randomsentence 0.2.2

Generate a sentence, randomly or from a list of keywords/initials. This is based on Brown corpus.

# Random Sentence

[](https://travis-ci.org/patarapolw/randomsentence) [](https://pypi.python.org/pypi/randomsentence/) [](https://pypi.python.org/pypi/randomsentence/) [](https://pypi.python.org/pypi/randomsentence/)

Generate a sentence, randomly or from a list of keywords/initials. This is based on Brown corpus.

## Installation

Download the git, and cd, then run ` python setup.py install python -m nltk.downloader all `

## Usage

`pycon >>> from randomsentence import Brown >>> tagged_sentence = Brown().get_tagged_sent() >>> tagged_sentence [('She', 'PPS'), ('saw', 'VBD'), ('it', 'PPO'), ('then', 'RB'), (',', ','), ('the', 'AT'), ('distant', 'JJ'), ('derrick', 'NN'), ('of', 'IN'), ('the', 'AT'), ('wildcat', 'NN'), ('--', '--'), ('a', 'AT'), ('test', 'NN'), ('well', 'RB'), ('in', 'IN'), ('unexplored', 'JJ'), ('country', 'NN'), ('.', '.')] `

For Brown corpus, it is tagged based on Part-of-speech. This can easily be turned to a real sentence.

`pycon >>> from randomsentence import SentenceTool >>> sentence_tool = SentenceTool() >>> sentence_tool.detokenize_tagged(tagged_sentence) 'She saw it then, the distant derrick of the wildcat -- a test well in unexplored country.' >>> from randomsentence import KeywordParse >>> parser = KeywordParse() >>> tagged_sentence = parser.from_keyword_list(['love', 'blind', 'trouble']) >>> tagged_sentence [('On', False), ('the', False), ('love', True), ('he', False), ('stopped', False), ('at', False), ('the', False), ('blind', True), ('to', False), ('receive', False), ('his', False), ('trouble', True)] `

For KeywordParse, the word is tagged based on whether the keyword overlaps.

`pycon >>> sentence_tool.detokenize_tagged(tagged_sentence) 'On the love he stopped at the blind to receive his trouble' >>> tagged_sentence = parser.from_initials('JKr') >>> tagged_sentence [('These', False), ('joints', True), ('may', False), ('be', False), ('knotted', True), ('as', False), ('receives', True)] >>> sentence_tool.detokenize_tagged(tagged_sentence) 'These joints may be knotted as receives' `

Grammar fixing module is also included, in case minor grammar fix is needed. This is based on language-check / languagetool.

`pycon >>> from randomsentence import GrammarCorrector >>> corrector = GrammarCorrector() >>> corrector.correct('A sentence with a error in the Hitchhiker’s Guide tot he Galaxy') 'A sentence with an error in the Hitchhiker’s Guide to the Galaxy' `

## Todo

KeywordParse sometimes fail. It returns None on failure. This needs to be minimized.

## Found In

https://memorable-password.herokuapp.com/