# Locale nl_BE

## `faker.providers.address`

class faker.providers.address.nl_BE.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()
        ...
        'Kimsingel 6\n4759 Saint-Médard'
        'Katjasteeg 892\n8115\nTailles'
        'Marcstraat 87\n9840\nAnthée'
        'Claralei 51\n3933\nSnellegem'
        'Wendysingel 1\n9841 Lisogne'

  administrative_unit() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.administrative_unit()
        ...
        'Oost-Vlaanderen'
        'Oost-Vlaanderen'
        'Antwerpen'
        'Luxemburg'
        'Waals-Brabant'

  building_number() → str
    Example:

      ‘791’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.building_number()
        ...
        '6'
        '4'
        '76'
        '759'
        '82'

  city() → str
    Example:

      ‘Sashabury’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.city()
        ...
        'Mons-lez-Liège'
        'Obourg'
        'Beauvoorde'
        'Housse'
        'Sart-Eustache'

  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()
        ...
        'Tanzania'
        'Iran'
        'Sao Tomé en Principe'
        'Turks- en Caicoseilanden'
        'Kaaimaneilanden'

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

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

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.country_code(representation='alpha-2')
        ...
        'MV'
        'PS'
        'NL'
        'BB'
        'IL'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.country_code(representation='alpha-3')
        ...
        'MDV'
        'PSE'
        'NLD'
        'BRB'
        'ISR'

  current_country() → str
    Examples:

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

  current_country_code() → str
    Examples:

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

  postcode() → str
    Example:

      86039-9874

    Examples:

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

  province() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.province()
        ...
        'Oost-Vlaanderen'
        'Oost-Vlaanderen'
        'Antwerpen'
        'Luxemburg'
        'Waals-Brabant'

  street_address() → str
    Example:

      ‘791 Crist Parks’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.street_address()
        ...
        'Bennysingel 6'
        'Nickhof 24'
        'Daphnelaan 92'
        'Jessiestraat 781'
        'Marcstraat 87'

  street_name() → str
    Example:

      ‘Crist Parks’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.street_name()
        ...
        'Katrienpad'
        'Kimsingel'
        'Raoullaan'
        'Nickhof'
        'Leviboulevard'

  street_suffix() → str
    Example:

      ‘Avenue’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.street_suffix()
        ...
        'pad'
        'pad'
        'baan'
        'laan'
        'singel'

## `faker.providers.automotive`

class faker.providers.automotive.nl_BE.Provider(generator: Any)

  Bases: `Provider`

  Implement automotive provider for nl_BE locale.

  https://nl.wikipedia.org/wiki/Belgisch_kenteken

  license_plate() → str

    Generate a license plate.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.license_plate()
        ...
        '2-YNB-487'
        '2-ZJP-593'
        '194-JEY'
        '157-JDX'
        'LNK-938'

  vin() → str

    Generate vin number.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.vin()
        ...
        'RT3GZYSK4Z9J97593'
        '7G0K75MX5LDXV8156'
        'G416S1YM2EF0V3513'
        '66LZY7KJ7DJV61858'
        'RLFJBCB3669039471'

## `faker.providers.bank`

class faker.providers.bank.nl_BE.Provider(generator: Any)

  Bases: `Provider`

  Implement bank provider for nl_BE locale.

  Information about the Belgian banks can be found on the website of the National Bank of Belgium: https://www.nbb.be/nl/betalingen-en-effecten/betalingsstandaarden/bankidentificatiecodes

  aba() → str

    Generate an ABA routing transit number.

    Examples:

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

  bank() → str

    Generate a bank name.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.bank()
        ...
        'Deutsche Bank AG'
        'Deutsche Bank AG'
        'Argenta Spaarbank'
        'Bpost Bank'
        'KBC Bank'

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

  bban() → str

    Generate a valid BBAN.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.bban()
        ...
        '660487647505'
        '938242194845'
        '924115781519'
        '659387784006'
        '801609753575'

  iban() → str

    Generate a valid IBAN.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.iban()
        ...
        'BE96660487647505'
        'BE44938242194845'
        'BE39924115781519'
        'BE85659387784006'
        'BE05801609753575'

  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()
        ...
        'YNBIBE65ZT4'
        'SGQEBESIGQ8'
        'JDXCBEV4'
        'LNKTBEN9'
        'OQIBBE9AFZA'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=8)
        ...
        'MYNBBEQ6'
        'PMZJBE4W'
        'SGQEBESI'
        'YDTZBEQ8'
        'WZTEBETG'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=8, use_dataset=True)
        ...
        'GKCCBEBX'
        'GKCCBEBE'
        'DEUTBE2X'
        'KREDBE3X'
        'DEUTBE75'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=11)
        ...
        'MYNBBEQ65ZT'
        'PLSGBE6ISIG'
        'TZIRBEJTGEV'
        'PRDLBE1UN94'
        'OQIBBE9AFZA'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=11, primary=True)
        ...
        'MYNBBEQ6XXX'
        'PMZJBE4WXXX'
        'SGQEBESIXXX'
        'YDTZBEQ8XXX'
        'WZTEBETGXXX'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=11, use_dataset=True)
        ...
        'GKCCBEBXMDC'
        'ARSPBE91VOD'
        'KREDBE3XIDJ'
        'KREDBE23XXX'
        'BPOTBE2XCIC'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift(length=11, primary=True, use_dataset=True)
        ...
        'GKCCBEBXXXX'
        'GKCCBEBEXXX'
        'DEUTBE2XXXX'
        'KREDBE3XXXX'
        'DEUTBE75XXX'

  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()
        ...
        'MYNBBEQ65ZT'
        'PLSGBE6ISIG'
        'TZIRBEJTGEV'
        'PRDLBE1UN94'
        'OQIBBE9AFZA'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift11(use_dataset=True)
        ...
        'GKCCBEBXMDC'
        'ARSPBE91VOD'
        'KREDBE3XIDJ'
        'KREDBE23XXX'
        'BPOTBE2XCIC'

  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()
        ...
        'MYNBBEQ6'
        'PMZJBE4W'
        'SGQEBESI'
        'YDTZBEQ8'
        'WZTEBETG'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.swift8(use_dataset=True)
        ...
        'GKCCBEBX'
        'GKCCBEBE'
        'DEUTBE2X'
        'KREDBE3X'
        'DEUTBE75'

## `faker.providers.company`

class faker.providers.company.nl_BE.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()
        ...
        'Van Damme-Huysmans CV'
        'Lemmens, Verlinden en Van den Eynde VOF'
        'Neven-Verheyen CommV'
        'Deconinck NV'
        'Van Parys, Wouters en Martens CommV'

  company_suffix() → str
    Example:

      ‘Ltd’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.company_suffix()
        ...
        'VOF'
        'VOF'
        'NV'
        'CV'
        'CommV'

## `faker.providers.lorem`

class faker.providers.lorem.nl_BE.Provider(generator: Any)

  Bases: `Provider`

  Implement lorem provider for `nl_BE` locale.

  Source: https://nl.wiktionary.org/wiki/WikiWoordenboek:Lijst_met_1000_basiswoorden

  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)
        ...
        'Bad zelfde meneer want verdienen zetten. Op vroeger modern grof stuk pistool. Zoon net sinds pad deel. Springen vragen samen mand. Jongen hoed prins even.'
        'Liefde naar belofte want wachten bodem verhoging. Aanbod midden vies gemakkelijk hoog vijver effect ons. Uitnodigen dansen noemen bloed zulke. Zwak met helder half bus huis wat. Zeil pan openlijk liggen overeenkomen. Hoek gemak echt vechten antwoorden zoeken.'
        'Beslissen rots comfortabel delen baan bijna schrijven. Samen vergeven nat naar geit fles roze. Oor list regen zwaar wakker trein. Hoofd brood openlijk hut.'
        'Afmaken graf sinds kijken dragen. Vandaag boos deel schreeuw bed ontwikkelen. Pagina bevatten bus eenzaam verdrietig bruin bloed. Avond algemeen zeer een.'
        'Feit u wie alleen laten bord gewoon. Betalen helder les bellen machine. Boos zorg en kaas stad vergissen want draaien.'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.paragraph(nb_sentences=5, variable_nb_sentences=False)
        ...
        'Suiker lamp gewicht mond koud thuis. Zetten kaas voorzichtig fris dag. Stuk pistool geschikt vrouw. Vriend het springen vragen samen mand boos lepel. Prins even object liefde naar belofte want wachten.'
        'Soep koorts veilig resultaat. Peper verder hun. Signaal belofte wanneer gat uitnodigen dansen. Liniaal bijna hoewel moeten werelddeel breed nummer. Noot van noch zeil.'
        'Noot haar bloed tuin hoek gemak echt vechten. Per rechts markt. Rots comfortabel delen baan. Vragen water noch koffie. Grens vakantie verrassen vos opnemen wolf oor.'
        'Middel prinses schudden zoet kaart hoofd brood. Poes verleden gemakkelijk stad bruikbaar gaan trekken huis. Boos deel schreeuw bed. Positie wie pagina bevatten bus eenzaam verdrietig. Koffie keus zoals avond.'
        'Eiland ziekenhuis snijden. Feit u wie alleen laten bord gewoon. Betalen helder les bellen machine. Boos zorg en kaas stad vergissen want draaien. Zes beker rood verleden ijs.'

        >>> 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)
        ...
        ['Bad zelfde meneer want verdienen zetten. Op vroeger modern grof stuk pistool. Zoon net sinds pad deel.', 'Vragen samen mand boos. Hoed prins even object liefde naar.', 'Wachten bodem verhoging slim tijd plastic peper. Gemakkelijk hoog vijver effect ons gelijk.', 'Liniaal bijna hoewel moeten werelddeel breed nummer. Noot van noch zeil.', 'Openlijk liggen overeenkomen klok oog halen eerste. Antwoorden zoeken gezicht beslissen. Vlieg water verkeerd vragen. Samen vergeven nat naar geit fles roze.']
        ['Grens middel prinses schudden zoet kaart hoofd brood. Poes verleden gemakkelijk stad bruikbaar gaan trekken huis. Boos deel schreeuw bed.', 'Pagina bevatten bus eenzaam verdrietig bruin bloed. Avond algemeen zeer een. Meel sport bellen roze.', 'Plaatje vergelijking best betalen helder les. Model baby boos zorg. Gezicht vriezen mama vriend ontbijt.', 'Toen dit dom negen. Overeenkomen liefde drogen man.', 'Vlag wanneer punt knippen rechtvaardig dienen schetsen. Steun hut bed groep geluid woud jong. Ring oranje voorzichtig verspreiden computer.']
        ['Stop verder bijna over schreeuwen doen. Praten klasse vlees ontsnappen laat.', 'Ladder reizen bedekken lijk gewoon ding nee. Vroeger pan aan baan hoog vergeven been. Eenzaam zwemmen populair bijzonder spel zonnig.', 'Hoed film snelheid aanraken veel neer. Eeuw pas elk helft. Boos verspreiden koning bijten.', 'Tweede brood geven rapport vanmorgen probleem brood. Groen afspraak bad rubber.', 'Winter wij vrouw bang storm seconde. Sluiten vriend prins kijken nieuw falen openlijk. Daarom graf idee.']
        ['Ieder plaatje bal dood. Hal kom normaal hamer medicijn geloof bedreven dun. Spreken helft vergelijking heel brandstof om meerdere.', 'Bus brug min avondeten hut schaduw. Wapen plat kist zijn. Berg binnen storm bellen.', 'Koken naald links mes.', 'Langs kennis zorg gezicht terug. Effect brood vechten verschrikkelijk ander natuur. Bruiloft koningin falen bang wissen. Plank bot luisteren kant veranderen.', 'Zoet deksel kraam roze vliegtuig mijn wanneer honderd. Zwembad postzegel vlag noemen wereld achter sinds.']
        ['Auto deksel geven tien verkeerd oost. Beroemd binnen vijand baby geboorte bad afhangen. Houden doen deksel rechts zeven modern vreemde.', 'Ontwikkelen rots uitzoeken. Zou stoffig vrij extreem niet overvallen ver meest. Partner geen vet al vol sterk.', 'Ontdekken huis midden gif ver tekenen klok. Belofte prins cadeau haar verdienen begrip.', 'Lachen mevrouw verzameling snelheid ring deze zonnig.', 'Peper klopt bedreiging. Terugkomst al overvallen computer honger schudden punt. Klimmen tennis meubel voelen pen.']

        >>> 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)
        ...
        'Suiker lamp gewicht mond koud thuis help markt op vroeger.'
        'Dag dag boek tweede zoon net sinds pad deel boon bevatten vers.'
        'Mand boos lepel pen waarom zes me vier gezicht uitzoeken.'
        'Wachten bodem verhoging slim tijd plastic peper verder hun staal signaal belofte wanneer.'
        'Gelijk zetten uitnodigen liniaal bijna hoewel moeten werelddeel.'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.sentence(nb_words=10, variable_nb_words=False)
        ...
        'Verlaten suiker lamp gewicht mond koud thuis help markt op.'
        'Vroeger modern grof stuk pistool geschikt vrouw zoet vak vriend.'
        'Het springen vragen samen mand boos lepel pen waarom zes.'
        'Me vier gezicht uitzoeken normaal afgelopen soep koorts veilig resultaat.'
        'Aanbod midden vies gemakkelijk hoog vijver effect ons gelijk zetten.'

        >>> 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()
        ...
        ['Suiker lamp gewicht mond koud thuis.', 'Zetten kaas voorzichtig fris dag.', 'Stuk pistool geschikt vrouw.']
        ['Vriend het springen vragen samen mand boos lepel.', 'Prins even object liefde naar belofte want wachten.', 'Soep koorts veilig resultaat.']
        ['Peper verder hun.', 'Signaal belofte wanneer gat uitnodigen dansen.', 'Liniaal bijna hoewel moeten werelddeel breed nummer.']
        ['Noot van noch zeil.', 'Noot haar bloed tuin hoek gemak echt vechten.', 'Per rechts markt.']
        ['Rots comfortabel delen baan.', 'Vragen water noch koffie.', 'Grens vakantie verrassen vos opnemen wolf oor.']

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.sentences(nb=5)
        ...
        ['Suiker lamp gewicht mond koud thuis.', 'Zetten kaas voorzichtig fris dag.', 'Stuk pistool geschikt vrouw.', 'Vriend het springen vragen samen mand boos lepel.', 'Prins even object liefde naar belofte want wachten.']
        ['Soep koorts veilig resultaat.', 'Peper verder hun.', 'Signaal belofte wanneer gat uitnodigen dansen.', 'Liniaal bijna hoewel moeten werelddeel breed nummer.', 'Noot van noch zeil.']
        ['Noot haar bloed tuin hoek gemak echt vechten.', 'Per rechts markt.', 'Rots comfortabel delen baan.', 'Vragen water noch koffie.', 'Grens vakantie verrassen vos opnemen wolf oor.']
        ['Middel prinses schudden zoet kaart hoofd brood.', 'Poes verleden gemakkelijk stad bruikbaar gaan trekken huis.', 'Boos deel schreeuw bed.', 'Positie wie pagina bevatten bus eenzaam verdrietig.', 'Koffie keus zoals avond.']
        ['Eiland ziekenhuis snijden.', 'Feit u wie alleen laten bord gewoon.', 'Betalen helder les bellen machine.', 'Boos zorg en kaas stad vergissen want draaien.', 'Zes beker rood verleden ijs.']

        >>> 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)
        ...
        'Vet kom tennis vuur.'
        'Bal glas zorg nacht.'
        'Laat wijs uitleggen.'
        'Het zout mes kat.'
        'Waarom welkom.'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.text(max_nb_chars=80)
        ...
        'Suiker lamp gewicht mond koud thuis. Zetten kaas voorzichtig fris dag.'
        'Vriend het springen vragen samen mand boos lepel.'
        'Soep koorts veilig resultaat. Peper verder hun.'
        'Liniaal bijna hoewel moeten werelddeel breed nummer. Noot van noch zeil.'
        'Per rechts markt. Rots comfortabel delen baan. Vragen water noch koffie.'

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.text(max_nb_chars=160)
        ...
        'Bad zelfde meneer want verdienen zetten. Op vroeger modern grof stuk pistool. Zoon net sinds pad deel.'
        'Wachten bodem verhoging slim tijd plastic peper. Gemakkelijk hoog vijver effect ons gelijk.'
        'Openlijk liggen overeenkomen klok oog halen eerste. Antwoorden zoeken gezicht beslissen. Vlieg water verkeerd vragen. Samen vergeven nat naar geit fles roze.'
        'Pagina bevatten bus eenzaam verdrietig bruin bloed. Avond algemeen zeer een. Meel sport bellen roze.'
        'Toen dit dom negen. Overeenkomen liefde drogen man.'

        >>> 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)
        ...
        ['Bad zelfde meneer want verdienen zetten. Op vroeger modern grof stuk pistool. Zoon net sinds pad deel.\nVragen samen mand boos. Hoed prins even object liefde naar.', 'Liniaal bijna hoewel moeten werelddeel breed nummer. Noot van noch zeil.', 'Grens middel prinses schudden zoet kaart hoofd brood. Poes verleden gemakkelijk stad bruikbaar gaan trekken huis. Boos deel schreeuw bed.', 'Plaatje vergelijking best betalen helder les. Model baby boos zorg. Gezicht vriezen mama vriend ontbijt.\nToen dit dom negen. Overeenkomen liefde drogen man.', 'Stop verder bijna over schreeuwen doen. Praten klasse vlees ontsnappen laat.']
        ['Hoed film snelheid aanraken veel neer. Eeuw pas elk helft. Boos verspreiden koning bijten.\nTweede brood geven rapport vanmorgen probleem brood. Groen afspraak bad rubber.', 'Ieder plaatje bal dood. Hal kom normaal hamer medicijn geloof bedreven dun. Spreken helft vergelijking heel brandstof om meerdere.', 'Koken naald links mes.\nLangs kennis zorg gezicht terug. Effect brood vechten verschrikkelijk ander natuur. Bruiloft koningin falen bang wissen. Plank bot luisteren kant veranderen.', 'Auto deksel geven tien verkeerd oost. Beroemd binnen vijand baby geboorte bad afhangen. Houden doen deksel rechts zeven modern vreemde.', 'Ontdekken huis midden gif ver tekenen klok. Belofte prins cadeau haar verdienen begrip.\nLachen mevrouw verzameling snelheid ring deze zonnig.']
        ['Poort idee bus ruimte plafond toen cadeau vuur. Wakker vinger ruiken vak naald. Baan kok kiezen eeuw kaars.', 'Boord telefoon station angst. Leiden lachen miljoen vet hoofd geur jong. Kamer anders ja achter.\nBest vork falen even ring wij. Stom hamer scherp werelddeel.', 'Postzegel een zuid borstelen oorlog dik vraag. Uitvinden hoe gemak studie.\nLaken bedekken computer al bibliotheek bevatten. Heel lach weer orde hebben jouw.', 'Papier dienen sex welke één land drogen. Iemand nacht jullie politie blad stuk hand.', 'Voorkomen sleutel liggen stoffig jongen vinden rijzen. Overal auto tram hemel iedereen. Vertrouwen voorkomen tamelijk bescherm verwachten grond controle.']
        ['Heet stof beetje plaats alsjeblieft man. Verliezen zitten schaar.\nAarde bal plaatje zwemmen vis schrijven. Dak ontvangen effect lepel snel.', 'Appel populair vinden kap stilte rook.\nHaten blad vijand straffen teken voet kunnen begin. Repareren punt noot station leger los gevaarlijk.', 'Gevangenis naar eeuw bijna vijf in. Gespannen springen helder munt klok. Ijzer sluiten basis west beter maag speciaal.\nZitten maag bruiloft bijten boon tas.', 'Slot terug moorden maaltijd positie. Gedragen bruiloft thuis boon stap. Fris voeden zwak aarde niet.', 'Kat positie vakantie vlieg dier droog. Cool extreem wachten miljoen. Geit computer geen klok pas.']
        ['Papa signaal vechten tijd. Wind familie hoe stom gereedschap verzamelen.\nIk donker afmaken ontwikkelen beker. Deze algemeen plattegrond als basis geboorte rapport beroemd.', 'Voorkomen netjes uitvinden zoals simpel taart.\nKrijgen koffer aanval daarom. Verhoging schrijven bij geliefde verder droog winnen. Stil vergissen oma snelheid.', 'Tekenen ontdekken gif. Lot soms kosten. Beest grappig zus gevaar rubber sex welkom.\nMunt klopt vergelijken geschikt brood zoeken uitvinden. Open sok ruiken jongen wakker.', 'Ontsnappen licht iets achter.\nStom eenheid normaal langs wolf. Negen beneden prijs oor. Poort nog klok lepel heuvel af terugkomst.\nNieuw ochtend zou eerste thee. Verlaten straat dier reiken.', 'Ontwikkelen geld smaak verzameling. Zand door water weg. Wijs geur voelen telefoon passeren blijven.\nActief geschikt tamelijk klopt tellen plastic koers.']

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.texts(nb_texts=5, max_nb_chars=50)
        ...
        ['Suiker lamp gewicht mond koud thuis.', 'Stuk pistool geschikt vrouw.', 'Soep koorts veilig resultaat. Peper verder hun.', 'Noot van noch zeil.', 'Per rechts markt. Rots comfortabel delen baan.']
        ['Grens vakantie verrassen vos opnemen wolf oor.', 'Boos deel schreeuw bed.', 'Koffie keus zoals avond.', 'Feit u wie alleen laten bord gewoon.', 'Boos zorg en kaas stad vergissen want draaien.']
        ['Bruikbaar wassen repareren af ruiken.', 'Steun hut bed groep geluid woud jong.', 'Knippen laat raam aanbod ei.', 'Kost seconde ladder. Doorzichtig beneden seconde.', 'Been veel zijn laatst normaal zeil zitten.']
        ['Afgelopen studie zoals rond per.', 'Markeren wat plattegrond algemeen.', 'Groen afspraak bad rubber.', 'Sluiten vriend prins kijken nieuw falen openlijk.', 'Snijden ieder plaatje bal dood zoeken.']
        ['Herfst vertellen spreken.', 'Idee tuin vallen bus brug min avondeten.', 'Berg binnen storm bellen. Boon of hal.', 'Leiden kaas beneden verzameling.', 'Min geven prins zwak.']

        >>> 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()
        ...
        'vet'
        'kom'
        'tennis'
        'vuur'
        'leger'

        >>> 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()
        ...
        ['verlaten', 'suiker', 'lamp']
        ['gewicht', 'mond', 'koud']
        ['thuis', 'help', 'markt']
        ['op', 'vroeger', 'modern']
        ['grof', 'stuk', 'pistool']

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.words(nb=5)
        ...
        ['verlaten', 'suiker', 'lamp', 'gewicht', 'mond']
        ['koud', 'thuis', 'help', 'markt', 'op']
        ['vroeger', 'modern', 'grof', 'stuk', 'pistool']
        ['geschikt', 'vrouw', 'zoet', 'vak', 'vriend']
        ['het', 'springen', 'vragen', 'samen', 'mand']

        >>> 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.nl_BE.Provider(generator: Any)

  Bases: `Provider`

  Provider of Person data (male and female first and last names) for locale ‘nl_BE’ (Belgium Dutch, Flemish).

  first_name() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.first_name()
        ...
        'Marie'
        'Katrien'
        'Roger'
        'Kim'
        'Wouter'

  first_name_female() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.first_name_female()
        ...
        'Renée'
        'Monique'
        'Jeanine'
        'Els'
        'Kim'

  first_name_male() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.first_name_male()
        ...
        'Samuel'
        'Philippe'
        'Johan'
        'Freddy'
        'Kris'

  first_name_nonbinary() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.first_name_nonbinary()
        ...
        'Marie'
        'Katrien'
        'Roger'
        'Kim'
        'Wouter'

  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()
        ...
        'Vandenbroucke'
        'Van Damme'
        'Huysmans'
        'De Wilde'
        'Maes'

  last_name_female() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.last_name_female()
        ...
        'Vandenbroucke'
        'Van Damme'
        'Huysmans'
        'De Wilde'
        'Maes'

  last_name_male() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.last_name_male()
        ...
        'Vandenbroucke'
        'Van Damme'
        'Huysmans'
        'De Wilde'
        'Maes'

  last_name_nonbinary() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.last_name_nonbinary()
        ...
        'Vandenbroucke'
        'Van Damme'
        'Huysmans'
        'De Wilde'
        'Maes'

  name() → str
    Example:

      ‘John Doe’

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.name()
        ...
        'Monique Huysmans'
        'Kris Heylen'
        'Fien Lammens'
        'Simonne Luyckx'
        'Philip Peeters'

  name_female() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.name_female()
        ...
        'Monique Huysmans'
        'Kim Heylen'
        'Fien Lammens'
        'Simonne Luyckx'
        'Monique Peeters'

  name_male() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.name_male()
        ...
        'Philippe Huysmans'
        'Kris Heylen'
        'Guido Lammens'
        'Tijl Luyckx'
        'Philip Peeters'

  name_nonbinary() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.name_nonbinary()
        ...
        'Monique Huysmans'
        'Kris Heylen'
        'Fien Lammens'
        'Simonne Luyckx'
        'Philip Peeters'

  prefix() → str
    Examples:

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

  prefix_female() → str
    Examples:

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

  prefix_male() → str
    Examples:

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

  prefix_nonbinary() → str
    Examples:

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

  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.nl_BE.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()
        ...
        '+32(0)604-876475'
        '(0824) 219489'
        '+32(0)411 578156'
        '+32938-778408'
        '0160 975351'

## `faker.providers.ssn`

class faker.providers.ssn.nl_BE.Provider(generator: Any)

  Bases: `Provider`

  ssn() → str

    Returns a 11 digits Belgian SSN called “rijksregisternummer” as a string

    The first 6 digits represent the birthdate with (in order) year, month and day. The second group of 3 digits is represents a sequence number (order of birth). It is even for women and odd for men. For men the range starts at 1 and ends 997, for women 2 until 998. The third group of 2 digits is a checksum based on the previous 9 digits (modulo 97). Divide those 9 digits by 97, subtract the remainder from 97 and that’s the result. For persons born in or after 2000, the 9 digit number needs to be proceeded by a 2 (add 2000000000) before the division by 97.

    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.ssn()
        ...
        '17041077716'
        '19110304282'
        '84063052491'
        '97031594185'
        '13111731143'

  vat_id() → str
    Examples:

        >>> Faker.seed(0)
        >>> for _ in range(5):
        ...     fake.vat_id()
        ...
        'BE1604876480'
        'BE1593824222'
        'BE0948924175'
        'BE0578156523'
        'BE0877840892'