Metadata-Version: 2.1
Name: linguaf
Version: 0.1.1
Summary: Python package for calculating famous measures in computational linguistics
Home-page: https://github.com/Perevalov/LinguaF
Author: Aleksandr Perevalov, Paul Heinze, Andreas Both
Author-email: perevalovproduction@gmail.com
License: MIT
Description: # LinguaF
        
        ![Version](https://img.shields.io/pypi/v/linguaf?logo=pypi)
        ![Downloads](https://img.shields.io/pypi/dm/linguaf)
        ![Repo size](https://img.shields.io/github/repo-size/perevalov/linguaf)
        
        **LinguaF provides an easy access for researchers and developers to methods of quantitative language analysis, such as: readability, complexity, diversity, and other descriptive statistics.**
        
        ## Usage
        
        ```python
        documents = [
            "Pain and suffering are always inevitable for a large intelligence and a deep heart. The really great men must, I think, have great sadness on earth.",
            "To go wrong in one's own way is better than to go right in someone else's.",
            "The darker the night, the brighter the stars, The deeper the grief, the closer is God!"
        ]
        ```
        
        ### Descriptive Statistics
        
        The following descriptive statistics are supported (`descriptive_statistics.py` module):
        
        * Number of characters `char_count`
        * Number of letters `letter_count`
        * Number of punctuation characters `punctuation_count`
        * Number of digits `digit_count`
        * Number of syllables `syllable_count`
        * Number of sentences `sentence_count`
        * Number of n-syllable words `number_of_n_syllable_words`
        * Average syllables per word `avg_syllable_per_word`
        * Average word length `avg_word_length`
        * Average sentence length `avg_sentence_length`
        * Average words per sentence `avg_words_per_sentence`
        
        Additional methods:
        * Get lexical items (nouns, adjectives, verbs, adverbs) `get_lexical_items`
        * Get n-grams `get_ngrams`
        * Get sentences `get_sentences`
        * Get words `get_words`
        * Tokenize `tokenize`
        * Remove punctuation `remove_punctuation`
        * Remove digits `remove_digits`
        
        Example:
        
        ```python
        from linguaf import descriptive_statistics as ds
        
        
        ds.words_per_sentence(documents)
        # Output: 15
        ```
        
        ### Syntactical Complexity
        
        The following syntactical complexity metrics are supported (`syntactical_complexity.py` module): 
        * Mean Dependency Distance (MDD) `mean_dependency_distance`
        
        Example:
        
        ```python
        from linguaf import syntactical_complexity as sc
        
        
        sc.mean_dependency_distance(documents)
        # Output: 2.307306255835668
        ```
        
        ### Lexical Diversity
        
        The following lexical diversity metrics are supported (`lexical_diversity.py` module): 
        * Lexical Density (LD) `lexical_density`
        * Type Token Ratio (TTR) `type_token_ratio`
        * Herdan's Constant or Log Type Token Ratio (LogTTR) `log_type_token_ratio`
        * Summer's Index `summer_index`
        * Root Type Token Ratio (RootTTR) `root_type_token_ratio`
        
        Example:
        
        ```python
        from linguaf import lexical_diversity as ld
        
        
        ld.log_type_token_ratio(documents)
        # Output: 94.03574963462502
        ```
        
        ### Readability
        
        The following readability metrics are supported (`readability.py` module): 
        * Flesch Reading Ease (FRE) `flesch_reading_ease`
        * Flesch-Kincaid Grade (FKG) `flesch_kincaid_grade`
        * Automated Readability Index (ARI) `automated_readability_index`
        * Simple Automated Readability Index (sARI) `automated_readability_index_simple`
        * Coleman's Readability Score `coleman_readability`
        * Easy Listening Score `easy_listening`
        
        
        Example:
        
        ```python
        from linguaf import readability as r
        
        
        r.flesch_kincaid_grade(documents)
        # Output: 4.813333333333336
        ```
        
        ## Install
        
        ### Via PIP
        
        ```bash
        pip install linguaf
        ```
        
        ### Latest version from GitHub
        
        ```bash
        git clone https://github.com/Perevalov/LinguaF.git
        cd LinguaF
        pip install .
        ```
        
        ## Language Support
        
        At the moment, library supports English and Russian languages for all the methods.
        
        ## Citation
        
        TBD
        
Keywords: language features computational linguistics quantitative text analysis
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
