the values set to null.

Getting the result

After the parsing is done, the result can be retrieved in a different ways:

  • If the date is complete, the result can be transformed into a DateTime object with the DateTime? date getter.

    However, if the date is incomplete, the date getter will return null.

    The result is considered complete when the year, month, and day fields of the result are not null.

    To make sure the parsed result is complete and can be transformed to a DateTime, the bool isComplete getter is used.

  • To get a non-nullable result independent of the parsing result, use the DatifyResult result getter.

    It will return a DatifyResult object which is not nullable by itself, but its fields may be null.

    The DatifyResult object has the nullable year, month, and day final fields, the isComplete and date getters that work just as the respective getters of the Datify instances. Moreover, the DatifyResult object can be transformed to a Map<String, int?> with the predefined structure. See the DatifyResult description for more details.

  • The Datify instance itself has the mutable nullable fields year, month, and day, which can be used to access the parsing result.


In the formats below, the sign $ represents any of the supported date splitters.

The $? sign represents an optional separator character (the separator may or may not be present).

  • General date format: YYYY$?MM$?DD - e.g. 20210706 or 2022-02-23 etc;

  • Alphanumeric dates in different languages - e.g. 6th of July 2021, 31st of December 2021, 20 жовтня, 1 июля etc;

    Datify tries to find different forms of month names in the natural languages where they are present.

When the dayFirst is set to true:

  • The most common digit-only date format: DD$MM$YYYY - e.g. 20.01.2022;

When the dayFirst is set to false:

  • American digit date format (the month is first): MM$DD$YYYY - e.g. 12.31.2021;

When the dayFirst is set to false, Datify will try to find the alphabetic month names before the parsing to avoid losing the month values in the strings of the format '1 of July 2020'. However, this makes the parsing a bit slower with this option enabled.

Configuring Datify

The library behavior can be customized with the DatifyConfig class fields and methods.

The following can be customized:

  1. Date splitters (., /, -, by default).

    Any of the supported splitters can be present in digit-only or alphanumeric dates (See Formats section of the documentation).

    To define a new custom separator, it must be added to the DatifyConfig.splitters set.

    For instance, to add the # separator to the config, the following syntax is used:


    After that the next Datify.parse() invocations will use the added splitter in the parsing operations.

    Splitters can also be string more than one character long

  2. Month names localization, different month aliases. By default, Datify supports English, English shortened, Ukrainian and Russian month names: {'january','jan','січень','январь',}

    More localizations can be added whenever they needed with DatifyConfig:

  • To add a new month name for the specific month, the DatifyConfig.addNewMonthName(int ordinal, String name) method is used. The ordinal argument takes int number in range 1, 12 inclusive to represent the month number.

    For example, to add the French name, Septembre, for the 9th month, the following syntax is used:

    DatifyConfig.addNewMonthName(9, 'Septembre');

    If the ordinal is not in the defined range, the StateError will be thrown.

  • To add an entire new localization, which consists of 12 ordered month names, the DatifyConfig.addNewMonthsLocale(Iterable<String> monthNames) method is used.

    The monthNames iterable must have the length of 12 and consist of the unique elements If these conditions are not satisfied, the ArgumentError will be thrown.

    For example, to add the French month localization, the following syntax is used:

    const frenchMonths = [
       'Janvier', 'Février', 'Mars', 'Avril', 'Peut', 'Juin',
       'Juillet', 'Août', 'Septembre', 'Octobre', 'Novembre', 

    Note: The months should be ordered in the months order for the correct work.


Datify was originally developed in Python in the summer of 2021, when I was working on my first pet project which needed to support user input of dates in various formats.

It was fascinating to write, and I decided to maintain the library.

In Dart implementation, there are several major logic and performance improvements;

Also, the regular expressions used in Python were replaced with the new ones, which work more predictable.