# Locale la

## `faker.providers.lorem`

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

  Bases: `Provider`

  Implement lorem provider for `la` locale.

  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.

    Sample:

      part_of_speech=”abc”, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

    Sample:

      part_of_speech=”abc”

    Sample:

      ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

    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.

  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.

    Sample:

      nb_sentences=5

    Sample:

      nb_sentences=5, variable_nb_sentences=False

    Sample:

      nb_sentences=5, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

    Sample:

      nb_sentences=5, variable_nb_sentences=False, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

  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.

    Sample:

      nb=5

    Sample:

      nb=5, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

  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.

    Sample:

      nb_words=10

    Sample:

      nb_words=10, variable_nb_words=False

    Sample:

      nb_words=10, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

    Sample:

      nb_words=10, variable_nb_words=True, ext_word_list=[‘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.

    Sample:

    Sample:

      nb=5

    Sample:

      nb=5, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

  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.

    Sample:

      max_nb_chars=20

    Sample:

      max_nb_chars=80

    Sample:

      max_nb_chars=160

    Sample:

      ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

  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.

    Sample:

      nb_texts=5

    Sample:

      nb_texts=5, max_nb_chars=50

    Sample:

      nb_texts=5, max_nb_chars=50, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

  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.

    Sample:

    Sample:

      ext_word_list=[‘abc’, ‘def’, ‘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.

    Sample:

    Sample:

      nb=5

    Sample:

      nb=5, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’]

    Sample:

      nb=4, ext_word_list=[‘abc’, ‘def’, ‘ghi’, ‘jkl’], unique=True