dateparser – python parser for human readable dates


Dateparser

Python parser for human readable dates

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Key Features • How To Use • Installation • Common use cases • You may also like... • License

Key Features

  • Support for almost every existing date format: absolute dates, relative dates ("two weeks ago" or "tomorrow"), timestamps, etc.

  • Support for more than 200 language locales.

  • Language autodetection

  • Customizable behavior through settings.

  • Support for non-Gregorian calendar systems.

  • Support for dates with timezones abbreviations or UTC offsets ("August 14, 2015 EST", "21 July 2013 10:15 pm +0500"…)

  • Search dates in longer texts.

  • Time span detection for expressions like “past month”, “last week”.

Online demo

Do you want to try it out without installing any dependency? Now you can test it quickly by visiting this online demo!

How To Use

The most straightforward way to parse dates with dateparser is to use the dateparser.parse() function, that wraps around most of the functionality of the module.

>>> import dateparser

>>> dateparser.parse('Fri, 12 Dec 2014 10:55:50')
datetime.datetime(2014, 12, 12, 10, 55, 50)

>>> dateparser.parse('1991-05-17')
datetime.datetime(1991, 5, 17, 0, 0)

>>> dateparser.parse('In two months')  # today is 1st Aug 2020
datetime.datetime(2020, 10, 1, 11, 12, 27, 764201)

>>> dateparser.parse('1484823450')  # timestamp
datetime.datetime(2017, 1, 19, 10, 57, 30)

>>> dateparser.parse('January 12, 2012 10:00 PM EST')
datetime.datetime(2012, 1, 12, 22, 0, tzinfo=<StaticTzInfo 'EST'>)

dateparser also works with strings in different languages:

>>> dateparser.parse('Martes 21 de Octubre de 2014')  # Spanish (Tuesday 21 October 2014)
datetime.datetime(2014, 10, 21, 0, 0)

>>> dateparser.parse('Le 11 Décembre 2014 à 09:00')  # French (11 December 2014 at 09:00)
datetime.datetime(2014, 12, 11, 9, 0)

>>> dateparser.parse('13 января 2015 г. в 13:34')  # Russian (13 January 2015 at 13:34)
datetime.datetime(2015, 1, 13, 13, 34)

>>> dateparser.parse('1 เดือนตุลาคม 2005, 1:00 AM')  # Thai (1 October 2005, 1:00 AM)
datetime.datetime(2005, 10, 1, 1, 0)

>>> dateparser.parse('yaklaşık 23 saat önce')  # Turkish (23 hours ago), current time: 12:46
datetime.datetime(2019, 9, 7, 13, 46)

>>> dateparser.parse('2小时前')  # Chinese (2 hours ago), current time: 22:30
datetime.datetime(2018, 5, 31, 20, 30)

You can specify the language(s), if known, using the languages argument. In this case, given languages are used and language detection is skipped:

>>> dateparser.parse('2015, Ago 15, 1:08 pm', languages=['pt', 'es'])
datetime.datetime(2015, 8, 15, 13, 8)

If you know the possible formats of the dates, you can use the date_formats argument:

>>> dateparser.parse('22 Décembre 2010', date_formats=['%d %B %Y'])
datetime.datetime(2010, 12, 22, 0, 0)

Relative Dates

>>> from dateparser import parse
>>> parse('1 hour ago')
datetime.datetime(2015, 5, 31, 23, 0)
>>> parse('Il ya 2 heures')  # French (2 hours ago)
datetime.datetime(2015, 5, 31, 22, 0)
>>> parse('1 anno 2 mesi')  # Italian (1 year 2 months)
datetime.datetime(2014, 4, 1, 0, 0)
>>> parse('yaklaşık 23 saat önce')  # Turkish (23 hours ago)
datetime.datetime(2015, 5, 31, 1, 0)
>>> parse('Hace una semana')  # Spanish (a week ago)
datetime.datetime(2015, 5, 25, 0, 0)
>>> parse('2小时前')  # Chinese (2 hours ago)
datetime.datetime(2015, 5, 31, 22, 0)

Note

Testing above code might return different values depending on your environment’s current date and time.

Note

For the Finnish language, please specify settings={'SKIP_TOKENS': []} to correctly parse relative dates.

Date Order

>>> # parsing ambiguous date
>>> parse('02-03-2016')  # assumes english language, uses MDY date order
datetime.datetime(2016, 2, 3, 0, 0)
>>> parse('le 02-03-2016')  # detects french, uses DMY date order
datetime.datetime(2016, 3, 2, 0, 0)

Note

Ordering is not locale-based — do not expect DMY order for UK/Australia English. You can specify date order explicitly:

>>> parse('18-12-15 06:00', settings={'DATE_ORDER': 'DMY'})
datetime.datetime(2015, 12, 18, 6, 0)

For more on date order, see the settings documentation.

Timezone and UTC Offset

By default, dateparser returns a timezone-aware datetime if a timezone is present in the date string. Otherwise it returns a naive datetime object.

>>> parse('January 12, 2012 10:00 PM EST')
datetime.datetime(2012, 1, 12, 22, 0, tzinfo=<StaticTzInfo 'EST'>)

>>> parse('January 12, 2012 10:00 PM -0500')
datetime.datetime(2012, 1, 12, 22, 0, tzinfo=<StaticTzInfo 'UTC\-05:00'>)

>>> parse('2 hours ago EST')
datetime.datetime(2017, 3, 10, 15, 55, 39, 579667, tzinfo=<StaticTzInfo 'EST'>)

If the date has no timezone name/abbreviation or offset, you can specify it using the TIMEZONE setting:

>>> parse('January 12, 2012 10:00 PM', settings={'TIMEZONE': 'US/Eastern'})
datetime.datetime(2012, 1, 12, 22, 0)

>>> parse('January 12, 2012 10:00 PM', settings={'TIMEZONE': 'US/Eastern', 'RETURN_AS_TIMEZONE_AWARE': True})
datetime.datetime(2012, 1, 12, 22, 0, tzinfo=<DstTzInfo 'US/Eastern' EST-1 day, 19:00:00 STD>)

>>> parse('10:00 am', settings={'TIMEZONE': 'EST', 'TO_TIMEZONE': 'EDT'})
datetime.datetime(2016, 9, 25, 11, 0)

>>> parse('10:00 am EST', settings={'TO_TIMEZONE': 'EDT'})
datetime.datetime(2017, 3, 12, 11, 0, tzinfo=<StaticTzInfo 'EDT'>)

For more on timezones, see the settings documentation.

Incomplete Dates

>>> from dateparser import parse
>>> parse('December 2015')  # default behavior
datetime.datetime(2015, 12, 16, 0, 0)
>>> parse('December 2015', settings={'PREFER_DAY_OF_MONTH': 'last'})
datetime.datetime(2015, 12, 31, 0, 0)
>>> parse('December 2015', settings={'PREFER_DAY_OF_MONTH': 'first'})
datetime.datetime(2015, 12, 1, 0, 0)

>>> parse('March')
datetime.datetime(2015, 3, 16, 0, 0)
>>> parse('March', settings={'PREFER_DATES_FROM': 'future'})
datetime.datetime(2016, 3, 16, 0, 0)

>>> import dateparser
>>> dateparser.parse("2015")  # default behavior
datetime.datetime(2015, 3, 27, 0, 0)
>>> dateparser.parse("2015", settings={"PREFER_MONTH_OF_YEAR": "last"})
datetime.datetime(2015, 12, 27, 0, 0)
>>> dateparser.parse("2015", settings={"PREFER_MONTH_OF_YEAR": "current"})
datetime.datetime(2015, 3, 27, 0, 0)

You can also ignore incomplete dates by setting the STRICT_PARSING flag:

>>> parse('December 2015', settings={'STRICT_PARSING': True})
None

For more on handling incomplete dates, see the settings documentation.

Search for Dates in Longer Chunks of Text

Warning

Support for date searching is limited and needs improvement. Contributions are welcome — see contributing.

You can extract dates from longer strings of text. Results are returned as a list of (substring, datetime) tuples:

>>> from dateparser.search import search_dates
>>> search_dates('Today is 25 of October 2017, so the 27th is in 2 days.')
[('25 of October 2017', datetime.datetime(2017, 10, 25, 0, 0)), ('the 27th is in 2 days', datetime.datetime(2017, 10, 27, 0, 0))]

Time Span Detection

The search_dates function can also detect time spans such as “past month” or “last week”. When RETURN_TIME_SPAN is enabled it returns start and end dates for the detected period:

>>> search_dates("Messages from the past month", settings={'RETURN_TIME_SPAN': True})
[('past month (start)', datetime.datetime(2024, 11, 7, 0, 0)),
 ('past month (end)', datetime.datetime(2024, 12, 7, 23, 59, 59, 999999))]

Settings

You can control multiple behaviors by using the settings parameter:

>>> dateparser.parse('2014-10-12', settings={'DATE_ORDER': 'YMD'})
datetime.datetime(2014, 10, 12, 0, 0)

>>> dateparser.parse('2014-10-12', settings={'DATE_ORDER': 'YDM'})
datetime.datetime(2014, 12, 10, 0, 0)

>>> dateparser.parse('1 year', settings={'PREFER_DATES_FROM': 'future'})  # Today is 2020-09-23
datetime.datetime(2021, 9, 23, 0, 0)

>>> dateparser.parse('tomorrow', settings={'RELATIVE_BASE': datetime.datetime(1992, 1, 1)})
datetime.datetime(1992, 1, 2, 0, 0)

To see all available settings, check the settings documentation.

False positives

dateparser will do its best to return a date, dealing with multiple formats and different locales. For that reason it is important that the input is a valid date, otherwise it could return false positives.

To reduce the possibility of receiving false positives, make sure that:

  • The input string is a valid date and doesn’t contain any other words or numbers.

  • If you know the language or languages beforehand, you add them through the languages or locales properties.

On the other hand, if you want to exclude any of the default parsers (timestamp, relative-time…) or change the order in which they are executed, you can do so through the settings PARSERS.

Installation

Dateparser supports Python 3.10+. You can install it by doing:

$ pip install dateparser

If you want to use the jalali or hijri calendar, you need to install the calendars extra:

$ pip install dateparser[calendars]

Supported Calendars

Apart from the Gregorian calendar, dateparser supports the Persian Jalali calendar and the Hijri/Islamic calendar. To use them, install the calendars extra (see Installation).

Example using the Persian Jalali calendar:

>>> from dateparser.calendars.jalali import JalaliCalendar
>>> JalaliCalendar('جمعه سی ام اسفند ۱۳۸۷').get_date()
DateData(date_obj=datetime.datetime(2009, 3, 20, 0, 0), period='day', locale=None)

Example using the Hijri/Islamic calendar:

>>> from dateparser.calendars.hijri import HijriCalendar
>>> HijriCalendar('17-01-1437 هـ 08:30 مساءً').get_date()
DateData(date_obj=datetime.datetime(2015, 10, 30, 20, 30), period='day', locale=None)

Dependencies

dateparser relies on the following libraries:

  • dateutil’s module relativedelta for its freshness parser.

  • convertdate to convert Jalali dates to Gregorian.

  • hijridate to convert Hijri dates to Gregorian.

  • tzlocal to reliably get local timezone.

  • ruamel.yaml (optional) for operations on language files.

Common use cases

dateparser can be used for a wide variety of purposes, but it stands out when it comes to:

Consuming data from different sources:

  • Scraping: extract dates from different places with several different formats and languages

  • IoT: consuming data coming from different sources with different date formats

  • Tooling: consuming dates from different logs / sources

  • Format transformations: when transforming dates coming from different files (PDF, CSV, etc.) to other formats (database, etc).

Offering natural interaction with users:

  • Tooling and CLI: allow users to write “3 days ago” to retrieve information.

  • Search engine: allow people to search by date in an easy / natural format.

  • Bots: allow users to interact with a bot easily

You may also like…

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  • Scrapy - Web crawling and web scraping framework

License

BSD3-Clause

Indices and tables

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