Locale en_KE

faker.providers.person

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

Bases: Provider

Kenyan English person name provider.

This class provides methods to generate authentic Kenyan names with appropriate frequency distributions based on statistical data.

Name formats follow common Kenyan patterns with optional prefixes.

first_name() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name()
...
'Yvonne'
'Sarah'
'Bernard'
'Fredrick'
'Tony'

first_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_female()
...
'Tracy'
'Kwamboka'
'Alice'
'Margaret'
'Maureen'

first_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_male()
...
'Nathan'
'Okoth'
'Julius'
'Michael'
'Thomas'

first_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_nonbinary()
...
'Yvonne'
'Sarah'
'Bernard'
'Fredrick'
'Tony'

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()
...
'Muthini'
'Koskei'
'Gitonga'
'Njuguna'
'Kosgei'

last_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_female()
...
'Muthini'
'Koskei'
'Gitonga'
'Njuguna'
'Kosgei'

last_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_male()
...
'Muthini'
'Koskei'
'Gitonga'
'Njuguna'
'Kosgei'

last_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_nonbinary()
...
'Muthini'
'Koskei'
'Gitonga'
'Njuguna'
'Kosgei'

name() → str

Example:

‘John Doe’

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name()
...
'Pastor Okoth Gitonga'
'Jael Said'
'Hon Kinuthia Musyoka'
'Sheila Barasa'
'Dr Njeri Adhiambo'

name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_female()
...
'Rev Kwamboka Gitonga'
'Jael Said'
'Prof Milkah Musyoka'
'Sheila Barasa'
'Ms Nelly Adhiambo'

name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_male()
...
'Pastor Okoth Gitonga'
'Gordon Said'
'Hon Kinuthia Musyoka'
'Joel Barasa'
'Dr Njeri Adhiambo'

name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_nonbinary()
...
'Pastor Okoth Gitonga'
'Jael Said'
'Hon Kinuthia Musyoka'
'Sheila Barasa'
'Dr Njeri Adhiambo'

prefix() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix()
...
'Rev'
'Hon'
'Rev'
'Pastor'
'Eng'

prefix_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_female()
...
'Rev'
'Rev'
'Mrs'
'Prof'
'Sis'

prefix_male() → str

Examples:

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

prefix_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_nonbinary()
...
'Rev'
'Hon'
'Rev'
'Pastor'
'Eng'

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()
...
''
''
''
''
''