Locale tw_GH

faker.providers.person

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

Bases: faker.providers.person.Provider

first_name() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name()
...
'Karen'
'Mary'
'Colins'
'Akos'
'Wendy'

first_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_female()
...
'Nicola'
'Rebecca'
'Alice'
'Joyce'
'Tracy'

first_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_male()
...
'Ronald'
'Akwasi'
'Nigel'
'Simon'
'James'

first_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.first_name_nonbinary()
...
'Karen'
'Mary'
'Colins'
'Akos'
'Wendy'

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()
...
'Boaten'
'Frimpomaa'
'Amo'
'Agyare'
'Owusuwaa'

last_name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_female()
...
'Fosua'
'Koomson'
'Adwubi'
'Ata'
'Nyame'

last_name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_male()
...
'Twumasi'
'Boadi'
'Otiwa'
'Yeboah'
'Boaten'

last_name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.last_name_nonbinary()
...
'Boaten'
'Frimpomaa'
'Amo'
'Agyare'
'Owusuwaa'

name() → str

Example:‘John Doe’ Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name()
...
'Awura Rebecca Adwubi'
'Vincent Fosu-Duah'
'Lisa Nkansah'
'Irene Nyaakoaa'
'Fiifi Akyeampong'

name_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_female()
...
'Awura Rebecca Adwubi'
'Vincent Fosu-Duah'
'Lisa Nkansah'
'Irene Nyaakoaa'
'Fiifi Akyeampong'

name_male() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_male()
...
'Awura Rebecca Adwubi'
'Vincent Fosu-Duah'
'Lisa Nkansah'
'Irene Nyaakoaa'
'Fiifi Akyeampong'

name_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.name_nonbinary()
...
'Awura Rebecca Adwubi'
'Vincent Fosu-Duah'
'Lisa Nkansah'
'Irene Nyaakoaa'
'Fiifi Akyeampong'

prefix() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix()
...
'Awura'
'Agya'
'Awura'
'Sista'
'Dr.'

prefix_female() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_female()
...
'Awura'
'Awura'
'Mrs.'
'Mama'
'Osofo Maame'

prefix_male() → str

Examples:

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

prefix_nonbinary() → str

Examples:

>>> Faker.seed(0)
>>> for _ in range(5):
...     fake.prefix_nonbinary()
...
'Awura'
'Agya'
'Awura'
'Sista'
'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.tw_GH.Provider(generator: Any)

Bases: faker.providers.phone_number.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()
...
'0556048764'
'0205938242'
'+233249489241'
'+233555781565'
'0283877840'