def intialize_model():
'''Feed the data to a markov chain and return the object of it'''
poems = fetch_poem()
mc = MarkovChain()
for poem in poems:
mc.add_string(poems[poem])
return mc
def main(args):
mc = MarkovChain()
for a in args[1::]:
fd = FetchData(a)
mc.add_string(fd.fetch_data())
chain = mc.generate_text()
out = (" ").join(chain)
print out
def main(args):
mc = MarkovChain()
for a in args[1::]:
fd = FetchData(a)
mc.add_string(fd.fetch_data())
chain = mc.generate_text()
out = (" ").join(chain)
print out
def get_chain(text, num_words):
#grab the text from the web. Data shouldn't contain HTML.
#initialize the markov chain with text
chain = MarkovChain()
chain.add_string(text)
#ask user for the number of words
#generate the markov chain using the number of words provided
#by the user and the text from the website entered.
chain_out = chain.generate_text(num_words)
stripped_chain = format_chain(chain_out)
return add_punct(stripped_chain)
def generateLyrics(artists): allLyrics = [] if USE_DATABASE == True: # TODO return None else: for artist in artists: allLyrics += [item[1] for item in getAllLyrics(artist)] # end for #print allLyrics mc = MarkovChain(2) for song in allLyrics: mc.add_string(song) # end newLyrics = mc.generate_text(80) print newLyrics return newLyrics
import fetch_data
from markov_python.cc_markov import MarkovChain
print "Welcom to MarkovChain"
url = raw_input("Provide an URL:")
text1 = fetch_data.getURL(url)
mc = MarkovChain()
mc.add_string(text1)
output = mc.generate_text()
print output
from fetch_data import train
from markov_python.cc_markov import MarkovChain
# The above comes from https://github.com/ReagentX/markov_python
import re
# Get the text from a webpage
data = train('http://www.gutenberg.org/files/135/135-h/135-h.htm')
# Clean the page to remove any pesky bits
data = re.sub('<.*?>', '', data)
data = re.sub('&rsquo', '\'', data)
data = re.sub('&rdquo|&ldquo', '\"', data)
# Make a markov chain object
mc = MarkovChain(4)
# Add the data
mc.add_string(data)
text = mc.generate_text(30)
result = ''
for word in text:
result += word + ' '
print(result)
"""
This module will tie together code from fetch_data.py and cc_markov.py.
"""
from markov_python.cc_markov import MarkovChain
import fetch_data
my_chain = MarkovChain()
my_chain.add_string(fetch_data.get_content('http://wiersze.juniora.pl/tuwim/tuwim_l01.html'))
# 3 years
my_text = my_chain.generate_text()
for word in my_text:
print u"word: {}".format(word)
"""
Script for running the project and outputting data
"""
from markov_python.cc_markov import MarkovChain
import fetch_data
"""
"""
# fetch_data.get_text()
open_text = open('concatenated.txt')
base_text = open_text.read()
# base_text = fetch_data.set_text()
# base_text = open('concatenated.txt')
# print (base_text)
# base_text.close()
mc = MarkovChain()
mc.add_string(base_text)
mctext = mc.generate_text()
print(mctext)
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)
Created on Mon Sep 11 21:08:34 2017
@author: ihsan
"""
#import urllib
#from bs4 import BeautifulSoup
import fetch_data
from markov_python.cc_markov import MarkovChain
text = fetch_data.get_forecast()
#print (text)
mc = MarkovChain()
mc.add_string(text)
mctext = mc.generate_text()
#Formatting the text
def formatting(strlist):
new_strlist = []
days = [
'monday', 'tuesday', 'wednesday', 'thursday', 'friday', 'saturday',
'sunday'
]
ampm = ['am', 'pm']
no_comma = ['to', 'mph', 'percent']
strlist[0] = strlist[0].capitalize() #cap first word
'''Running a Markov Chain to build Robert Frost's first "original" poem in 50 years. May need to rerun until you get a good one!'''
from markov_python.cc_markov import MarkovChain
from fetch_data_f import just_poems
mc = MarkovChain()
mc.add_string(just_poems)
#Goal: Make a three stanza poem of 4 lines, 9 words per line in the phrasing of Robert Frost
print '"Random thoughts" by Robert (Markov) Frost\n'
def poem():
stanzas = 3
while stanzas > 0:
stanza()
print("\n")
stanzas = stanzas - 1
def stanza():
set = 4
while set > 0:
raw_list = mc.generate_text()
#convert list to a string, make the first word uppercase and print
string = ' '.join(raw_list)
line = string.capitalize()
print line
set = set - 1
content = request.text
soup = BeautifulSoup(content, "html.parser")
comments = soup.find_all(id="mid-song-discussion")
for comment in comments:
comment.extract()
return soup.find_all(id="lyrics-body-text")[0].get_text()
def grab_hitler(url):
request = requests.get(url)
content = request.text
soup = BeautifulSoup(content, "html.parser")
results = soup.find_all('span','bqQuoteLink')
for result in results:
yield result.get_text()
for url in taytay_urls:
mc.add_string(grab_taytay(url))
output = mc.generate_text(max_length=20)
print "PRE HITLER LYRICS: "
print " ".join(output)
hitlers = grab_hitler(hitler_urls[0])
for hitler in hitlers:
mc.add_string(hitler)
h_output = mc.generate_text(max_length=20)
print "POST HITLER LYRICS: "
print " ".join(h_output)
print("\nOK, I've loaded the original lyrics.")
time.sleep(1)
#below we generate the markov chain
#first we assign values for words per song and words per line for later use in the Markov Chain
num_songs = sum([len(albums[x]) for x in selections])
num_lines = len(out.splitlines())
num_words = len(out.split())
lines_per_song = num_lines / num_songs
words_per_song = num_words / num_songs
words_per_line = words_per_song / lines_per_song
#adds album lyrics to Markov chain data
mc = MarkovChain()
mc.add_string(out)
#prompts the user for the first word of the song, with the option to view available words, and generate the chain
time.sleep(1)
print(
"\nRight, let's move on to your new song. It's time to write the first word!"
)
print(
"Note that the word has to be in your chosen album(s) original lyrics at least once, else I can't generate a new song from it."
)
print(
"You can either view the available words, or just try a common song word like 'love' or 'I' to get started."
)
time.sleep(3)
cont3 = validated_input("\nView available words (y/n)? ", ["y", "n"])
if cont3 == "y":
from markov_python.cc_markov import MarkovChain
import sqlite3
from datetime import datetime
mk = MarkovChain()
conn = sqlite3.connect('tweets.db')
c = conn.cursor()
c.execute("SELECT COUNT(DISTINCT tweet) from home_tweets")
num_rows = c.fetchone()[0]
c.execute("SELECT DISTINCT tweet from home_tweets")
tweets = c.fetchmany(num_rows)
for tweet in tweets:
mk.add_string(list(tweet)[0])
all_status = []
for i in range(int(num_rows / 50)):
all_status.append(" ".join(mk.generate_text(20)))
with open("data/update_status_" + str(datetime.today()) + ".txt",
'wt',
encoding='utf-8') as f:
for status in all_status:
f.write(status)
f.write("\n")
pass
def generate_data():
raw_text = read_data(data_file)
mc = MarkovChain()
mc.add_string(raw_text)
mcg = mc.generate_text()
return mcg
# This section pulls out the lyrics and puts into a list
rough = soup.find_all(itemprop='description')
results2 = list(map(str, rough[0].contents))
stripped_results2 = []
for line in results2[:-5]:
if line != "<br/>":
if line:
stripped_results2.append(line.strip())
song2 = ''.join(stripped_results2)
print("*** New song with more Cowbell!", )
#print (stripped_results2)
mc = MarkovChain()
mc.add_string(song1)
mc.add_string(song2)
x = mc.generate_text()
x = ' '.join(x)
print(x)
# This section pulls out the breaks
# new_rough = rough.replace("<br/>", "")
# print(new_rough)
# This printed the lyrics but included div class and <br> print(soup.find_all(itemprop='description'))
# This found null print(soup.find_all('lyrics'))
# from jerry. Said worked on 2.7 -- print ("".join(map(str, div.contents)))
#div = soup.find('div', id='lyrics')
#soup = BeautifulSoup(r.content, builder=HTMLParserTreeBuilder())
from markov_python.cc_markov import MarkovChain
from fetch_data import fetch_data
lyrics = fetch_data()
mc = MarkovChain()
for song in lyrics:
mc.add_string(song)
print mc
"""text = mc.generate_text(400)
for i in range(0,400,5):
for j in text[i:i+5]:
print j,
print ""
if i % 4 == 0:
print "\n"""
desired_period = str(randint(1, 3))
if desired_period == "1":
period = wagnerian
elif desired_period == "2":
period = positivistic
else:
period = late
# use method to read a string (call multiple times to add additional data)
print
print("Accessing works... ")
for link in period:
if desired_activity == "1":
print period[link] + ": " + link
mc.add_string(fetch_data.acquire_data(link))
# smooth out time if playing game
if desired_activity == "2":
if period == wagnerian:
sleep(12)
if period == late:
sleep(8)
# set parameters of passages (number and length)
number = ""
while number != "1" and number != "2" and number != "3" and number != "4" and number != "5":
print
print("How many passages would you like to generate(1-5)")
number = raw_input("? ")
from markov_python.cc_markov import MarkovChain
import requests
from bs4 import BeautifulSoup, Tag
r = requests.get('https://www.familyfriendpoems.com/print/poem/NDA3ODk=')
response = r.content
soup = BeautifulSoup(response, 'html.parser')
tag = soup.find_all('p') + soup.find_all('script') + soup.find_all(
'b') + soup.find_all('title') + soup.find_all('a')
for i in tag:
i.decompose()
markov_input = soup.get_text()
mc = MarkovChain()
mc.add_string(markov_input)
a = mc.generate_text()
b = mc.generate_text()
c = mc.generate_text()
d = mc.generate_text()
print(' '.join(a))
print(' '.join(b))
print(' '.join(c))
print(' '.join(d))
print(markov_input)
from markov_python.cc_markov import MarkovChain
from fetch_data import lyric_links
lyric_links()
markov_lyrics = open("lyrics.txt", "r")
mc = MarkovChain()
mc.add_string(markov_lyrics.read())
markov_lyrics.close()
answer = " ".join(mc.generate_text())
answer = answer.capitalize()
print answer
'''Running a Markov Chain to build Robert Frost's first "original" poem in 50 years. May need to rerun until you get a good one!'''
from markov_python.cc_markov import MarkovChain
from fetch_data_f import just_poems
mc = MarkovChain()
mc.add_string(just_poems)
#Goal: Make a three stanza poem of 4 lines, 9 words per line in the phrasing of Robert Frost
print '"Random thoughts" by Robert (Markov) Frost\n'
def poem():
stanzas = 3
while stanzas > 0:
stanza()
print ("\n")
stanzas = stanzas - 1
def stanza():
set = 4
while set > 0:
raw_list = mc.generate_text()
#convert list to a string, make the first word uppercase and print
string = ' '.join(raw_list)
line = string.capitalize()
print line
set = set - 1
length = raw_input("?: ")
length = int(length)
except ValueError:
print ""
print "Sorry, that's not a valid length."
print ""
print "Please, try again!"
length = 0
print ""
print "Accessing works... "
for link in books_catalog:
if book == "A":
print "Dead Men Tell No Tale"
mc.add_string(
fetch_data.fetch_web_data(
"https://www.gutenberg.org/files/1703/1703-h/1703-h.htm"))
else:
print "No Hero"
mc.add_string(
fetch_data.fetch_web_data(
"https://www.gutenberg.org/files/11153/11153-h/11153-h.htm"))
"""
generate text from the Markov Chain and
convert output to the required format
"""
for current in range(num_quote):
while True:
try:
temporary = mc.generate_text(length)
formatted = " ".join(temporary)
