def write_song(doc1, doc2):
mc = MarkovChain()
verse = 1
mc.add_file(doc1)
with open(doc2, "w") as f:
while verse < 5:
f.write(("Verse %s" + "\n") % (verse))
for x in range(4):
line = mc.generate_text()
join_line = " ".join(line)
f.write(join_line.capitalize() + "\n")
verse += 1
def write_song(doc1, doc2):
mc = MarkovChain()
verse = 1
mc.add_file(doc1)
with open(doc2, 'w') as f:
while verse < 5:
f.write(('Verse %s' + '\n') % (verse))
for x in range(4):
line = mc.generate_text()
join_line = ' '.join(line)
f.write(join_line.capitalize() + '\n')
f.write('\n')
verse += 1
def main():
try:
mc = MarkovChain()
text = mc.add_file('ascii.txt')
mc.generate_text(text)
except ValueError:
print "Oops! There's been an issue"
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file("story.txt")
print mc.generate_text()
import os from markov_python.cc_markov import MarkovChain mc = MarkovChain() dirname = os.path.dirname(os.path.abspath(__file__)) book = os.path.join(dirname, 'Monologo_do_Vaqueiro_Gil_Vicente.txt') mc.add_file(book) sentence = mc.generate_text() print(sentence)
from markov_python.cc_markov import MarkovChain
q = MarkovChain()
a = MarkovChain()
q.add_file('/users/agaro/desktop/Talk_bot/questions.txt')
a.add_file('/users/agaro/desktop/Talk_bot/answers.txt')
counter = 0
while counter <= 10:
question = q.generate_text(13)
question = ' '.join(question)
print('Bot A: ')
print question
answer = a.generate_text(14)
print('Bot B: ')
answer = ' '.join(answer)
print answer
counter += 1
"""
Run.py includes the code that ties the flow of the application together.
It will be started from the command line.
"""
# Importing the modules needed.
from markov_python.cc_markov import MarkovChain
# Makes a new object.
mc = MarkovChain()
# Adds the text file.
mc.add_file('quotes.json')
# Generates some word in a list.
generatedWords = mc.generate_text(10)
# Prints out the word with the first letter uppercase,
# in a numbered list.
i = 0
for word in generatedWords:
i += 1
print("%s. %s." % (i, word.title()))
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file('C:/Users/dell/PycharmProjects/markov_chain/Wine Reviews.txt')
mc.add_string("red")
word_lst_1 = mc.generate_text(10)
print (word_lst_1)
word_lst_2 = []
for word in word_lst_1:
if word.isdigit() == False:
word_lst_2.append(word)
print(word_lst_2)
not_allowed = ["cases", "made", "has", "while"]
not_all_end = ["with", "and", "or", "on", "direct", "that", "are", "now", "through", "the", "supports", "hard", "a"]
word_lst_3 = []
for word in word_lst_2:
if word not in not_allowed:
word_lst_3.append(word)
print(word_lst_3)
while word_lst_3[len(word_lst_3) - 1] in not_all_end:
del word_lst_3[len(word_lst_3) - 1]
print(word_lst_3)
str1 = ' '.join(word_lst_3)
from markov_python.cc_markov import MarkovChain
import scrapy
mc = MarkovChain()
#add filepath into mc.add_file(filepath) for files created by scrapy
mc.add_file('fetched_text')
#.generate_text() should generate a list of words
listofwords = []
listofwords = mc.generate_text(5)
listofwords = " ".join(listofwords)
print listofwords
from markov_python.cc_markov import MarkovChain as mc
mc_first = MarkovChain()
f = mc.add_file("test_text.rtf")
g = generate_text(f)
print (g)
from markov_python.cc_markov import MarkovChain
import fetch_data
hounds = MarkovChain()
hounds.add_file('D:\Projects\holmes_markov\Hounds.txt')
output = hounds.generate_text()
output = ' '.join(output)
output = output.capitalize() + "."
print output
from markov_python.cc_markov import MarkovChain file = "pg1661.txt" mc = MarkovChain() mc.add_file(file) print mc.generate_text().items
from markov_python.cc_markov import MarkovChain
#standard parser
mc = MarkovChain()
#mc.add_file('C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/carols.txt')
#mc.add_file('C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/farie tales.txt')
#mc.add_file('C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/50Shades.txt')
#mc.add_file('C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/lovecraft.txt')
#mc.add_file('C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/songdata.txt')
mc.add_file(
'C:/Users/Chris/PycharmProjects/CodeCademy/venv/text files/bass_guitar_tabs.txt'
)
lyrics = mc.generate_text(20)
def printChain(L):
s = "\n"
while len(L) > 0:
s = s + L.pop(0) + " "
return s
print printChain(lyrics)
"""
Execute the Markov Chain of the data and produce the output
"""
import data_retrieval
from markov_python.cc_markov import MarkovChain
data_retrieval.retr()
mc = MarkovChain()
mc.add_file("gulistan-raw.txt")
sentence = mc.generate_text(10)
print "\nGENERATED SENTENCE: "
sentence[0] = sentence[0]
for i in range(0, len(sentence)):
print sentence[i],
from markov_python.cc_markov import MarkovChain
import fetch_data
text = fetch_data
mc = MarkovChain()
mc.add_file("C:\Users\Wojtek\Desktop\Python Programming\markov_chain\Data_separate.txt")
start = True
while start == True:
user_input = raw_input("You: ")
if user_input == "bye":
print "Judy: OK, byee!"
start = False
else:
print "Judy: " + " ".join(mc.generate_text())
'''
Created on June 2, 2018
@author: vanessa
'''
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file('songtexte.txt')
lyric = mc.generate_text()
lyric = ' '.join(lyric)
from markov_python.cc_markov import MarkovChain
import random
mc = MarkovChain(3)
mc.add_file('phrase_bank.txt')
generated_song = ""
def generate_verse():
new_verse = ""
for lyric in mc.generate_text(random.randint(5, 16)):
if lyric == 'i' or lyric == "i'm" or lyric == "i'ma" or lyric == "i'mma":
lyric = lyric.capitalize()
if new_verse == "":
lyric = lyric.capitalize()
new_verse += lyric + ' '
return new_verse
def generate_song():
generated_song = ""
for i in range(0, random.randint(45, 55)):
generated_song += (generate_verse() + ('\n'))
return generated_song
print generate_song()
from markov_python.cc_markov import MarkovChain
if __name__ == '__main__':
mc = MarkovChain()
mc.add_file('lyrics.txt')
lyric = mc.generate_text()
lyric = ' '.join(lyric)
lyric = ''.join([i for i in lyric if not i.isdigit()])
print '---------------------------'
print '---------------------------'
print lyric
print '---------------------------'
print '---------------------------'
' ').replace('</br>', ' ').replace('<b>', ' ').replace(
'</b>', ' ').replace('<p>', ' ').replace('</p>', ' ')
song_string += x
#Write lyrics to files.
f.write(song_string)
f.close()
#3. Generate new song text*********************************************************************
mc = MarkovChain() #initialise a MarkovChain class object - REMEMBER brackets!
#read a file or string:
mc.add_file('all_songs.txt')
#generate text (list of words)
output_list = mc.generate_text(200)
#add a new line after every n words (to give appearance of lyric sheet)
n = 10
i = n
while i < len(output_list):
output_list.insert(i, '\n')
i += (n + 1)
#join list of words and newlines into a string
output_string = " ".join(output_list)
#Print to console or save to file
from markov_python.cc_markov import MarkovChain
import fetch_data
lyrics_5 =fetch_data.lyrics_4
#blink_data= open('')
'''with open('/Users/lennykogosov/Desktop/markovproject/text.txt', 'r+') as f:
text=f.read()'''
my_file= open('/Users/lennykogosov/Desktop/markovproject/text.txt', 'r+')
for x in lyrics_5:
my_file.write(x)
#my_file.close()
mc= MarkovChain()
mc.add_file('/Users/lennykogosov/Desktop/markovproject/text.txt')
first_sample= mc.generate_text(20)
print first_sample
my_file.close()
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file('Romeo.txt')
lines = (mc.generate_text(20))
line = " ".join(lines)
newLine = line[0].upper()
for char in line[1:]:
newLine = newLine + char
print(newLine)
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file('/Users/mobpro/desktop/winereviews.txt')
mc.add_string("red")
print str(mc.generate_text(10))
from markov_python.cc_markov import MarkovChain
#import fetch_data
import os
mc = MarkovChain()
file_path = os.getcwd()
print file_path
mc.add_file("sermon_output_" + "0" + ".txt")
initial = mc.generate_text()
def convert_to_string(initial):
sermon_string = ""
for n in initial:
sermon_string += (n + " ")
print sermon_string
return sermon_string
convert_to_string(initial)
'''
Created on 17/02/2019
@author: dinis
'''
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file("texto.txt")
words_list = mc.generate_text()
words_list = " ".join(words_list)
print (words_list)
from markov_python.cc_markov import MarkovChain
import fetch_data
link = 'http://www.e-reading.club/bookreader.php/1020088/Fomina_-_Pritchi._Daosskie%2C_kitayskie%2C_dzenskie.html'
#link='http://www.krotov.info/acts/01/joseph/filon_02.htm'
vocabul = fetch_data.load_web_to_text(link, 'voc.txt')
print type(vocabul)
fetch_data.show_param(str(vocabul))
out_fileS = 'out_text_string.txt'
out_file = 'out_text.txt'
text_object = MarkovChain(3)
text_object.add_file('voc.txt')
out_text = text_object.generate_text(200)
for i in out_text:
try:
print type(i), i.decode('utf8').encode('cp866')
except:
print 'Error'
out_text_j = ' '.join(out_text)
#with open(out_fileS,'w+') as ofile:
# for i in out_text: ofile.write(i+'\n')
with open(out_file, 'w+') as ofile:
for i in out_text:
ofile.write(i + ' ')
#runs the project and outputs the text
from markov_python.cc_markov import MarkovChain
import fetch_data
mc = MarkovChain()
mc.add_file("sermon_output.txt")
initial = mc.generate_text()
def convert_to_file(initial):
sermon_string = ""
for n in initial:
sermon_string += (n + " ")
with open("Markov_Sermon.txt", "w") as f:
f.write(sermon_string)
convert_to_file(initial)
'''
Created on Apr 7, 2018
@author: burust
'''
from markov_python.cc_markov import MarkovChain
mc = MarkovChain()
mc.add_file('lyrics.txt')
lyric = mc.generate_text()
lyric = ' '.join(lyric)
print '(Accompanied by soft guitar riffs, Ed Sheeran sings,)'
print ' '
print '"... ' + lyric + ' ..."'
