User:Lidia.Pereira/PNMII/WB/POP: Difference between revisions

Latest revision as of 22:32, 2 March 2014

This is the development of 1st Trimester's self-directed research project, which now accomodates the storing of the generated fictions.

#!/usr/bin/env python
#-*- coding:utf-8 -*-

import re
from nltk.probability import FreqDist, LidstoneProbDist
from nltk.probability import ConditionalFreqDist as CFD
from nltk.util import tokenwrap, LazyConcatenation
from nltk.model import NgramModel
from nltk.metrics import f_measure, BigramAssocMeasures
from nltk.collocations import BigramCollocationFinder
from nltk.compat import python_2_unicode_compatible, text_type
import feedparser, pickle, nltk
import random
import nltk.tokenize
import cgi
import urlparse, urllib

url = "http://feeds.bbci.co.uk/news/rss.xml"
searchwords= ["president","minister","cameron","presidential","obama","angela","barroso","pm","chancellor"]
rawFeed = feedparser.parse(url)

# thank you mathijs for my own personalized generate function!
def lidia_generate(dumpty, length=100):
    if '_trigram_model' not in dumpty.__dict__:
        estimator = lambda fdist, bins: LidstoneProbDist(fdist, 0.2)
        dumpty._trigram_model = NgramModel(3, dumpty, estimator=estimator)
    text = dumpty._trigram_model.generate(length)
    return tokenwrap(text) # or just text if you don't want to wrap

def convert (humpty):
    tokens = nltk.word_tokenize(humpty)
    return nltk.Text(tokens)

superSumario = " "
for i in rawFeed.entries:
    sumario = i["summary"].lower()
    for w in searchwords:
        if w in sumario.strip():
            superSumario = superSumario + sumario
            out = (open("afiltertest.txt", "w"))
            pickle.dump(superSumario,out) 

textrss = open('afiltertest.txt').read()
textslash = open('harrypotterslash.txt').read()

names = re.compile(r"[a-z]\s([A-Z]\w+)")
pi = names.findall(textslash)
lista = []

for name in pi:
    if name not in lista:
        lista.append(name)

variavel = ""

for name in lista:
    variavel = variavel + name + "|"
    
ze = "(" + variavel.rstrip ("|") + ")"

nomes = re.compile(ze)

office1 = re.compile(r"(president\s\w+\w+)")
office2 = re.compile(r"(minister\s\w+\w+)")
office3 = re.compile(r"(chancellor\s\w+\w+)")
repls = office1.findall(textrss) + office2.findall(textrss) + office3.findall(textrss)

def r(m):
    return random.choice(repls)

yes = nomes.sub(r,textslash)

lala = re.sub("\"","",yes)

both = lala.strip() + textrss.strip()

puff = convert(both)
title = lidia_generate(puff,5)
title = str(title)
herpDerp = lidia_generate(puff, 500)
herpDerp = str(herpDerp) + "."

#append to a file
dictionary = {}
dictionary["h1"] = title
dictionary["p"] = herpDerp
f = open("slashtest.txt","a")
f.write(urllib.urlencode(dictionary) + "\n")
f.close()

print "Content-Type: text/html"
print 
print """
    <!DOCTYPE html>
<html>
<head>
    <title>President Obama's Panties</title>
    <link href='http://fonts.googleapis.com/css?family=Artifika' rel='stylesheet' type='text/css'>
    <link href='http://fonts.googleapis.com/css?family=Fenix' rel='stylesheet' type='text/css'>
    <style>
        h1 {
        color:#F00;
        font-family: 'Artifika', sans-serif;
        font-size:23px;
        text-transform: lowercase;
        margin:10% 0 0 5%;}
        p {margin:5% 30% 0 5%;
        font-family: 'Fenix', serif;
        font-size:15px;
        text-indent:2%;
        text-align:justify;
        punctuation-trim:[start];}
    </style>
</head>
<body> 
"""

f = open("slashtest.txt")
lines = f.readlines()
for line in reversed(lines):
    d = urlparse.parse_qs(line.rstrip())
    print "<h1>"+d["h1"][0]+"</h1>"
    print "<p>"+d["p"][0]+"</p>"
print """</body>
</html>"""

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 This is the development of 1st Trimester's self-directed research project, which now accomodates the storing of the generated fictions.
+[[File:Cgiscript.png|750px]]
 <syntaxhighlight lang="python">