def main():
words = cleanup.text_list('text/dickens.txt')
m_chain = markov.order_mchain(2, words)
c_start = markov.start_token(m_chain)
walk_the_dog = markov.walk(c_start, m_chain)
almost = markov.finalize(walk_the_dog)
home = str(almost)
return render_template("main.html", sentence=home)
def main():
#process and import file
words = cleanup.text_list('text/dickens.txt')
m_chain = markov.order_mchain(2, words)
c_start = markov.start_token(m_chain)
walk_the_dog = markov.walk(c_start, m_chain)
almost = markov.finalize(walk_the_dog)
home = str(almost)
# # #create resulting object
# return home
return render_template("main.html", sentence=home)
from sys import argv
import cleanup
import tokenize
import wordcount
import sample
def sentance(histogram, total, loop):
looper = int(loop)
sentance1 = []
word_string = " "
# loop
for i in range(0, looper):
weight_word = sample.weighted_random(histogram, total)
sentance1.append(weight_word)
#turn list into a string
word_string = word_string.join(word for word in sentance1)
return word_string
if __name__ == '__main__':
file1 = argv[1] #file to analyze
looper = int(argv[2]) # number of times that loop will run
hist1 = wordcount.dict_words((cleanup.text_list(file1)))
total = wordcount.sum_value(hist1)
#runs sentance function
print(sentance(hist1, total, looper))
# walks the markov
sentence = ['START', start_token[1]]
#while the last entry in the list sentence is not "STOP"
while sentence[len(sentence)-1] != 'STOP': #or len(sentence) < 19:
window = (sentence[len(sentence) - 2], sentence[len(sentence)-1])
hist = dictionary[tuple(window)]
next_word = sample.weighted_random(hist, sample.sum_value(hist))
sentence.append(next_word)
return(sentence)
def finalize(sentence):
# remove start_token and capatlize the second word of the listself.
sentence.pop(0)
sentence.pop()
sentence[0] = sentence[0].capitalize()
word_string = ''
word_string = word_string.join(' '+ word for word in sentence) + '.'
return word_string
if __name__ == '__main__':
file1 = argv[1] #file to analyze
words = cleanup.text_list(file1)
# m_chain = order_mchain(2, words)
m_chain = m_chain_one(words)
print(m_chain)
# c_start = start_token(m_chain)
# walk_the_dog = walk(c_start, m_chain)
# print(finalize(walk_the_dog))
# Creates a list of unique values
from sys import argv
import cleanup
def unique_list(words):
unique_words = []
for word in words:
if word not in unique_words:
unique_words.append(word)
# return unique words lists
return unique_words
if __name__ == '__main__':
file1 = argv[1]
list = unique_list(cleanup.text_list(file1))
print(list)
#takes a list argument and returns a word count
tuple_list = []
for word in words:
if (word, words.count(word)) not in tuple_list:
tuple_list.append((word, words.count(word)))
return tuple_list
#sums dictionary in histo
def sum_value(histogram):
total = (sum(histogram.values()))
return total
#opens file_name
if __name__ == '__main__':
file1 = argv[1]
print_list = cleanup.text_list(file1)
#promts user for method
print("==================================")
print("Welcome to Hist-o-grama-rama!!!!!")
print("=======>INSTRUCTIONS<============")
print("Press 1 for a Dictionary")
print("Press 2 for a List of Lists")
print("Press 3 for a Tuple")
input1 = input("Which method would you like returned? ")
#dictionary
if input1 == "1":
dict_list = dict_words(print_list)
tots = sum_value(dict_list)
print(dict_list)
print(tots)
def main():
file1 = argv[1]
words = cleanup.text_list(file1)
m_chain = order_mchain(2, words)
print(m_chain)