#!/usr/bin/env python
import sys, re, operator, string

#
# The One class for this example
#
class TFTheOne:
    def __init__(self, v):
        self._value = v

    def bind(self, func):
        self._value = func(self._value)
        return self

    def printme(self):
        print(self._value)

#
# The functions
#
def read_file(path_to_file):
    with open(path_to_file) as f:
        data = f.read()
    return data

def filter_chars(str_data):
    pattern = re.compile('[\W_]+')
    return pattern.sub(' ', str_data)

def normalize(str_data):
    return str_data.lower()

def scan(str_data):
    return str_data.split()

def remove_stop_words(word_list):
    with open('../stop_words.txt') as f:
        stop_words = f.read().strip('\n').split(',')
    # add single-letter words
    stop_words.extend(list(string.ascii_lowercase))
    return [w for w in word_list if not w in stop_words]

def frequencies(word_list):
    word_freqs = {}
    for w in word_list:
        if w in word_freqs:
            word_freqs[w] += 1
        else:
            word_freqs[w] = 1
    return word_freqs

def sort(word_freq):
    return sorted(word_freq.items(), key=operator.itemgetter(1), reverse=True)

def top25_freqs(word_freqs):
    top25 = ""
    for tf in word_freqs[0:25]:
        top25 += str(tf[0]) + ' - ' + str(tf[1]) + '\n'
    return top25

#
# The main function
#
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)\
.printme()