Skip to main content

Lorem ipsum generator.

Project description

Lorem ipsum generator.

In publishing and graphic design, lorem ipsum is a placeholder text commonly used to demonstrate the visual form of a document or a typeface without relying on meaningful content.

The lorem module provides a generic access to generating the lorem ipsum text from its very original text:

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Usage of the lorem module is rather simple. Depending on your needs, the lorem module provides generation of words, sentences, and paragraphs.

Get Random Words

The lorem module provides two different ways for getting random words.

  1. word -- generate a list of random words

    word(count=1, func=None, args=[], kwargs={}) -> Iterable[str]
    
  2. get_word -- return random words

    get_word(count=1, sep=' ', func=None, args=[], kwargs={}) -> str
    

Get Random Sentences

The lorem module provides two different ways for getting random sentences.

  1. sentence -- generate a list of random sentences

    sentence(count=1, comma=(0, 2), word_range=(4, 8)) -> Iterable[str]
    
  2. get_sentence -- return random sentences

    get_sentence(count=1, comma=(0, 2), word_range=(4, 8), sep=' ') -> Union[str]
    

Get Random Paragraphs

The lorem module provides two different ways for getting random paragraphs.

  1. paragraph -- generate a list of random paragraphs

    paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10)) -> Iterable[str]
    
  2. get_paragraph -- return random paragraphs

    get_paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10), sep=os.linesep) -> Union[str]
    

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

python_lorem-1.3.0.post2.tar.gz (11.7 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

python_lorem-1.3.0.post2-pp310-none-any.whl (9.1 kB view details)

Uploaded PyPy

python_lorem-1.3.0.post2-pp39-none-any.whl (9.1 kB view details)

Uploaded PyPy

python_lorem-1.3.0.post2-pp38-none-any.whl (9.1 kB view details)

Uploaded PyPy

python_lorem-1.3.0.post2-cp312-none-any.whl (9.1 kB view details)

Uploaded CPython 3.12

python_lorem-1.3.0.post2-cp311-none-any.whl (9.1 kB view details)

Uploaded CPython 3.11

python_lorem-1.3.0.post2-cp310-none-any.whl (9.1 kB view details)

Uploaded CPython 3.10

python_lorem-1.3.0.post2-cp39-none-any.whl (9.1 kB view details)

Uploaded CPython 3.9

python_lorem-1.3.0.post2-cp38-none-any.whl (9.1 kB view details)

Uploaded CPython 3.8

File details

Details for the file python_lorem-1.3.0.post2.tar.gz.

File metadata

  • Download URL: python_lorem-1.3.0.post2.tar.gz
  • Upload date:
  • Size: 11.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/5.1.0 CPython/3.12.4

File hashes

Hashes for python_lorem-1.3.0.post2.tar.gz
Algorithm Hash digest
SHA256 fd094044a8b576a685f25f3ac57cf9a8e63972b09a235a28052bfeef74c08c8b
MD5 24475cde54bd03c02729d605f49506d2
BLAKE2b-256 1d9e3320828be5d209424b5d2f7992fccd318fbff5ce95b53edf1ae0c3013bef

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-pp310-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-pp310-none-any.whl
Algorithm Hash digest
SHA256 3d5624f3d41bf454384947dfd21ed64392ce2c577f8d5a9b401860d14e196490
MD5 19f12ad102d120cbc16bdeead19101ed
BLAKE2b-256 ffdccc601173a1903261d3868b509118e8cdbbb68b5729292dbfc8f63be27451

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-pp39-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-pp39-none-any.whl
Algorithm Hash digest
SHA256 45bb51d597758a807d119fd6c6677ab4e4b4221520b647376b75ef54950df689
MD5 43719c099ae11c965e0875d70ed271be
BLAKE2b-256 5191317f40d9da7ed338a12534b9ca2f75100b6edf05e6c14a99067a91e12417

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-pp38-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-pp38-none-any.whl
Algorithm Hash digest
SHA256 f59dcf5de099e04d7f44cc199b239c5167b08780cdd313421062511dc4d5775f
MD5 d326784dc87dc41321df22b2ee539633
BLAKE2b-256 a4e48866617e1ff6f275482fa22ad8d6c583d5806c2ddb3061ba6962b21dc3ac

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-cp312-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-cp312-none-any.whl
Algorithm Hash digest
SHA256 bc122370bb96cdb3512b8f2bba37e31cb568ec3b751d2b5bddd6d7cdff35bb9e
MD5 fdf69120e5350ce1a96f80b35c38380e
BLAKE2b-256 4dd858c7a2b0398ae4e8426c54aa99e03d9b5931b27314842f68c1b10579ccba

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-cp311-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-cp311-none-any.whl
Algorithm Hash digest
SHA256 d03c7848b9ff239d7f62bc783ece6b40ab7883b0d2c1874e44555ca4382eacb0
MD5 258225730622b8e5cd45535b530b9b76
BLAKE2b-256 4f9b0ee2de9991eaac657d4a40ce848cdc59a844c068b47aab608451e7b9c627

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-cp310-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-cp310-none-any.whl
Algorithm Hash digest
SHA256 95eb4641cb8de82d31efcdd5273b1bf0958ec251e8a52f2d54cb63f14e44f762
MD5 47794b7934af8aad86931e0ecdd906a4
BLAKE2b-256 f38677c96061ed26acf248fc0fde77d364668f826eb095a41b38ba1ec46606c9

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-cp39-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-cp39-none-any.whl
Algorithm Hash digest
SHA256 bc74c290b7db39e9e3c7de0e42190e1ea6a385926e942722e72d73cfb6a81452
MD5 347276bb8561b7fb4c31879f569db9b2
BLAKE2b-256 c77e730b8e6996eaf7d562b1eccf53edb8ff6f77185b29b261695e9114da130a

See more details on using hashes here.

File details

Details for the file python_lorem-1.3.0.post2-cp38-none-any.whl.

File metadata

File hashes

Hashes for python_lorem-1.3.0.post2-cp38-none-any.whl
Algorithm Hash digest
SHA256 55f3392e2cfb721c5cc631c2fac8afd5bdf8e6b3156d2b130f7d9b127fbe3e4a
MD5 213552241bb1be5607f7eca874c3510f
BLAKE2b-256 134834e71e9d9b946e2b7c9941d5a7cbd41bc5629a4ba8095fa7853cc5b27222

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page