Files
exercises-in-programming-style/18-reflective/tf-18.py
2013-09-25 10:45:23 -07:00

56 lines
1.7 KiB
Python

#!/usr/bin/env python
import sys, re, operator, string
#
# Two down-to-earth things that cannot be reflected on
# without serious performance penalties
#
stops = set(open("../stop_words.txt").read().split(",") + list(string.ascii_lowercase))
def frequencies_imp(word_list):
"""
Takes a list of words and returns a dictionary associating
words with frequencies of occurrence
"""
word_freqs = {}
for w in word_list:
if w in word_freqs:
word_freqs[w] += 1
else:
word_freqs[w] = 1
return word_freqs
#
# Let's write our function bodies as strings.
# Because we're looking at them from "above"
#
extract_words_func_body = "lambda name : [x.lower() for x in re.split('[^a-zA-Z]+', open(name).read()) if len(x) > 0 and x.lower() not in stops]"
frequencies_func_body = "lambda word_list : frequencies_imp(word_list)"
sort_func_body = "lambda word_freq: sorted(word_freq.iteritems(), key=operator.itemgetter(1), reverse=True)"
#
# So far, this program isn't much about term-frequency. It's about
# a bunch of strings that look like function bodies.
# Let's add our functions to the "base" program, dynamically.
# We're re-writing this program by adding more functions to it
# from "above".
#
exec('extract_words = ' + extract_words_func_body)
exec('frequencies = ' + frequencies_func_body)
exec('sort = ' + sort_func_body)
#
# The main function. This would work just fine:
# word_freqs = sort(frequencies(extract_words(sys.argv[1])))
# But because we're being introspective, we'll call the
# functions also from "above"
#
word_freqs = locals()['sort'](locals()['frequencies'](locals()['extract_words'](sys.argv[1])))
for tf in word_freqs[0:25]:
print tf[0], ' - ', tf[1]