Simplify map-reduce
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@@ -1,5 +1,4 @@
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#!/usr/bin/env python
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import sys, re, operator, string
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#
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@@ -7,7 +6,7 @@ import sys, re, operator, string
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#
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def partition(data_str, nlines):
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"""
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Generator function that partitions the input data_str (a big string)
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Partitions the input data_str (a big string)
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into chunks of nlines.
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"""
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lines = data_str.split('\n')
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@@ -21,38 +20,22 @@ def split_words(data_str):
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It returns a list of pairs (word, 1), one for each word in the input, so
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[(w1, 1), (w2, 1), ..., (wn, 1)]
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"""
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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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"""
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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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Takes a string and returns a list of words
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"""
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return str_data.split()
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pattern = re.compile('[\W_]+')
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return pattern.sub(' ', str_data).lower().split()
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def _remove_stop_words(word_list):
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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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with open('../stop_words.txt') as f:
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stop_words = f.read().split(',')
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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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# The actual work of splitting the input into words
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result = []
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words = _remove_stop_words(_scan(_normalize(_filter_chars(data_str))))
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words = _remove_stop_words(_scan(data_str))
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for w in words:
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result.append((w, 1))
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@@ -79,21 +62,11 @@ def count_words(pairs_list_1, pairs_list_2):
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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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with open(path_to_file) as f:
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data = f.read()
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return data
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def sort(word_freq):
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"""
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Takes a collection of words and their frequencies
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and returns a collection of pairs where the entries are
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sorted by frequency
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"""
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return sorted(word_freq, key=operator.itemgetter(1), reverse=True)
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@@ -104,6 +77,6 @@ splits = map(split_words, partition(read_file(sys.argv[1]), 200))
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splits.insert(0, []) # Normalize input to reduce
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word_freqs = sort(reduce(count_words, splits))
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for tf in word_freqs[0:25]:
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print tf[0], ' - ', tf[1]
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for (w, c) in word_freqs[0:25]:
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print w, ' - ', c
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