Project for Python Create an application containing the following 2+ user define

Question

Project for Python Create an application containing the following 2+ user defined classes data members per class including at least one use of an list including at least one use of a dictionary (dictionary value should be a complex object, not just a simple value such as number or string) 2+ manipulation methods per class Demonstrate the use of if/if-else statements while loops forloops, including use of range exceptions (try except 1 or more nested loops (while and/or for) File IO for reading and writing data Import library and use of imported library9bjects Due at 4:00pm Dec 12, 2016 University of Colorado CSCI 1300 Fall 2016 Boulder

Explanation / Answer

I am giving one example code that covers all the topics which you have mentioned.

import sys
import nltk
from nltk.tokenize import PunktSentenceTokenizer
from nltk.corpus import product_reviews_2
from nltk.tokenize import RegexpTokenizer
from nltk.tokenize import word_tokenize
from nltk.corpus import stopwords
from nltk.stem import PorterStemmer
from nltk.stem import WordNetLemmatizer
from replacers import RegexpReplacer
from nltk import pos_tag
from nltk.tree import Tree
from nltk import ne_chunk

text = product_reviews_2.raw('ipod.txt')

sent_tokenizer = PunktSentenceTokenizer()
lemmatizer = WordNetLemmatizer()
stop_words = set(stopwords.words('english'))
reg_tokenizer = RegexpTokenizer("[w']+")
custom_reg_tokenizer = RegexpTokenizer("[##]")
replacer = RegexpReplacer()
stemmer = PorterStemmer()

class DataPreprocess:

def __init__(self):
pass
  
def stopWordRemoval(self):
try:
stopWriteFile = open ("stopwords_deleted.txt","a")
i = 1
for sent in sent_tokenizer.tokenize(replacer.replace(text)):
for word in reg_tokenizer.tokenize(sent):
if word.lower() not in stop_words:
stopWriteFile.write((lemmatizer.lemmatize(word.lower()) + " "))   
stopWriteFile.write(". ")

except Exception as ex:
print str(ex)
  
finally:   
stopWriteFile.close()
  

def pos_Tagging(self):
freq_list = []
try:
stopReadFile = open ("stopwords_deleted.txt","r")
posWriteFile = open ("pos_tagged.txt","a")
nounWriteFile = open("cSet_1.txt","a")
nounSentWriteFile = open("nounSents.txt","a")

for review_sent in sent_tokenizer.tokenize(stopReadFile.read()):
review_word = word_tokenize(review_sent)
tagged = ne_chunk(nltk.pos_tag(review_word),binary=False)
for key,tag in tagged:
if tag == 'NN':
nounSentWriteFile.write(" "+key)
nounSentWriteFile.write(". ")
  
posWriteFile.write(str(tagged)+" ")
chunkGrammar_NN = r"""NN: {<NN>} """
chunkParser_NN = nltk.RegexpParser(chunkGrammar_NN)
tree_NN = chunkParser_NN.parse(tagged)
for subtree in tree_NN.subtrees():
if subtree.label() == 'NN':
for word,label in subtree.leaves():
nounWriteFile.write(word+" ")#candidate sets
else:
pass

except Exception as ex:
print(str(ex))
  
finally:
stopReadFile.close()
posWriteFile.close()
nounWriteFile.close()
nounSentWriteFile.close()

  
  
  
  
  
  
  

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