Metadata-Version: 1.2
Name: prosegrinder
Version: 1.2.0
Summary: A text analytics library for prose fiction.
Home-page: https://github.com/prosegrinder/python-prosegrinder
Author: David L. Day
Author-email: dday376@gmail.com
License: UNKNOWN
Description: Prosegrinder
        ===============
        
        .. image:: https://img.shields.io/pypi/v/prosegrinder.svg
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            :alt: Latest PyPI version
        
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            :alt: Latest Codacy Coverage Report
        
        A relatively fast, functional prose text counter with readability scoring.
        
        Installation
        ------------
        
        ``prosegrinder`` is available on PyPI. Simply install it with ``pip``::
        
            $ pip install prosegrinder
        
        Usage
        -----
        
        The main use is via the prosegrinder.Prose object.
        
            >>> from prosegrinder import Prose
            >>> p = Prose("Some lengthy text that's actual prose, like a novel or article.")
        
        The Prose object will parse everything down and compute basic staticstics, including word count,
        sentence count, paragraph count, syllable count, point of view, dialogue, narrative, and a set
        of readabilit scores. All objects and attributes should be treated as immutable.
        
        I know this isn't great documentation, but it should be enough to get you going.
        
        Command Line Interaface
        ~~~~~~~~~~~~~~~~~~~~~~~
        
        Prosegrinder now includes a simple CLI for analyzing text in a file:::
        
            Usage: prosegrinder [OPTIONS] FILE
        
            Options:
                -s, --save FILENAME
                -i, --indent INTEGER
                --help                Show this message and exit.
        
        Will provide basic statistics on text from a file, the filename, and the sh256 of text analyzed. Output is json to help facilitate use in automation:::
        
            {
                "filename": "./tests/resources/shortstory.txt",
                "sha256": "5b756dea7c7f0088ff3692e402466af7f4fc493fa357c1ae959fa4493943fc03",
                "word_character_count": 7008,
                "phone_count": 5747,
                "syllable_count": 2287,
                "word_count": 1528,
                "sentence_count": 90,
                "paragraph_count": 77,
                "complex_word_count": 202,
                "long_word_count": 275,
                "pov_word_count": 113,
                "first_person_word_count": 8,
                "second_person_word_count": 74,
                "third_person_word_count": 31,
                "pov": "first",
                    "readability_scores": {
                        "automated_readability_index": 0.281,
                        "coleman_liau_index": 9.425,
                        "flesch_kincaid_grade_level": 8.693,
                        "flesch_reading_ease": 62.979,
                        "gunning_fog_index": 12.079,
                        "linsear_write": 10.733,
                        "lix": 34.975,
                        "rix": 3.056,
                        "smog": 11.688
                    }
            }
        
        
        
        Readbility scores
        ~~~~~~~~~~~~~~~~~
        
        The set of scores automatically calculated:
        
        * Automated Readability Index
        * Coleman Liau Index
        * Flesch Kincaid Grade Level
        * Flesch Reading Ease
        * Gunning Fog Index
        * Linsear Write
        * LIX
        * RIX
        * SMOG
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6
