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 + ' ..."'