faker.providers.person

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

Bases: faker.providers.BaseProvider

first_name() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name()
...
'Megan'
'Katherine'
'Robert'
'Jonathan'
'William'

first_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_female()
...
'Sarah'
'Norma'
'Jennifer'
'Deanna'
'Kayla'

first_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_male()
...
'Ryan'
'Peter'
'Jason'
'David'
'Jorge'

first_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_nonbinary()
...
'Megan'
'Katherine'
'Robert'
'Jonathan'
'William'

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()
...
'Richard'
'Chang'
'Fisher'
'Green'
'Dixon'

last_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_female()
...
'Richard'
'Chang'
'Fisher'
'Green'
'Dixon'

last_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_male()
...
'Richard'
'Chang'
'Fisher'
'Green'
'Dixon'

last_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_nonbinary()
...
'Richard'
'Chang'
'Fisher'
'Green'
'Dixon'

name() → str

Example:‘John Doe’ Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name()
...
'Norma Fisher'
'Jorge Sullivan'
'Elizabeth Woods'
'Susan Wagner'
'Peter Montgomery'

name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_female()
...
'Norma Fisher'
'Kayla Sullivan'
'Elizabeth Woods'
'Susan Wagner'
'Nicole Montgomery'

name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_male()
...
'Peter Fisher'
'Jorge Sullivan'
'Eric Woods'
'Terry Wagner'
'Peter Montgomery'

name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_nonbinary()
...
'Katherine Fisher'
'William Sullivan'
'Kevin Woods'
'Rebecca Wagner'
'Katelyn Montgomery'

prefix() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix()
...
'Mx.'
'Mx.'
'Mrs.'
'Mr.'
'Mrs.'

prefix_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_female()
...
'Dr.'
'Dr.'
'Mrs.'
'Mrs.'
'Ms.'

prefix_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_male()
...
'Dr.'
'Dr.'
'Mr.'
'Mr.'
'Mr.'

prefix_nonbinary() → str

Examples:

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

suffix() → str

Examples:

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

suffix_female() → str

Examples:

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

suffix_male() → str

Examples:

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

suffix_nonbinary() → str

Examples:

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