Library for statistics extraction from texts in Russian
Overview
ruTS is a library that allows extracting statistics from texts in Russian. It provides the following functionality:
Object extraction - creating tools for sentence and word extraction from a text, which can be further employed for counting statistics
Basic statistics - extracting basic linguistic statistics from a text (the number of complex words, syllables, letters, etc)
Readability metrics - counting readability metrics for a text (SMOG Index, Flesch-Kincaid Grade Level, etc)
Lexical diversity metrics - counting lexical diversity metrics for a text (Hapax Legomena Index, Type-Token Ratio, etc)
Morphological statistics - extracting morphological features from a text (part of speech, gender, transitivity, etc)
Datasets - working with a number of preprocessed datasets (soviet reading-books for literature classes, the collected works of Stalin)
Visualization - visualizing text with the help of graphs (Zipf's law, Literature Fingerprinting, Word Tree)
Components - adding the library's classes to spaCy pipelines
API - using functions via RESTful interface
Installation
ruTS requires Python 3.7 or higher. To install the latest stable version from PyPI:
$ pip install ruts
Usage
from ruts import ReadabilityStats
text = "Ног нет, а хожу, рта нет, а скажу: когда спать, когда вставать, когда работу начинать"
rs = ReadabilityStats(text)
rs.get_stats()
{'automated_readability_index': 0.2941666666666656,
'coleman_liau_index': 0.2941666666666656,
'flesch_kincaid_grade': 3.4133333333333304,
'flesch_reading_easy': 83.16166666666666,
'lix': 48.333333333333336,
'smog_index': 0.05}
rs.print_stats()
Метрика | Значение
--------------------------------------------------
Тест Флеша-Кинкайда | 3.41
Индекс удобочитаемости Флеша | 83.16
Индекс Колман-Лиау | 0.29
Индекс SMOG | 0.05
Автоматический индекс удобочитаемости | 0.29
Индекс удобочитаемости LIX | 48.33
