94 lines
2.3 KiB
Python
94 lines
2.3 KiB
Python
import sys, re, operator, string
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#
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# The monadic class for this example
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#
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class TFTheOne:
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def __init__(self, v):
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self._value = v
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def bind(self, func):
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result = func(self._value)
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return TFTheOne(result)
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def printm(monad):
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print monad._value
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#
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# The functions
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#
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def read_file(path_to_file):
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"""
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Takes a path to a file and returns the entire
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contents of the file as a string
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"""
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f = open(path_to_file)
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data = f.read()
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f.close()
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return data
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def filter_chars(str_data):
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"""
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Takes a string and returns a copy with all nonalphanumeric chars
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replaced by white space
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"""
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pattern = re.compile('[\W_]+')
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return pattern.sub(' ', str_data)
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def normalize(str_data):
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"""
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Takes a string and returns a copy with all characters in lower case """
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return str_data.lower()
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def scan(str_data):
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"""
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Takes a string and scans for words, returning
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a list of words.
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"""
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return str_data.split()
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def remove_stop_words(word_list):
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""" Takes a list of words and returns a copy with all stop words removed """
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f = open('../stop_words.txt')
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stop_words = f.read().split(',')
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f.close()
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# add single-letter words
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stop_words.extend(list(string.ascii_lowercase))
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return [w for w in word_list if not w in stop_words]
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def frequencies(word_list):
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"""
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Takes a list of words and returns a dictionary associating
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words with frequencies of occurrence
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"""
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word_freqs = {}
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for w in word_list:
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if w in word_freqs:
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word_freqs[w] += 1
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else:
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word_freqs[w] = 1
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return word_freqs
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def sort(word_freq):
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"""
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Takes a dictionary of words and their frequencies and returns a list
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of pairs where the entries are sorted by frequency
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"""
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return sorted(word_freq.iteritems(), key=operator.itemgetter(1), reverse=True)
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def print_freqs(word_freqs):
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for tf in word_freqs[0:25]:
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print tf[0], ' - ', tf[1]
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def top25_freqs(word_freqs):
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top25 = ""
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for tf in word_freqs[0:25]:
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top25 += str(tf[0]) + ' - ' + str(tf[1]) + '\n'
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return top25
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#
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# The main function
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#
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printm(TFTheOne(sys.argv[1]).bind(read_file).bind(filter_chars).bind(normalize).bind(scan).bind(remove_stop_words).bind(frequencies).bind(sort).bind(top25_freqs))
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