72 lines
2.2 KiB
Python
72 lines
2.2 KiB
Python
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# -*- coding: utf-8 -*-
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"""
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Post Statistics
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========================
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This plugin calculates various statistics about a post and stores them in an article.stats dictionary:
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wc: how many words
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read_mins: how many minutes to read this article, based on 250 wpm (http://en.wikipedia.org/wiki/Words_per_minute#Reading_and_comprehension)
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word_counts: frquency count of all the words in the article; can be used for tag/word clouds/
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fi: Flesch-kincaid Index/ Reading Ease
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fk: Flesch-kincaid Grade Level
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"""
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from pelican import signals
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from bs4 import BeautifulSoup
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import re
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from collections import Counter
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from .readability import *
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def calculate_stats(instance):
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if instance._content is not None:
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stats = {}
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content = instance._content
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# How fast do average people read?
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WPM = 250
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# Use BeautifulSoup to get readable/visible text
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raw_text = BeautifulSoup(content, 'html.parser').getText()
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# Process the text to remove entities
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entities = r'\&\#?.+?;'
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raw_text = raw_text.replace(' ', ' ')
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raw_text = re.sub(entities, '', raw_text)
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# Flesch-kincaid readbility stats counts sentances,
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# so save before removing punctuation
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tmp = raw_text
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# Process the text to remove punctuation
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drop = u'.,?!@#$%^&*()_+-=\|/[]{}`~:;\'\"‘’—…“”'
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raw_text = raw_text.translate(dict((ord(c), u'') for c in drop))
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# Count the words in the text
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words = raw_text.lower().split()
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word_count = Counter(words)
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# Return the stats
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stats['word_counts'] = word_count
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stats['wc'] = sum(word_count.values())
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# Calulate how long it'll take to read, rounding up
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stats['read_mins'] = (stats['wc'] + WPM - 1) // WPM
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if stats['read_mins'] == 0:
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stats['read_mins'] = 1
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# Calculate Flesch-kincaid readbility stats
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readability_stats = stcs, words, sbls = text_stats(tmp, stats['wc'])
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stats['fi'] = "{:.2f}".format(flesch_index(readability_stats))
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stats['fk'] = "{:.2f}".format(flesch_kincaid_level(readability_stats))
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instance.stats = stats
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def register():
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signals.content_object_init.connect(calculate_stats)
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