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 **word**s, **sentence**s, and
**paragraph**s.
Get Random Words
----------------
The `lorem` module provides two different ways for getting random words.
1. `word` -- generate a list of random words
```python
word(count=1, func=None, args=[], kwargs={}) -> Iterable[str]
```
2. `get_word` -- return random words
```python
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
```python
sentence(count=1, comma=(0, 2), word_range=(4, 8)) -> Iterable[str]
```
2. `get_sentence` -- return random sentences
```python
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
```python
paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10)) -> Iterable[str]
```
2. `get_paragraph` -- return random paragraphs
```python
get_paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10), sep=os.linesep) -> Union[str]
```
Raw data
{
"_id": null,
"home_page": "",
"name": "python-lorem",
"maintainer": "Jarry Shaw",
"docs_url": null,
"requires_python": ">=3.5",
"maintainer_email": "",
"keywords": "lorem,loremipsum",
"author": "",
"author_email": "Jarry Shaw <jarryshaw@icloud.com>",
"download_url": "https://files.pythonhosted.org/packages/75/d7/1856ba85f56e587240a01a317017b316d43d5d63d77295881a9173368b1e/python-lorem-1.3.0.post1.tar.gz",
"platform": null,
"description": "Lorem ipsum generator.\n\nIn publishing and graphic design, lorem ipsum is a placeholder text commonly\nused to demonstrate the visual form of a document or a typeface without\nrelying on meaningful content.\n\nThe `lorem` module provides a generic access to generating the lorem ipsum text\nfrom its very original text:\n\n> Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod\n> tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim\n> veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea\n> commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit\n> esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat\n> cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id\n> est laborum.\n\nUsage of the `lorem` module is rather simple. Depending on your needs, the\n`lorem` module provides generation of **word**s, **sentence**s, and\n**paragraph**s.\n\nGet Random Words\n----------------\n\nThe `lorem` module provides two different ways for getting random words.\n\n1. `word` -- generate a list of random words\n\n ```python\n word(count=1, func=None, args=[], kwargs={}) -> Iterable[str]\n ```\n\n2. `get_word` -- return random words\n\n ```python\n get_word(count=1, sep=' ', func=None, args=[], kwargs={}) -> str\n ```\n\nGet Random Sentences\n--------------------\n\nThe `lorem` module provides two different ways for getting random sentences.\n\n1. `sentence` -- generate a list of random sentences\n\n ```python\n sentence(count=1, comma=(0, 2), word_range=(4, 8)) -> Iterable[str]\n ```\n\n2. `get_sentence` -- return random sentences\n\n ```python\n get_sentence(count=1, comma=(0, 2), word_range=(4, 8), sep=' ') -> Union[str]\n ```\n\nGet Random Paragraphs\n---------------------\n\nThe `lorem` module provides two different ways for getting random paragraphs.\n\n1. `paragraph` -- generate a list of random paragraphs\n\n ```python\n paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10)) -> Iterable[str]\n ```\n\n2. `get_paragraph` -- return random paragraphs\n\n ```python\n get_paragraph(count=1, comma=(0, 2), word_range=(4, 8), sentence_range=(5, 10), sep=os.linesep) -> Union[str]\n ```\n\n",
"bugtrack_url": null,
"license": "BSD 3-Clause License",
"summary": "Lorem ipsum generator.",
"version": "1.3.0.post1",
"project_urls": {
"changelog": "https://github.com/JarryShaw/lorem/releases",
"documentation": "https://jarryshaw.github.io/lorem/",
"homepage": "https://jarryshaw.github.io/lorem/",
"repository": "https://github.com/JarryShaw/lorem"
},
"split_keywords": [
"lorem",
"loremipsum"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "4d69d73d84ad4a94c51332a024e5fb23c3c511faa6eef2881f9aaa30d04bf9f5",
"md5": "0fd6b6a09b4fc1b1efad2201dd04cd26",
"sha256": "a4db9ea35622e17920c6b021e437741fafa133a2a6835770fdf18846800263a2"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-cp310-none-any.whl",
"has_sig": false,
"md5_digest": "0fd6b6a09b4fc1b1efad2201dd04cd26",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:28:38",
"upload_time_iso_8601": "2023-06-15T09:28:38.220244Z",
"url": "https://files.pythonhosted.org/packages/4d/69/d73d84ad4a94c51332a024e5fb23c3c511faa6eef2881f9aaa30d04bf9f5/python_lorem-1.3.0.post1-cp310-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "2a5822f16718efce4dc5ae5c950d9cf4619a4ab9f9cc2da9385354d5d3c9a4eb",
"md5": "7418cd26d8b05adad53201a9c9b60454",
"sha256": "e72b925481b788341cb258c23b959ed479c18bd55335dfaa974e09cb25a67fba"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-cp311-none-any.whl",
"has_sig": false,
"md5_digest": "7418cd26d8b05adad53201a9c9b60454",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:28:50",
"upload_time_iso_8601": "2023-06-15T09:28:50.316425Z",
"url": "https://files.pythonhosted.org/packages/2a/58/22f16718efce4dc5ae5c950d9cf4619a4ab9f9cc2da9385354d5d3c9a4eb/python_lorem-1.3.0.post1-cp311-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "f0fe5e9304257487b67aea40104fda648722442eaf31a71c80acbd4d5070722c",
"md5": "541f4fb5ea7dd62f81e3bb4ef4b2e695",
"sha256": "bc911215e220a0a2dd98d233b95b831db1ce2804ab9fff724f6c34ee2c6f165f"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-cp38-none-any.whl",
"has_sig": false,
"md5_digest": "541f4fb5ea7dd62f81e3bb4ef4b2e695",
"packagetype": "bdist_wheel",
"python_version": "cp38",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:28:42",
"upload_time_iso_8601": "2023-06-15T09:28:42.612243Z",
"url": "https://files.pythonhosted.org/packages/f0/fe/5e9304257487b67aea40104fda648722442eaf31a71c80acbd4d5070722c/python_lorem-1.3.0.post1-cp38-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "149bc71586a03e0cc07b2fa29b6b9726654fa27c7fe7e496ab3f38fcba38d79d",
"md5": "c94100636c5d86a829d3fb2dd3039a98",
"sha256": "da5265724035decf14e873e72c940587bfef539648bf0d3a9ec731041d42d41e"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-cp39-none-any.whl",
"has_sig": false,
"md5_digest": "c94100636c5d86a829d3fb2dd3039a98",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:28:37",
"upload_time_iso_8601": "2023-06-15T09:28:37.228476Z",
"url": "https://files.pythonhosted.org/packages/14/9b/c71586a03e0cc07b2fa29b6b9726654fa27c7fe7e496ab3f38fcba38d79d/python_lorem-1.3.0.post1-cp39-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "1c7c2b411d42a3a7a9ce1cd6cdd25c2abb099e59dac7920540ec7eaac864c1dd",
"md5": "492615280c15fd5ae8d4783dbe04335c",
"sha256": "444a2f6d9c1b373119bc20ccad776476fe9b761b531ea50c45b6406e5447fe5f"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-pp38-none-any.whl",
"has_sig": false,
"md5_digest": "492615280c15fd5ae8d4783dbe04335c",
"packagetype": "bdist_wheel",
"python_version": "pp38",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:29:00",
"upload_time_iso_8601": "2023-06-15T09:29:00.901319Z",
"url": "https://files.pythonhosted.org/packages/1c/7c/2b411d42a3a7a9ce1cd6cdd25c2abb099e59dac7920540ec7eaac864c1dd/python_lorem-1.3.0.post1-pp38-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "53286500d5560b65ad0a3757beb53e36c9c05857a68318fe21b831908058899a",
"md5": "9e0c6aa808447113f3f1dbf63ec7c8a6",
"sha256": "9d17253bb7040eef86cac76658eae9628d11c238b2f60e9b0b7a5c3a8b66643e"
},
"downloads": -1,
"filename": "python_lorem-1.3.0.post1-pp39-none-any.whl",
"has_sig": false,
"md5_digest": "9e0c6aa808447113f3f1dbf63ec7c8a6",
"packagetype": "bdist_wheel",
"python_version": "pp39",
"requires_python": ">=3.5",
"size": 9116,
"upload_time": "2023-06-15T09:28:58",
"upload_time_iso_8601": "2023-06-15T09:28:58.590483Z",
"url": "https://files.pythonhosted.org/packages/53/28/6500d5560b65ad0a3757beb53e36c9c05857a68318fe21b831908058899a/python_lorem-1.3.0.post1-pp39-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "75d71856ba85f56e587240a01a317017b316d43d5d63d77295881a9173368b1e",
"md5": "c61a957a0a8b6eda7bbe0bf09569f85d",
"sha256": "6a890b0ae42aea21e90bdd0c2c270843178402b3f2c75a3a454d76db8c597716"
},
"downloads": -1,
"filename": "python-lorem-1.3.0.post1.tar.gz",
"has_sig": false,
"md5_digest": "c61a957a0a8b6eda7bbe0bf09569f85d",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.5",
"size": 11616,
"upload_time": "2023-06-15T09:28:51",
"upload_time_iso_8601": "2023-06-15T09:28:51.583258Z",
"url": "https://files.pythonhosted.org/packages/75/d7/1856ba85f56e587240a01a317017b316d43d5d63d77295881a9173368b1e/python-lorem-1.3.0.post1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-06-15 09:28:51",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "JarryShaw",
"github_project": "lorem",
"travis_ci": false,
"coveralls": true,
"github_actions": true,
"lcname": "python-lorem"
}
JSON
