Locale da_DK¶

`faker.providers.address`¶

class faker.providers.address.da_DK.Provider(generator: Any)¶

Bases: Provider

address() → str¶

Example:: ‘791 Crist Parks, Sashabury, IL 86039-9874’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.address()
...
'Heilsvej 56\n9593 Løgstør'
'Præstegårdsvej 3\n8115 Ryomgård'
'Reverdilsvej 58\n7801 Veksø Sjælland'
'Thorupgård Allé 439\n2287 Nørre Alslev'
'Rentemesterstræde 2\n9839 Terndrup'

administrative_unit() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.administrative_unit()
...
'Sjælland'
'Sjælland'
'Hovedstaden'
'Nordjylland'
'Syddanmark'

building_number() → str¶

Example:: ‘791’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.building_number()
...
'16'
'88'
'84'
'49'
'3'

city() → str¶

Example:: ‘Sashabury’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.city()
...
'Struer'
'Kongerslev'
'Spøttrup'
'Ulstrup'
'Hørve'

city_name() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.city_name()
...
'Skælskør'
'Struer'
'Brabrand'
'Kongerslev'
'Vissenbjerg'

city_suffix() → str¶

Example:: ‘town’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.city_suffix()
...
'Ville'
'Ville'
'Ville'
'Ville'
'Ville'

country() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.country()
...
'Liechtenstein'
'Usbekistan'
'Marokko'
'Bahamas'
'Guinea-Bissau'

country_code(representation: str = 'alpha-2') → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.country_code()
...
'MV'
'PS'
'NL'
'BB'
'IL'

current_country() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.current_country()
...
'Denmark'
'Denmark'
'Denmark'
'Denmark'
'Denmark'

current_country_code() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.current_country_code()
...
'DK'
'DK'
'DK'
'DK'
'DK'

dk_street_name() → str¶

This returns the name of a street, without any suffix.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.dk_street_name()
...
'Lakse'
'Vallekilde'
'Lykkebo'
'Bavnehøj'
'Heils'

postcode() → str¶

Example:: 86039-9874
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.postcode()
...
'9604'
'6647'
'3824'
'3948'
'8115'

state() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.state()
...
'Sjælland'
'Sjælland'
'Hovedstaden'
'Nordjylland'
'Syddanmark'

street_address() → str¶

Example:: ‘791 Crist Parks’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.street_address()
...
'Bavnehøjstræde 8'
'Nokken Fornstræde 4'
'Egils Allé 994'
'Bækkeskovvej 957'
'Magisterstræde 4'

street_name() → str¶

Example:: ‘Crist Parks’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.street_name()
...
'Vallekildevej'
'Heilsvej'
'Lille Thekla Allé'
'Nokken Fornstræde'
'Oldermandsgade'

street_suffix() → str¶

Example:: ‘Avenue’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.street_suffix()
...
' Allé'
'vej'
' Allé'
'vej'
'gade'

`faker.providers.automotive`¶

class faker.providers.automotive.da_DK.Provider(generator: Any)¶

Bases: Provider

Implement automotive provider for da_DK locale. Source: https://en.wikipedia.org/wiki/Vehicle_registration_plates_of_Denmark

license_plate() → str¶

Generate a license plate.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.license_plate()
...
'YN 04 876'
'PL 93 824'
'YD 94 892'
'DX 15 781'
'NK 93 877'

vin() → str¶

Generate vin number.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.vin()
...
'RT3GZYSKXXNDZ9J97'
'G0K75MX77NULDXVG4'
'16S1YMFL25CEF0V66'
'LZY7KJ8M0DJV6RLFJ'
'BCB3GX5649036SHFD'

`faker.providers.bank`¶

class faker.providers.bank.da_DK.Provider(generator: Any)¶

Bases: Provider

Implement bank provider for da_DK locale.

aba() → str¶

Generate an ABA routing transit number.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.aba()
...
'076048766'
'057593829'
'052194896'
'034115783'
'025659384'

bank_country() → str¶

Generate the bank provider’s ISO 3166-1 alpha-2 country code.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.bank_country()
...
'DK'
'DK'
'DK'
'DK'
'DK'

bban() → str¶

Generate a Basic Bank Account Number (BBAN).

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.bban()
...
'6604876475938242'
'1948924115781565'
'9387784080160975'
'3513933287115871'
'4841858398947196'

iban() → str¶

Generate an International Bank Account Number (IBAN).

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.iban()
...
'DK456604876475938242'
'DK861948924115781565'
'DK929387784080160975'
'DK383513933287115871'
'DK734841858398947196'

swift(length: int | None = None, primary: bool = False, use_dataset: bool = False) → str¶

Generate a SWIFT code.

SWIFT codes, reading from left to right, are composed of a 4 alphabet character bank code, a 2 alphabet character country code, a 2 alphanumeric location code, and an optional 3 alphanumeric branch code. This means SWIFT codes can only have 8 or 11 characters, so the value of length can only be None or the integers 8 or 11. If the value is None, then a value of 8 or 11 will randomly be assigned.

Because all 8-digit SWIFT codes already refer to the primary branch or office, the primary argument only has an effect if the value of length is 11. If primary is True and length is 11, the 11-digit SWIFT codes generated will always end in 'XXX' to denote that they belong to primary branches/offices.

For extra authenticity, localized providers may opt to include SWIFT bank codes, location codes, and branch codes used in their respective locales. If use_dataset is True, this method will generate SWIFT codes based on those locale-specific codes if included. If those codes were not included, then it will behave as if use_dataset were False, and in that mode, all those codes will just be randomly generated as per the specification.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift()
...
'YNBIDK65ZT4'
'SGQEDKSIGQ8'
'JDXCDKV4'
'LNKTDKN9'
'OQIBDK9AFZA'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=8)
...
'MYNBDKQ6'
'PMZJDK4W'
'SGQEDKSI'
'YDTZDKQ8'
'WZTEDKTG'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=8, use_dataset=True)
...
'MYNBDKQ6'
'PMZJDK4W'
'SGQEDKSI'
'YDTZDKQ8'
'WZTEDKTG'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=11)
...
'MYNBDKQ65ZT'
'PLSGDK6ISIG'
'TZIRDKJTGEV'
'PRDLDK1UN94'
'OQIBDK9AFZA'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=11, primary=True)
...
'MYNBDKQ6XXX'
'PMZJDK4WXXX'
'SGQEDKSIXXX'
'YDTZDKQ8XXX'
'WZTEDKTGXXX'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=11, use_dataset=True)
...
'MYNBDKQ65ZT'
'PLSGDK6ISIG'
'TZIRDKJTGEV'
'PRDLDK1UN94'
'OQIBDK9AFZA'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift(length=11, primary=True, use_dataset=True)
...
'MYNBDKQ6XXX'
'PMZJDK4WXXX'
'SGQEDKSIXXX'
'YDTZDKQ8XXX'
'WZTEDKTGXXX'

swift11(primary: bool = False, use_dataset: bool = False) → str¶

Generate an 11-digit SWIFT code.

This method uses swift() under the hood with the length argument set to 11. If primary is set to True, the SWIFT code will always end with 'XXX'. All 11-digit SWIFT codes use this convention to refer to the primary branch/office.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift11()
...
'MYNBDKQ65ZT'
'PLSGDK6ISIG'
'TZIRDKJTGEV'
'PRDLDK1UN94'
'OQIBDK9AFZA'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift11(use_dataset=True)
...
'MYNBDKQ65ZT'
'PLSGDK6ISIG'
'TZIRDKJTGEV'
'PRDLDK1UN94'
'OQIBDK9AFZA'

swift8(use_dataset: bool = False) → str¶

Generate an 8-digit SWIFT code.

This method uses swift() under the hood with the length argument set to 8 and with the primary argument omitted. All 8-digit SWIFT codes already refer to the primary branch/office.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift8()
...
'MYNBDKQ6'
'PMZJDK4W'
'SGQEDKSI'
'YDTZDKQ8'
'WZTEDKTG'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.swift8(use_dataset=True)
...
'MYNBDKQ6'
'PMZJDK4W'
'SGQEDKSI'
'YDTZDKQ8'
'WZTEDKTG'

`faker.providers.color`¶

class faker.providers.color.da_DK.Provider(generator: Any)¶

Bases: Provider

Implement color provider for da_DK locale. Source: https://tools.hopetrip.com.hk/web/colorcode/index-da-1.html

Generate a color in a human-friendly way.

Under the hood, this method first creates a color represented in the HSV color model and then converts it to the desired color_format. The argument hue controls the H value according to the following rules:

If the value is a number from 0 to 360, it will serve as the H value of the generated color.
If the value is a tuple/list of 2 numbers from 0 to 360, the color’s H value will be randomly selected from that range.
If the value is a valid string, the color’s H value will be randomly selected from the H range corresponding to the supplied string. Valid values are 'monochrome', 'red', 'orange', 'yellow', 'green', 'blue', 'purple', and 'pink'.

The argument luminosity influences both S and V values and is partially affected by hue as well. The finer details of this relationship are somewhat involved, so please refer to the source code instead if you wish to dig deeper. To keep the interface simple, this argument either can be omitted or can accept the following string values:'bright', 'dark', 'light', or 'random'.

The argument color_format controls in which color model the color is represented. Valid values are 'hsv', 'hsl', 'rgb', or 'hex' (default).

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(hue='red')
...
'#af2f33'
'#e02141'
'#ef6466'
'#a80a14'
'#ed9e95'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(luminosity='light')
...
'#79c3e0'
'#89ffa1'
'#96cbf7'
'#aafaff'
'#e3f495'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(hue=(100, 200), color_format='rgb')
...
'rgb(26, 155, 88)'
'rgb(9, 193, 49)'
'rgb(73, 229, 154)'
'rgb(107, 249, 166)'
'rgb(76, 204, 69)'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(hue='orange', luminosity='bright')
...
'#efc332'
'#edae65'
'#d1861d'
'#ffcc42'
'#e09533'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(hue=135, luminosity='dark', color_format='hsv')
...
'hsv(135, 96, 45)'
'hsv(135, 98, 57)'
'hsv(135, 94, 61)'
'hsv(135, 99, 47)'
'hsv(135, 94, 50)'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color(hue=(300, 20), luminosity='random', color_format='hsl')
...
'hsl(217, 94, 27)'
'hsl(40, 23, 54)'
'hsl(268, 100, 74)'
'hsl(175, 43, 31)'
'hsl(131, 47, 11)'

Generate a HSL color tuple in a human-friendly way.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color_hsl()
...
(197, 57, 32)
(132, 90, 39)
(207, 76, 65)
(183, 88, 33)
(258, 62, 73)

Generate a HSV color tuple in a human-friendly way.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color_hsv()
...
(197, 73, 51)
(132, 95, 76)
(207, 58, 92)
(183, 94, 64)
(258, 37, 90)

color_name() → str¶

Generate a color name.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color_name()
...
'Antik rubin'
'Luftoverlegenhed blå'
'Cybergult'
'Columbia Blue'
'Bistre'

Generate a RGB color tuple of integers in a human-friendly way.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color_rgb()
...
(35, 103, 130)
(9, 193, 46)
(98, 173, 234)
(9, 155, 163)
(170, 144, 229)

Generate a RGB color tuple of floats in a human-friendly way.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.color_rgb_float()
...
(0.13770000000000002, 0.4045149999999999, 0.51)
(0.038000000000000034, 0.76, 0.18239999999999984)
(0.3864000000000001, 0.6798800000000002, 0.92)
(0.03840000000000004, 0.6099200000000001, 0.64)
(0.6668999999999999, 0.5670000000000001, 0.9)

hex_color() → str¶

Generate a color formatted as a hex triplet.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.hex_color()
...
'#d82c08'
'#629f70'
'#c2094d'
'#e3e707'
'#6baa95'

rgb_color() → str¶

Generate a color formatted as a comma-separated RGB value.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.rgb_color()
...
'197,215,20'
'132,248,207'
'155,244,183'
'111,71,144'
'71,48,128'

rgb_css_color() → str¶

Generate a color formatted as a CSS rgb() function.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.rgb_css_color()
...
'rgb(197,215,20)'
'rgb(132,248,207)'
'rgb(155,244,183)'
'rgb(111,71,144)'
'rgb(71,48,128)'

safe_color_name() → str¶

Generate a web-safe color name.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.safe_color_name()
...
'turkis'
'blågrøn'
'pink'
'hvid'
'blågrøn'

safe_hex_color() → str¶

Generate a web-safe color formatted as a hex triplet.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.safe_hex_color()
...
'#ccdd11'
'#88ffcc'
'#99ffbb'
'#664499'
'#443388'

`faker.providers.company`¶

class faker.providers.company.da_DK.Provider(generator: Any)¶

Bases: Provider

bs() → str¶

Example:: ‘integrate extensible convergence’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.bs()
...
'iterate integrated e-markets'
'integrate back-end mindshare'
'synthesize wireless content'
'syndicate synergistic applications'
'productize killer mindshare'

catch_phrase() → str¶

Example:: ‘Robust full-range hub’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.catch_phrase()
...
'Networked well-modulated instruction set'
'Balanced empowering migration'
'Pre-emptive impactful toolset'
'Innovative mission-critical help-desk'
'Reduced didactic middleware'

company() → str¶

Example:: ‘Acme Ltd’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.company()
...
'Skov & Christensen ApS'
'Steffensen & Søn ApS'
'Johnsen & Jepsen A/S'
'Johansen & Søn ApS'
'Kristensen ApS'

company_suffix() → str¶

Example:: ‘Ltd’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.company_suffix()
...
'ApS'
'ApS'
'A/S'
'ApS'
'ApS'

`faker.providers.currency`¶

class faker.providers.currency.da_DK.Provider(generator: Any)¶

Bases: Provider

cryptocurrency() → Tuple[str, str]¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.cryptocurrency()
...
('XRP', 'Ripple')
('STC', 'SwiftCoin')
('BC', 'BlackCoin')
('NXT', 'Nxt')
('IOTA', 'IOTA')

cryptocurrency_code() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.cryptocurrency_code()
...
'XRP'
'STC'
'BC'
'NXT'
'IOTA'

cryptocurrency_name() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.cryptocurrency_name()
...
'Ripple'
'SwiftCoin'
'BlackCoin'
'Nxt'
'IOTA'

currency() → Tuple[str, str]¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.currency()
...
('MWK', 'Malawian kwacha')
('NZD', 'New Zealand dollar')
('BAM', 'Bosnia and Herzegovina convertible mark')
('IRR', 'Iranian rial')
('SPL', 'Seborga luigino')

currency_code() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.currency_code()
...
'MWK'
'NZD'
'BAM'
'IRR'
'SPL'

currency_name() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.currency_name()
...
'Malawian kwacha'
'New Zealand dollar'
'Bosnia and Herzegovina convertible mark'
'Iranian rial'
'Seborga luigino'

currency_symbol(code: str | None = None) → str¶

Example:: $
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.currency_symbol()
...
'$'
'$'
'KM'
'kr'
'L'

pricetag()¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.pricetag()
...
'7.604,87 kr.'
'975,93 kr.'
'54,21 kr.'
'89.241,15 kr.'
'91.565,93 kr.'

`faker.providers.date_time`¶

class faker.providers.date_time.da_DK.Provider(generator: Any)¶

Bases: Provider

am_pm() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.am_pm()
...
'PM'
'PM'
'AM'
'AM'
'PM'

century() → str¶

Example:: ‘XVII’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.century()
...
'XIII'
'XIV'
'II'
'IX'
'XVII'

Get a date string between January 1, 1970 and now.

Parameters:: pattern – Format of the date (year-month-day by default)
Example:: ‘2008-11-27’
Returns:: Date
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date()
...
'2016-03-25'
'2011-07-01'
'1993-01-10'
'1984-03-05'
'1997-12-28'

Get a Date object based on a random date between two given dates. Accepts date strings that can be recognized by strtotime().

Parameters:

start_date – Defaults to 30 years ago
end_date – Defaults to “today”

Example:

Date(‘1999-02-02’)

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_between()
...
datetime.date(2020, 1, 30)
datetime.date(2017, 6, 26)
datetime.date(2007, 5, 13)
datetime.date(2002, 7, 7)
datetime.date(2010, 1, 31)

Takes two Date objects and returns a random date between the two given dates. Accepts Date or datetime objects

Parameters:

date_start – Date
date_end – Date

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_between_dates()
...
datetime.date(2024, 9, 30)
datetime.date(2024, 9, 30)
datetime.date(2024, 9, 30)
datetime.date(2024, 9, 30)
datetime.date(2024, 9, 30)

date_object(end_datetime: datetime | None = None) → date¶

Get a date object between January 1, 1970 and now

Example:: datetime.date(2016, 9, 20)
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_object()
...
datetime.date(2016, 3, 25)
datetime.date(2011, 7, 1)
datetime.date(1993, 1, 10)
datetime.date(1984, 3, 5)
datetime.date(1997, 12, 28)

date_of_birth(tzinfo: tzinfo | None = None, minimum_age: int = 0, maximum_age: int = 115) → date¶

Generate a random date of birth represented as a Date object, constrained by optional miminimum_age and maximum_age parameters.

Parameters:

tzinfo – Defaults to None.
minimum_age – Defaults to 0.
maximum_age – Defaults to 115.

Example:

Date(‘1979-02-02’)

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_of_birth()
...
datetime.date(2006, 9, 13)
datetime.date(1996, 9, 1)
datetime.date(1957, 7, 14)
datetime.date(1938, 10, 13)
datetime.date(1968, 1, 21)

date_this_century(before_today: bool = True, after_today: bool = False) → date¶

Gets a Date object for the current century.

Parameters:

before_today – include days in current century before today
after_today – include days in current century after today

Example:

Date(‘2012-04-04’)

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_this_century()
...
datetime.date(2020, 11, 23)
datetime.date(2018, 10, 4)
datetime.date(2010, 5, 29)
datetime.date(2006, 5, 29)
datetime.date(2012, 8, 26)

date_this_decade(before_today: bool = True, after_today: bool = False) → date¶

Gets a Date object for the decade year.

Parameters:

before_today – include days in current decade before today
after_today – include days in current decade after today

Example:

Date(‘2012-04-04’)

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_this_decade()
...
datetime.date(2024, 1, 4)
datetime.date(2023, 8, 7)
datetime.date(2021, 12, 30)
datetime.date(2021, 3, 24)
datetime.date(2022, 6, 5)

date_this_month(before_today: bool = True, after_today: bool = False) → date¶

Gets a Date object for the current month.

Parameters:

before_today – include days in current month before today
after_today – include days in current month after today

Example:

dtdate(‘2012-04-04’)

Returns:

dtdate

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_this_month()
...
datetime.date(2024, 9, 25)
datetime.date(2024, 9, 22)
datetime.date(2024, 9, 13)
datetime.date(2024, 9, 8)
datetime.date(2024, 9, 15)

date_this_year(before_today: bool = True, after_today: bool = False) → date¶

Gets a Date object for the current year.

Parameters:

before_today – include days in current year before today
after_today – include days in current year after today

Example:

Date(‘2012-04-04’)

Returns:

Date

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_this_year()
...
datetime.date(2024, 8, 18)
datetime.date(2024, 7, 25)
datetime.date(2024, 4, 24)
datetime.date(2024, 3, 11)
datetime.date(2024, 5, 19)

Get a datetime object for a date between January 1, 1970 and now

Parameters:: tzinfo – timezone, instance of datetime.tzinfo subclass
Example:: datetime(‘2005-08-16 20:39:21’)
Returns:: datetime
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time()
...
datetime.datetime(2016, 3, 25, 15, 6, 29, 969792)
datetime.datetime(2011, 7, 1, 13, 37, 57, 541100)
datetime.datetime(1993, 1, 10, 0, 47, 57, 862819)
datetime.datetime(1984, 3, 5, 11, 22, 47, 821635)
datetime.datetime(1997, 12, 28, 19, 4, 9, 237220)

Get a datetime object for a date between January 1, 001 and now

Parameters:: tzinfo – timezone, instance of datetime.tzinfo subclass
Example:: datetime(‘1265-03-22 21:15:52’)
Returns:: datetime
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_ad()
...
datetime.datetime(1709, 11, 24, 17, 41, 25, 439644)
datetime.datetime(1534, 11, 29, 13, 44, 11, 424469)
datetime.datetime(852, 2, 18, 3, 10, 49, 906815)
datetime.datetime(524, 12, 25, 13, 29, 28, 791489)
datetime.datetime(1035, 9, 11, 3, 29, 50, 229424)

Get a datetime object based on a random date between two given dates. Accepts date strings that can be recognized by strtotime().

Parameters:

start_date – Defaults to 30 years ago
end_date – Defaults to “now”
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘1999-02-02 11:42:52’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_between()
...
datetime.datetime(2020, 1, 30, 23, 23, 2, 236214)
datetime.datetime(2017, 6, 27, 12, 47, 48, 808743)
datetime.datetime(2007, 5, 14, 18, 17, 29, 361449)
datetime.datetime(2002, 7, 8, 11, 28, 5, 49189)
datetime.datetime(2010, 2, 1, 14, 45, 1, 171082)

Takes two datetime objects and returns a random datetime between the two given datetimes. Accepts datetime objects.

Parameters:

datetime_start – datetime
datetime_end – datetime
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘1999-02-02 11:42:52’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_between_dates()
...
datetime.datetime(2024, 9, 30, 16, 12, 19)
datetime.datetime(2024, 9, 30, 16, 12, 19)
datetime.datetime(2024, 9, 30, 16, 12, 19)
datetime.datetime(2024, 9, 30, 16, 12, 19)
datetime.datetime(2024, 9, 30, 16, 12, 19)

date_time_this_century(before_now: bool = True, after_now: bool = False, tzinfo: tzinfo | None = None) → datetime¶

Gets a datetime object for the current century.

Parameters:

before_now – include days in current century before today
after_now – include days in current century after today
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘2012-04-04 11:02:02’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_this_century()
...
datetime.datetime(2020, 11, 24, 7, 10, 58, 343172)
datetime.datetime(2018, 10, 4, 15, 52, 45, 184440)
datetime.datetime(2010, 5, 29, 19, 55, 54, 978287)
datetime.datetime(2006, 5, 29, 12, 33, 35, 853891)
datetime.datetime(2012, 8, 26, 18, 10, 41, 893324)

date_time_this_decade(before_now: bool = True, after_now: bool = False, tzinfo: tzinfo | None = None) → datetime¶

Gets a datetime object for the decade year.

Parameters:

before_now – include days in current decade before today
after_now – include days in current decade after today
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘2012-04-04 11:02:02’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_this_decade()
...
datetime.datetime(2024, 1, 4, 19, 8, 37, 909435)
datetime.datetime(2023, 8, 7, 19, 18, 47, 859862)
datetime.datetime(2021, 12, 30, 13, 19, 20, 593737)
datetime.datetime(2021, 3, 25, 3, 16, 31, 72986)
datetime.datetime(2022, 6, 5, 21, 29, 38, 952084)

date_time_this_month(before_now: bool = True, after_now: bool = False, tzinfo: tzinfo | None = None) → datetime¶

Gets a datetime object for the current month.

Parameters:

before_now – include days in current month before today
after_now – include days in current month after today
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘2012-04-04 11:02:02’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_this_month()
...
datetime.datetime(2024, 9, 26, 1, 24, 6, 117577)
datetime.datetime(2024, 9, 23, 11, 49, 8, 853920)
datetime.datetime(2024, 9, 13, 11, 31, 59, 878384)
datetime.datetime(2024, 9, 8, 16, 24, 6, 753829)
datetime.datetime(2024, 9, 16, 4, 7, 57, 197831)

date_time_this_year(before_now: bool = True, after_now: bool = False, tzinfo: tzinfo | None = None) → datetime¶

Gets a datetime object for the current year.

Parameters:

before_now – include days in current year before today
after_now – include days in current year after today
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘2012-04-04 11:02:02’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.date_time_this_year()
...
datetime.datetime(2024, 8, 19, 2, 20, 9, 822688)
datetime.datetime(2024, 7, 26, 10, 24, 0, 394947)
datetime.datetime(2024, 4, 25, 2, 24, 1, 716827)
datetime.datetime(2024, 3, 11, 20, 37, 6, 116806)
datetime.datetime(2024, 5, 19, 22, 9, 26, 363836)

day_of_month() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.day_of_month()
...
'25'
'01'
'10'
'05'
'28'

day_of_week()¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.day_of_week()
...
'lørdag'
'lørdag'
'mandag'
'tirsdag'
'mandag'

Get a Date object based on a random date between 1 day from now and a given date. Accepts date strings that can be recognized by strtotime().

Parameters:

end_date – Defaults to “+30d”
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

dtdate(‘2030-01-01’)

Returns:

dtdate

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.future_date()
...
datetime.date(2024, 10, 25)
datetime.date(2024, 10, 22)
datetime.date(2024, 10, 13)
datetime.date(2024, 10, 8)
datetime.date(2024, 10, 15)

Get a datetime object based on a random date between 1 second form now and a given date. Accepts date strings that can be recognized by strtotime().

Parameters:

end_date – Defaults to “+30d”
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘1999-02-02 11:42:52’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.future_datetime()
...
datetime.datetime(2024, 10, 26, 0, 11, 20, 594731)
datetime.datetime(2024, 10, 23, 9, 55, 57, 54467)
datetime.datetime(2024, 10, 13, 7, 1, 1, 116942)
datetime.datetime(2024, 10, 8, 10, 37, 31, 957843)
datetime.datetime(2024, 10, 16, 0, 19, 23, 566513)

Get a timestamp in ISO 8601 format (or one of its profiles).

Parameters:

tzinfo – timezone, instance of datetime.tzinfo subclass
sep – separator between date and time, defaults to ‘T’
timespec – format specifier for the time part, defaults to ‘auto’ - see datetime.isoformat() documentation

Example:

‘2003-10-21T16:05:52+0000’

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.iso8601()
...
'2016-03-25T15:06:29.969792'
'2011-07-01T13:37:57.541100'
'1993-01-10T00:47:57.862819'
'1984-03-05T11:22:47.821635'
'1997-12-28T19:04:09.237220'

month() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.month()
...
'03'
'07'
'01'
'03'
'12'

month_name()¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.month_name()
...
'marts'
'juli'
'januar'
'marts'
'decembder'

Get a Date object based on a random date between a given date and 1 day ago. Accepts date strings that can be recognized by strtotime().

Parameters:

start_date – Defaults to “-30d”
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

dtdate(‘1999-02-02’)

Returns:

dtdate

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.past_date()
...
datetime.date(2024, 9, 24)
datetime.date(2024, 9, 21)
datetime.date(2024, 9, 12)
datetime.date(2024, 9, 7)
datetime.date(2024, 9, 14)

Get a datetime object based on a random date between a given date and 1 second ago. Accepts date strings that can be recognized by strtotime().

Parameters:

start_date – Defaults to “-30d”
tzinfo – timezone, instance of datetime.tzinfo subclass

Example:

datetime(‘1999-02-02 11:42:52’)

Returns:

datetime

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.past_datetime()
...
datetime.datetime(2024, 9, 26, 0, 11, 19, 594731)
datetime.datetime(2024, 9, 23, 9, 55, 56, 54467)
datetime.datetime(2024, 9, 13, 7, 1, 0, 116942)
datetime.datetime(2024, 9, 8, 10, 37, 30, 957843)
datetime.datetime(2024, 9, 16, 0, 19, 22, 566513)

pytimezone(*args: Any, **kwargs: Any) → tzinfo | None¶

Generate a random timezone (see faker.timezone for any args) and return as a python object usable as a tzinfo to datetime or other fakers.

Example:: faker.pytimezone()
Returns:: dateutil.tz.tz.tzfile
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.pytimezone()
...
tzfile('/usr/share/zoneinfo/Indian/Maldives')
tzfile('/usr/share/zoneinfo/America/Barbados')
tzfile('/usr/share/zoneinfo/Europe/Stockholm')
tzfile('/usr/share/zoneinfo/Africa/Windhoek')
tzfile('/usr/share/zoneinfo/Asia/Qatar')

Get a time string (24h format by default)

Parameters:: pattern – format
Example:: ‘15:02:34’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.time()
...
'15:06:29'
'13:37:57'
'00:47:57'
'11:22:47'
'19:04:09'

Get a timedelta object

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.time_delta()
...
datetime.timedelta(0)
datetime.timedelta(0)
datetime.timedelta(0)
datetime.timedelta(0)
datetime.timedelta(0)

Get a time object

Example:: datetime.time(15, 56, 56, 772876)
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.time_object()
...
datetime.time(15, 6, 29, 969792)
datetime.time(13, 37, 57, 541100)
datetime.time(0, 47, 57, 862819)
datetime.time(11, 22, 47, 821635)
datetime.time(19, 4, 9, 237220)

Returns a generator yielding tuples of (<datetime>, <value>).

The data points will start at start_date, and be at every time interval specified by precision. distrib is a callable that accepts <datetime> and returns <value>

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.time_series()
...
<generator object Provider.time_series at 0x7f5fb4400040>
<generator object Provider.time_series at 0x7f5fb4400040>
<generator object Provider.time_series at 0x7f5fb4400040>
<generator object Provider.time_series at 0x7f5fb4400040>
<generator object Provider.time_series at 0x7f5fb4400040>

timezone() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.timezone()
...
'Indian/Maldives'
'America/Barbados'
'Europe/Stockholm'
'Africa/Windhoek'
'Asia/Qatar'

Get a timestamp between January 1, 1970 and now, unless passed explicit start_datetime or end_datetime values.

On Windows, the decimal part is always 0.

Example:: 1061306726.6
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.unix_time()
...
1458918389.9697921
1309527477.5410995
726626877.8628191
447333767.82163477
883335849.2372204

year() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.year()
...
'2016'
'2011'
'1993'
'1984'
'1997'

`faker.providers.job`¶

class faker.providers.job.da_DK.Provider(generator: Any)¶

Bases: Provider

Source: https://star.dk/it/saadan-arbejder-vi-med-it-i-styrelsen/oversigt-over-stillingsbetegnelser-og-kvalifikationer/. # NOQA

job() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.job()
...
'Fotograf'
'Bibliotekschef'
'Procesoperatør'
'Turistchef'
'IT-supporterelev'

`faker.providers.lorem`¶

class faker.providers.lorem.da_DK.Provider(generator: Any)¶

Bases: Provider

Implement lorem provider for da_DK locale. # NOQA

get_words_list(part_of_speech: str | None = None, ext_word_list: Sequence[str] | None = None) → List[str]¶

Get list of words.

ext_word_list is a parameter that allows the user to provide a list of words to be used instead of the built-in word list. If ext_word_list is provided, then the value of part_of_speech is ignored.

part_of_speech is a parameter that defines to what part of speech the returned word belongs. If ext_word_list is not None, then part_of_speech is ignored. If the value of part_of_speech does not correspond to an existent part of speech according to the set locale, then an exception is raised.

Warning

Depending on the length of a locale provider’s built-in word list or on the length of ext_word_list if provided, a large nb can exhaust said lists if unique is True, raising an exception.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.get_words_list(part_of_speech="abc", ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.get_words_list(ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']
['abc', 'def', 'ghi', 'jkl']

paragraph(nb_sentences: int = 3, variable_nb_sentences: bool = True, ext_word_list: Sequence[str] | None = None) → str¶

Generate a paragraph.

The nb_sentences argument controls how many sentences the paragraph will contain, and setting variable_nb_sentences to False will generate the exact amount, while setting it to True (default) will generate a random amount (+/-40%, minimum of 1) using randomize_nb_elements().

Under the hood, sentences() is used to generate the sentences, so the argument ext_word_list works in the same way here as it would in that method.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraph(nb_sentences=5)
...
'Følelse våben regn umulig rådgiver junior. Sommetider forudsige butik pæn nederlag fabrikant. Informere fortælle måler kommunikere sandsynligvis. Reagere hvordan kvarter sværge. Fase strategi ønske information.'
'Kerne billede celle umulig transportør par bevægelse. Verden distrikt initial arbejder på måne hun lethed. Højttaler tegne respekt senere synes. Overalt peber struktur brev rig køre brændstof. Facilitet til træt tælle angreb. Vend køkken lille betyder bestemme observation.'
'Medier sektor plukke familie kraft forbrydelse diagram. Kvarter tung udgave billede hed fyr alkohol. Grave meget omfavne japansk søn magtfulde. Konto forskellige træt jo.'
'Bære rejse måler psykolog arbejde. Alternativ altid sandsynligvis uddanne TV forvirring. Top møde rig fysisk bage jeg senere. At politisk udvidelse miljømæssigt.'
'Tjene ville moderne ret rør tryk professor. Tre struktur røg cykle afvige. Altid indtægter fremstille tillid mandskab indkomst umulig forbi.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraph(nb_sentences=5, variable_nb_sentences=False)
...
'Holde mirakel smerte religion langt søg. Junior tillid skade karakter nå. Nederlag fabrikant sang fed. Via mål reagere hvordan kvarter sværge altid lag. Ønske information fødselsdag kerne billede celle umulig transportør.'
'Nærme erhverve lænke dræbe. Væg skuldertræk sandhed. Tilladelse celle de godt højttaler tegne. Opbevaring forbrydelse start korrekt provins have solid. Vidner udvej funktion facilitet.'
'Vidner bruge senere villig vend køkken lille betyder. Køn produktion skib. Sektor plukke familie kraft. Hvordan live funktion gård. Grad pie pensionering også mad følge grave.'
'Type tur stående opførsel grøntsag konto forskellige. Metode fylde arbejder mandskab grine sprog sammenhæng køre. Altid sandsynligvis uddanne TV. Spids moderne top møde rig fysisk bage. Gård enhed adgang at.'
'Fuld hemmelighed fuldt. Tjene ville moderne ret rør tryk professor. Tre struktur røg cykle afvige. Altid indtægter fremstille tillid mandskab indkomst umulig forbi. Styrke tanke snart fylde udenlandsk.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraph(nb_sentences=5, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'Abc jkl def jkl jkl jkl. Ghi jkl ghi def jkl ghi. Jkl ghi ghi ghi abc. Ghi jkl ghi def. Def def ghi abc.'
'Def ghi abc jkl jkl abc jkl. Abc def jkl abc def jkl abc ghi. Jkl abc ghi abc jkl. Jkl def def def abc def jkl. Jkl ghi ghi def ghi. Def abc abc jkl abc jkl.'
'Abc ghi abc abc abc abc ghi. Ghi jkl ghi ghi abc abc ghi. Ghi def ghi jkl jkl jkl. Def abc ghi def.'
'Abc def ghi def abc. Jkl abc abc ghi abc ghi. Ghi abc abc abc jkl abc abc. Abc abc jkl abc.'
'Abc jkl jkl abc def abc def. Abc def def abc def. Abc jkl abc def ghi jkl jkl abc.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraph(nb_sentences=5, variable_nb_sentences=False, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'Jkl def def ghi def jkl. Jkl def jkl abc abc. Jkl ghi def jkl. Jkl def ghi jkl ghi def abc def. Ghi abc ghi def ghi abc jkl jkl.'
'Ghi def jkl ghi. Ghi jkl def. Ghi abc jkl abc jkl abc. Def abc def ghi jkl abc ghi. Ghi jkl ghi jkl.'
'Ghi def abc jkl def abc abc jkl. Ghi ghi def. Ghi abc abc abc. Jkl jkl ghi def. Def jkl jkl jkl ghi jkl ghi.'
'Def ghi ghi jkl def def abc. Ghi jkl abc ghi abc abc jkl def. Abc abc ghi abc. Ghi jkl ghi abc abc abc jkl. Def def jkl abc.'
'Abc jkl ghi. Abc jkl jkl abc def abc def. Abc def def abc def. Abc jkl abc def ghi jkl jkl abc. Jkl abc ghi jkl def.'

paragraphs(nb: int = 3, ext_word_list: Sequence[str] | None = None) → List[str]¶

Generate a list of paragraphs.

This method uses paragraph() under the hood to generate paragraphs, and the nb argument controls exactly how many sentences the list will contain. The ext_word_list argument works in exactly the same way as well.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraphs(nb=5)
...
['Følelse våben regn umulig rådgiver junior. Sommetider forudsige butik pæn nederlag fabrikant. Informere fortælle måler kommunikere sandsynligvis.', 'Hvordan kvarter sværge altid. Strategi ønske information fødselsdag kerne billede.', 'Transportør par bevægelse instruktion kriterier klatre væg. Arbejder på måne hun lethed over.', 'Opbevaring forbrydelse start korrekt provins have solid. Vidner udvej funktion facilitet.', 'Træt tælle angreb forpligtelse trick hård nu. Bestemme observation mørk medier. Afsnit live bruser hvordan. Kvarter tung udgave billede hed fyr alkohol.']
['Grad type tur stående opførsel grøntsag konto forskellige. Metode fylde arbejder mandskab grine sprog sammenhæng køre. Altid sandsynligvis uddanne TV.', 'Top møde rig fysisk bage jeg senere. At politisk udvidelse miljømæssigt. Tilføjelse tale cykle alkohol.', 'Direktør omsorg kant tre struktur røg. Major andet altid indtægter. Mørk gammel regnet via sukker.', 'Argument politik lave nummer. Angreb kerne vest te.', 'Minde de levested mig sol kan ventilator. Spændende jo TV hvorfor alder høj afhængig. Universel investere skade oversætte ekspert.']
['Koncentration skuldertræk forbrydelse ekstraordinær fisk anden. Terrorist parkering opmærksomhed misbrug længde.', 'Fjerde sind bold forventer professor design anerkende. Forudsige til område kraft på tung dårligst. Fysisk brygge konsensus krig profil deltage.', 'Strategi barn nyttig nødvendig find bygge. Svare film endelig virkelighed. Altid oversætte vane os.', 'Uddannelse forskellige virkelig virksomhed øge print forskellige. Sommer station følelse ansvarlig.', 'Album republikansk fed problem desperat massiv. Bevare via ønske psykolog stof faktisk træt. Store rejse formue.']
['Bjørn direktør bred skulle. Vej øjeblik fejl ved ivrige penge medicinsk spørge. Repræsentant virkelighed omsorg værdi vil annonce bombe.', 'Rig artikel signal især jo ankomme. Hør økonom indlysende eliminere. Spise videnskab desperat cykle.', 'Passager bag relevant sikkert.', 'Punkt undersøgelse indtægter mørk garanti. Hun forskellige betyder henvise offer hal. Forklare erkende faktisk problem lyd. Permanent sager pulver markedsføring strategisk.', 'Opførsel placere fond alkohol kunde kontrast de vise. Programmmere kategori minde respekt masser viden måler.']
['Forekomme placere virkelig flaske bruser model. Efterår videnskab forhandling andet stor følelse vente. Skyde anden placere produktion faret butik borgmester.', 'Forvirring sektor lige. Sjovt begavet erstatte ned samling stjerne konstant helikopter. Køretøj datter overvinde hjerte udvikling kirke.', 'Støj køre distrikt årti konstant fejre forpligtelse. Celle ønske sikker bruge rådgiver beløb.', 'Ungdom skygge mejse nyttig universel dag deltage.', 'Væg tilhører vælge. Berømthed hjerte stjerne ekspert selvom stående levested. Frokost mord retfærdig passe kul.']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.paragraphs(nb=5, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['Abc jkl def jkl jkl jkl. Ghi jkl ghi def jkl ghi. Jkl ghi ghi ghi abc.', 'Jkl ghi def abc. Def ghi abc ghi def ghi.', 'Jkl abc jkl ghi jkl ghi ghi. Abc def jkl abc ghi abc.', 'Def abc def ghi jkl abc ghi. Ghi jkl ghi jkl.', 'Ghi def ghi def ghi def abc. Abc jkl def abc. Jkl jkl jkl jkl. Ghi jkl ghi ghi abc abc ghi.']
['Def def ghi ghi jkl def def abc. Ghi jkl abc ghi abc abc jkl def. Abc abc ghi abc.', 'Ghi abc abc abc jkl abc abc. Abc abc jkl abc. Def ghi abc ghi.', 'Ghi jkl abc abc def def. Ghi abc abc jkl. Def jkl def jkl ghi.', 'Jkl abc abc ghi. Ghi def abc def.', 'Jkl jkl ghi def ghi abc ghi. Ghi def abc def abc jkl def. Ghi ghi jkl jkl abc.']
['Ghi jkl abc ghi ghi abc. Ghi def jkl ghi def.', 'Def ghi abc def def abc ghi. Jkl ghi abc abc def jkl abc. Abc jkl ghi abc ghi jkl.', 'Def abc ghi abc jkl ghi. Abc ghi abc def. Abc jkl def abc.', 'Jkl abc def ghi jkl ghi abc. Def abc abc ghi.', 'Jkl jkl jkl abc ghi ghi. Ghi jkl ghi def ghi abc ghi. Abc def def.']
['Def ghi abc abc. Def def ghi def def abc abc abc. Ghi def jkl def abc ghi def.', 'Abc abc def abc def ghi. Jkl ghi def jkl. Abc abc ghi abc.', 'Def ghi def def.', 'Def def jkl def jkl. Abc abc jkl jkl abc ghi. Abc def abc abc jkl. Ghi abc def def jkl.', 'Jkl abc def ghi jkl def jkl def. Jkl ghi jkl ghi jkl abc ghi.']
['Abc abc def jkl jkl ghi. Abc abc jkl abc abc abc abc. Def abc abc ghi jkl ghi jkl.', 'Ghi ghi jkl. Jkl ghi jkl abc ghi ghi jkl def. Ghi abc jkl abc jkl ghi.', 'Ghi def def def jkl jkl def. Abc ghi abc def jkl abc.', 'Def def jkl ghi ghi abc jkl.', 'Ghi def abc. Jkl abc ghi abc def ghi ghi. Def jkl def jkl ghi.']

sentence(nb_words: int = 6, variable_nb_words: bool = True, ext_word_list: Sequence[str] | None = None) → str¶

Generate a sentence.

The nb_words argument controls how many words the sentence will contain, and setting variable_nb_words to False will generate the exact amount, while setting it to True (default) will generate a random amount (+/-40%, minimum of 1) using randomize_nb_elements().

Under the hood, words() is used to generate the words, so the argument ext_word_list works in the same way here as it would in that method.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentence(nb_words=10)
...
'Holde mirakel smerte religion langt søg disse skib sommetider forudsige.'
'Nå nå hundrede uddannelse informere fortælle måler kommunikere sandsynligvis aften møde procedure.'
'Sværge altid lag kul forurening styrke frembringe plante mørk lige.'
'Transportør par bevægelse instruktion kriterier klatre væg skuldertræk sandhed tegning tilladelse celle de.'
'Over junior højttaler opbevaring forbrydelse start korrekt provins.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentence(nb_words=10, variable_nb_words=False)
...
'Imod holde mirakel smerte religion langt søg disse skib sommetider.'
'Forudsige butik pæn nederlag fabrikant sang fed opførsel baggrund via.'
'Mål reagere hvordan kvarter sværge altid lag kul forurening styrke.'
'Frembringe plante mørk lige fejl andre nærme erhverve lænke dræbe.'
'Verden distrikt initial arbejder på måne hun lethed over junior.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentence(nb_words=10, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'Jkl def def ghi def jkl def def ghi jkl.'
'Abc abc abc jkl jkl ghi ghi ghi abc abc abc jkl.'
'Def abc def ghi jkl jkl def jkl def jkl.'
'Jkl abc jkl ghi jkl ghi ghi jkl def ghi ghi abc jkl.'
'Abc jkl jkl def abc def ghi jkl.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentence(nb_words=10, variable_nb_words=True, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'Jkl def def ghi def jkl def def ghi jkl.'
'Abc abc abc jkl jkl ghi ghi ghi abc abc abc jkl.'
'Def abc def ghi jkl jkl def jkl def jkl.'
'Jkl abc jkl ghi jkl ghi ghi jkl def ghi ghi abc jkl.'
'Abc jkl jkl def abc def ghi jkl.'

sentences(nb: int = 3, ext_word_list: Sequence[str] | None = None) → List[str]¶

Generate a list of sentences.

This method uses sentence() under the hood to generate sentences, and the nb argument controls exactly how many sentences the list will contain. The ext_word_list argument works in exactly the same way as well.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentences()
...
['Holde mirakel smerte religion langt søg.', 'Junior tillid skade karakter nå.', 'Nederlag fabrikant sang fed.']
['Via mål reagere hvordan kvarter sværge altid lag.', 'Ønske information fødselsdag kerne billede celle umulig transportør.', 'Nærme erhverve lænke dræbe.']
['Væg skuldertræk sandhed.', 'Tilladelse celle de godt højttaler tegne.', 'Opbevaring forbrydelse start korrekt provins have solid.']
['Vidner udvej funktion facilitet.', 'Vidner bruge senere villig vend køkken lille betyder.', 'Køn produktion skib.']
['Sektor plukke familie kraft.', 'Hvordan live funktion gård.', 'Grad pie pensionering også mad følge grave.']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentences(nb=5)
...
['Holde mirakel smerte religion langt søg.', 'Junior tillid skade karakter nå.', 'Nederlag fabrikant sang fed.', 'Via mål reagere hvordan kvarter sværge altid lag.', 'Ønske information fødselsdag kerne billede celle umulig transportør.']
['Nærme erhverve lænke dræbe.', 'Væg skuldertræk sandhed.', 'Tilladelse celle de godt højttaler tegne.', 'Opbevaring forbrydelse start korrekt provins have solid.', 'Vidner udvej funktion facilitet.']
['Vidner bruge senere villig vend køkken lille betyder.', 'Køn produktion skib.', 'Sektor plukke familie kraft.', 'Hvordan live funktion gård.', 'Grad pie pensionering også mad følge grave.']
['Type tur stående opførsel grøntsag konto forskellige.', 'Metode fylde arbejder mandskab grine sprog sammenhæng køre.', 'Altid sandsynligvis uddanne TV.', 'Spids moderne top møde rig fysisk bage.', 'Gård enhed adgang at.']
['Fuld hemmelighed fuldt.', 'Tjene ville moderne ret rør tryk professor.', 'Tre struktur røg cykle afvige.', 'Altid indtægter fremstille tillid mandskab indkomst umulig forbi.', 'Styrke tanke snart fylde udenlandsk.']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.sentences(nb=5, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['Jkl def def ghi def jkl.', 'Jkl def jkl abc abc.', 'Jkl ghi def jkl.', 'Jkl def ghi jkl ghi def abc def.', 'Ghi abc ghi def ghi abc jkl jkl.']
['Ghi def jkl ghi.', 'Ghi jkl def.', 'Ghi abc jkl abc jkl abc.', 'Def abc def ghi jkl abc ghi.', 'Ghi jkl ghi jkl.']
['Ghi def abc jkl def abc abc jkl.', 'Ghi ghi def.', 'Ghi abc abc abc.', 'Jkl jkl ghi def.', 'Def jkl jkl jkl ghi jkl ghi.']
['Def ghi ghi jkl def def abc.', 'Ghi jkl abc ghi abc abc jkl def.', 'Abc abc ghi abc.', 'Ghi jkl ghi abc abc abc jkl.', 'Def def jkl abc.']
['Abc jkl ghi.', 'Abc jkl jkl abc def abc def.', 'Abc def def abc def.', 'Abc jkl abc def ghi jkl jkl abc.', 'Jkl abc ghi jkl def.']

text(max_nb_chars: int = 200, ext_word_list: Sequence[str] | None = None) → str¶

Generate a text string.

The max_nb_chars argument controls the approximate number of characters the text string will have, and depending on its value, this method may use either words(), sentences(), or paragraphs() for text generation. The ext_word_list argument works in exactly the same way it would in any of those methods.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.text(max_nb_chars=20)
...
'Overvinde øjeblik.'
'Vagt klinge bred.'
'Indtægter modtage.'
'Længde urban flad.'
'Mål høre sikkert.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.text(max_nb_chars=80)
...
'Holde mirakel smerte religion langt søg. Junior tillid skade karakter nå.'
'Via mål reagere hvordan kvarter sværge altid lag.'
'Nærme erhverve lænke dræbe. Væg skuldertræk sandhed.'
'Opbevaring forbrydelse start korrekt provins have solid.'
'Vidner bruge senere villig vend køkken lille betyder. Køn produktion skib.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.text(max_nb_chars=160)
...
'Følelse våben regn umulig rådgiver junior. Sommetider forudsige butik pæn nederlag fabrikant. Informere fortælle måler kommunikere sandsynligvis.'
'Transportør par bevægelse instruktion kriterier klatre væg. Arbejder på måne hun lethed over.'
'Træt tælle angreb forpligtelse trick hård nu. Bestemme observation mørk medier. Afsnit live bruser hvordan. Kvarter tung udgave billede hed fyr alkohol.'
'Top møde rig fysisk bage jeg senere. At politisk udvidelse miljømæssigt. Tilføjelse tale cykle alkohol.'
'Argument politik lave nummer. Angreb kerne vest te.'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.text(ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'Abc jkl def jkl jkl jkl. Ghi jkl ghi def jkl ghi. Jkl ghi ghi ghi abc.\nJkl ghi def abc. Def ghi abc ghi def ghi.\nJkl abc jkl ghi jkl ghi ghi. Abc def jkl abc ghi abc.'
'Ghi def ghi def ghi def abc. Abc jkl def abc. Jkl jkl jkl jkl. Ghi jkl ghi ghi abc abc ghi.\nDef def ghi ghi jkl def def abc. Ghi jkl abc ghi abc abc jkl def. Abc abc ghi abc.'
'Ghi jkl abc abc def def. Ghi abc abc jkl. Def jkl def jkl ghi.\nJkl abc abc ghi. Ghi def abc def.\nJkl jkl ghi def ghi abc ghi. Ghi def abc def abc jkl def. Ghi ghi jkl jkl abc.'
'Def ghi abc def def abc ghi. Jkl ghi abc abc def jkl abc. Abc jkl ghi abc ghi jkl.\nDef abc ghi abc jkl ghi. Abc ghi abc def. Abc jkl def abc.\nJkl abc def ghi jkl ghi abc. Def abc abc ghi.'
'Def ghi abc abc. Def def ghi def def abc abc abc. Ghi def jkl def abc ghi def.\nAbc abc def abc def ghi. Jkl ghi def jkl. Abc abc ghi abc.\nDef ghi def def.'

texts(nb_texts: int = 3, max_nb_chars: int = 200, ext_word_list: Sequence[str] | None = None) → List[str]¶

Generate a list of text strings.

The nb_texts argument controls how many text strings the list will contain, and this method uses text() under the hood for text generation, so the two remaining arguments, max_nb_chars and ext_word_list will work in exactly the same way as well.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.texts(nb_texts=5)
...
['Følelse våben regn umulig rådgiver junior. Sommetider forudsige butik pæn nederlag fabrikant. Informere fortælle måler kommunikere sandsynligvis.', 'Transportør par bevægelse instruktion kriterier klatre væg. Arbejder på måne hun lethed over.\nOpbevaring forbrydelse start korrekt provins have solid. Vidner udvej funktion facilitet.', 'Grad type tur stående opførsel grøntsag konto forskellige. Metode fylde arbejder mandskab grine sprog sammenhæng køre. Altid sandsynligvis uddanne TV.', 'Direktør omsorg kant tre struktur røg. Major andet altid indtægter. Mørk gammel regnet via sukker.\nArgument politik lave nummer. Angreb kerne vest te.', 'Koncentration skuldertræk forbrydelse ekstraordinær fisk anden. Terrorist parkering opmærksomhed misbrug længde.']
['Strategi barn nyttig nødvendig find bygge. Svare film endelig virkelighed. Altid oversætte vane os.\nUddannelse forskellige virkelig virksomhed øge print forskellige. Sommer station følelse ansvarlig.', 'Bjørn direktør bred skulle. Vej øjeblik fejl ved ivrige penge medicinsk spørge. Repræsentant virkelighed omsorg værdi vil annonce bombe.', 'Passager bag relevant sikkert.', 'Opførsel placere fond alkohol kunde kontrast de vise. Programmmere kategori minde respekt masser viden måler.', 'Forvirring sektor lige. Sjovt begavet erstatte ned samling stjerne konstant helikopter. Køretøj datter overvinde hjerte udvikling kirke.']
['Ungdom skygge mejse nyttig universel dag deltage.\nVæg tilhører vælge. Berømthed hjerte stjerne ekspert selvom stående levested. Frokost mord retfærdig passe kul.', 'Leje borgmester andet vellykket. Kage begreb senat. Central mord nogle sats ovn. Mirakel data taske rør udgør brændstof henviser.', 'Kant fordi faktisk information universel republikansk. Brug ved spejl provins.\nTilbud fordel korn defensiv. Offer direkte jo had.', 'Bevæbnet bold ekspert hjerte overveje møde. Værdi udbredt foreslog reb ressource genetisk.\nTid terrorist nummer årsag plads udvidelse. Vital gensidig snor senere genkende vil.', 'Anholdelse karakter aldrig talt struktur gear frihed radio. Sektor support oplade rose. Tid politisk skulder dræbe område.']
['Tjene rød vågne løg spændende gammel sommer kerne. Kæledyr design uddanne muskel reb nå dræbe. Tid guld karakter sikkert sikkerhed type.', 'Midt bred direktør brygge forberedelse diagram. Hende syg hun lag sjæl.\nSkyde levested ankomme placere. Udgave udmelding attribut tælle. Forhandler skygge reagere søge angst information.', 'Vigtig stemme forhandling radio investering hus væsentligt netværk. Lastbil levested vidner formode klinge stil hit.', 'Vellykket billede svare forbrydelse hals heller. Imidlertid reagere struktur gevinst forpligtelse. Kontanter bevare tusind institution rækkevidde fiktion kyst.\nTalt fiktion forklare os aften tilmeld.', 'Musikalsk garanti kunne anholdelse spids. Ord forklare søg aften sekvens. Karakter afstand overalt midt samling.']
['Synlig spids pie afsnit finansiel jeres. Igennem ned transportør opdage. Hed ekspert datter forpligtelse film.', 'Fødsel tilladelse betyder kriterier. Flyselskab direkte blå brug bedst fundament.\nKorn læge bære forvirring tanke. Dag politisk sats åben tusind stor virksomhed efterår.', 'Invitere mysterium forsvinde adgang samme matematik.\nOpnå eventuelt ligge store. Bevægelse diagram ur rapport skuldertræk jeres bekostning. Guld indkomst dem nyttig.', 'Fejre støj årti. Sofistikeret psykologi afgørende. Miljø interview reduktion tab ansvarlig byrde krænkelse.', 'Mekanisme vært politimand miljø evne korn. Klatre selvom tættere elementære informere.\nMisbrug vital titel viden.']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.texts(nb_texts=5, max_nb_chars=50)
...
['Holde mirakel smerte religion langt søg.', 'Nederlag fabrikant sang fed.', 'Nærme erhverve lænke dræbe.', 'Tilladelse celle de godt højttaler tegne.', 'Vidner udvej funktion facilitet.']
['Køn produktion skib. Sektor plukke familie kraft.', 'Grad pie pensionering også mad følge grave.', 'Altid sandsynligvis uddanne TV.', 'Gård enhed adgang at. Fuld hemmelighed fuldt.', 'Tre struktur røg cykle afvige.']
['Styrke tanke snart fylde udenlandsk.', 'Minde de levested mig sol kan ventilator.', 'Universel investere skade oversætte ekspert.', 'Fantasi massiv fjerde. Myndighed løb massiv.', 'Deltage landdistrikter sektor strategi.']
['Forklare bebrejde forberedelse stå talt.', 'Sommer station følelse ansvarlig.', 'Bevare via ønske psykolog stof faktisk træt.', 'Fuldt bjørn direktør bred skulle observation.', 'Glemme næste repræsentant.']
['Formue villig lugt rig artikel signal især.', 'Spise videnskab desperat cykle. Aften er vej.', 'Nød tillid løb mejse. Stolt egen snart.', 'Permanent sager pulver markedsføring strategisk.', 'Kunde kontrast de vise gnide gnide.']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.texts(nb_texts=5, max_nb_chars=50, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['Jkl def def ghi def jkl. Jkl def jkl abc abc.', 'Jkl def ghi jkl ghi def abc def.', 'Ghi def jkl ghi. Ghi jkl def.', 'Def abc def ghi jkl abc ghi. Ghi jkl ghi jkl.', 'Ghi ghi def. Ghi abc abc abc. Jkl jkl ghi def.']
['Def ghi ghi jkl def def abc.', 'Abc abc ghi abc. Ghi jkl ghi abc abc abc jkl.', 'Abc jkl ghi. Abc jkl jkl abc def abc def.', 'Abc jkl abc def ghi jkl jkl abc.', 'Abc jkl ghi abc ghi. Jkl jkl ghi def ghi abc ghi.']
['Ghi ghi jkl jkl abc. Def def ghi abc abc.', 'Def ghi def. Abc abc ghi.', 'Abc jkl jkl def ghi jkl jkl. Jkl def ghi def.', 'Abc ghi jkl def jkl. Def jkl ghi abc.', 'Def abc abc ghi. Def def ghi jkl jkl jkl ghi.']
['Abc def def. Ghi def ghi abc abc jkl.', 'Def jkl ghi. Def def def abc jkl.', 'Ghi jkl jkl ghi def jkl. Abc abc ghi abc.', 'Jkl ghi abc abc abc jkl ghi. Def def abc jkl.', 'Def def ghi jkl. Ghi abc def def jkl.']
['Jkl def jkl def def def. Ghi jkl abc ghi ghi.', 'Def ghi def jkl ghi jkl abc abc.', 'Jkl ghi jkl ghi ghi ghi jkl.', 'Ghi abc jkl abc jkl ghi. Ghi def abc jkl jkl.', 'Def jkl abc abc def. Jkl ghi abc ghi jkl def abc.']

word(part_of_speech: str | None = None, ext_word_list: Sequence[str] | None = None) → str¶

Generate a word.

This method uses words() under the hood with the nb argument set to 1 to generate the result.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.word()
...
'overvinde'
'øjeblik'
'mord'
'vagt'
'klinge'

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.word(ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
'jkl'
'jkl'
'abc'
'ghi'
'jkl'

words(nb: int = 3, ext_word_list: List[str] | None = None, part_of_speech: str | None = None, unique: bool = False) → List[str]¶

Generate a tuple of words.

The nb argument controls the number of words in the resulting list, and if ext_word_list is provided, words from that list will be used instead of those from the locale provider’s built-in word list.

if word_list is not provided, the method will use a default value of None, which will result in the method calling the get_words_list method to get the word list. If word_list is provided, the method will use the provided list.

If unique is True, this method will return a list containing unique words. Under the hood, random_sample() will be used for sampling without replacement. If unique is False, random_choices() is used instead, and the list returned may contain duplicates.

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.words()
...
['imod', 'holde', 'mirakel']
['smerte', 'religion', 'langt']
['søg', 'disse', 'skib']
['sommetider', 'forudsige', 'butik']
['pæn', 'nederlag', 'fabrikant']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.words(nb=5)
...
['imod', 'holde', 'mirakel', 'smerte', 'religion']
['langt', 'søg', 'disse', 'skib', 'sommetider']
['forudsige', 'butik', 'pæn', 'nederlag', 'fabrikant']
['sang', 'fed', 'opførsel', 'baggrund', 'via']
['mål', 'reagere', 'hvordan', 'kvarter', 'sværge']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.words(nb=5, ext_word_list=['abc', 'def', 'ghi', 'jkl'])
...
['jkl', 'jkl', 'def', 'def', 'ghi']
['def', 'jkl', 'def', 'def', 'ghi']
['jkl', 'ghi', 'def', 'jkl', 'ghi']
['def', 'jkl', 'jkl', 'jkl', 'jkl']
['def', 'ghi', 'jkl', 'ghi', 'def']

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.words(nb=4, ext_word_list=['abc', 'def', 'ghi', 'jkl'], unique=True)
...
['jkl', 'def', 'abc', 'ghi']
['jkl', 'def', 'ghi', 'abc']
['ghi', 'jkl', 'abc', 'def']
['ghi', 'abc', 'jkl', 'def']
['def', 'jkl', 'abc', 'ghi']

`faker.providers.person`¶

class faker.providers.person.da_DK.Provider(generator: Any)¶

Bases: Provider

first_name() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name()
...
'Randi'
'Silas'
'Malou'
'Sofie'
'Tobias'

first_name_female() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_female()
...
'Stine'
'Jacqueline'
'Ronja'
'Tina'
'Jonna'

first_name_male() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_male()
...
'Tom'
'Joakim'
'Rune'
'Victor'
'Julius'

first_name_nonbinary() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_nonbinary()
...
'Randi'
'Silas'
'Malou'
'Sofie'
'Tobias'

language_name() → str¶

Generate a random i18n language name (e.g. English).

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.language_name()
...
'Luba-Katanga'
'Malay'
'Aymara'
'Interlingue'
'Quechua'

last_name() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name()
...
'Jessen'
'Skov'
'Christensen'
'Clausen'
'Krogh'

last_name_female() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_female()
...
'Jessen'
'Skov'
'Christensen'
'Clausen'
'Krogh'

last_name_male() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_male()
...
'Jessen'
'Skov'
'Christensen'
'Clausen'
'Krogh'

last_name_nonbinary() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_nonbinary()
...
'Jessen'
'Skov'
'Christensen'
'Clausen'
'Krogh'

name() → str¶

Example:: ‘John Doe’
Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name()
...
'Univ.Prof. Ronja Skov'
'George Krogh'
'Jean Jeppesen'
'Inge Mathiasen'
'Laurits Johansen'

name_female() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_female()
...
'Univ.Prof. Ronja Skov'
'George Krogh'
'Jean Jeppesen'
'Inge Mathiasen'
'Laurits Johansen'

name_male() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_male()
...
'Univ.Prof. Ronja Skov'
'George Krogh'
'Jean Jeppesen'
'Inge Mathiasen'
'Laurits Johansen'

name_nonbinary() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_nonbinary()
...
'Univ.Prof. Ronja Skov'
'George Krogh'
'Jean Jeppesen'
'Inge Mathiasen'
'Laurits Johansen'

prefix() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix()
...
'Univ.Prof.'
'Prof.'
'Univ.Prof.'
'Univ.Prof.'
'Dr.'

prefix_female() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_female()
...
'Univ.Prof.'
'Univ.Prof.'
'Fru'
'Prof.'
'Univ.Prof.'

prefix_male() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_male()
...
'Univ.Prof.'
'Univ.Prof.'
'Hr'
'Prof.'
'Univ.Prof.'

prefix_nonbinary() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_nonbinary()
...
'Univ.Prof.'
'Prof.'
'Univ.Prof.'
'Univ.Prof.'
'Dr.'

suffix() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.suffix()
...
''
''
''
''
''

suffix_female() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.suffix_female()
...
''
''
''
''
''

suffix_male() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.suffix_male()
...
''
''
''
''
''

suffix_nonbinary() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.suffix_nonbinary()
...
''
''
''
''
''

`faker.providers.phone_number`¶

class faker.providers.phone_number.da_DK.Provider(generator: Any)¶

Bases: Provider

country_calling_code() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.country_calling_code()
...
'+687'
'+595'
'+880'
'+964'
'+41'

msisdn() → str¶

https://en.wikipedia.org/wiki/MSISDN

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.msisdn()
...
'6048764759382'
'2194892411578'
'5659387784080'
'6097535139332'
'1158714841858'

phone_number() → str¶

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.phone_number()
...
'60487647'
'+45 93 82 42 19'
'+45 89 24 11 57'
'1565 9387'
'84080160'

Locale da_DK¶

`faker.providers.address`¶

`faker.providers.automotive`¶

`faker.providers.bank`¶

`faker.providers.color`¶

`faker.providers.company`¶

`faker.providers.currency`¶

`faker.providers.date_time`¶

`faker.providers.job`¶

`faker.providers.lorem`¶

`faker.providers.person`¶

`faker.providers.phone_number`¶

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Locale da_DK¶

faker.providers.address¶

faker.providers.automotive¶

faker.providers.bank¶

faker.providers.color¶

faker.providers.company¶

faker.providers.currency¶

faker.providers.date_time¶

faker.providers.job¶

faker.providers.lorem¶

faker.providers.person¶

faker.providers.phone_number¶

`faker.providers.address`¶

`faker.providers.automotive`¶

`faker.providers.bank`¶

`faker.providers.color`¶

`faker.providers.company`¶

`faker.providers.currency`¶

`faker.providers.date_time`¶

`faker.providers.job`¶

`faker.providers.lorem`¶

`faker.providers.person`¶

`faker.providers.phone_number`¶