def main():
parser = argparse.ArgumentParser(description='Check input for profanity.')
parser.add_argument('-f',
'--filename',
dest='path',
type=str,
help='Path to input file to check.')
parser.add_argument('-t',
'--text',
dest='text',
type=str,
help='Text to check.')
parser.add_argument("--censor",
help="Returns censored text.",
action="store_true")
args = parser.parse_args()
if args.path:
f = open(args.path)
text = "".join(f.readlines())
elif args.text:
text = args.text
else:
print "No input specified."
return
if args.censor:
print profanity.censor(text)
return
print profanity.contains_profanity(text)
return
async def on_message_edit(before, after):
if after.channel.is_private:
return
if contains_profanity(after.content):
await handle_message(message)
elif not contains_profanity(after.content):
await client.remove_reaction(after, get_pooh(after.server), after.server.me)
async def on_message(message):
if message.channel.is_private:
return
if is_admin(message.author):
if message.content.startswith('!strict'):
client._strict = not client._strict
strict = "on" if client._strict else "off"
reply = f'Watch your language kids. Strict mode: **{strict}**'
await client.send_message(message.channel, reply)
return
if contains_profanity(message.content):
await handle_message(message)
def main():
parser = argparse.ArgumentParser(description='Check input for profanity.')
parser.add_argument('-f', '--filename', dest='path', type=str,
help='Path to input file to check.')
parser.add_argument('-t', '--text', dest='text', type=str,
help='Text to check.')
parser.add_argument("--censor", help="Returns censored text.",
action="store_true")
args = parser.parse_args()
if args.path:
f = open(args.path)
text = "".join(f.readlines())
elif args.text:
text = args.text
else:
print "No input specified."
return
if args.censor:
print profanity.censor(text)
return
print profanity.contains_profanity(text)
return
def home(request):
if request.method=='POST':
form=CommentForm(request.POST)
#com=request.POST.get(['comment'])
com=form['comment'].value()
if form.is_valid():
if(profanity.contains_profanity(com)):
print('Badwords present')
posts=comments.objects.all()
args={'form':form,'posts':posts}
return render(request,'Form.html',args)
else:
stop_words = set(stopwords.words('english'))
tokenizer=nltk.tokenize.punkt.PunktSentenceTokenizer()
tokens=tokenizer.tokenize(com)
tokens2=list()
index=0
for i in tokens:
tokens2=tokens2+word_tokenize(tokens[index])
index=index+1
print('\n\n\nSentence tokens',tokens)
print('\n\n\nWord tokens',tokens2)
filtered_sentence = []
for w in tokens2:
if w.lower() not in stop_words and w not in string.punctuation:
filtered_sentence.append(w.lower())
print('\n\n\nFiltered tokens',filtered_sentence)
tagged=pos_tag(filtered_sentence)
print('\n\n\nPOS tagging',tagged)
candNouns=[word for word,pos in tagged if(pos=='NN'or pos=='NNS' or pos=='NNP' or pos=='NNPS')]
print('\n\n\nCandidate nouns',candNouns)
bigram=list(ngrams(candNouns,2))
result=[list(i) for i in bigram]
print('\n\n\nBigrams',result)
dictionary = corpora.Dictionary(result)
print(dictionary)
corpus = [dictionary.doc2bow(text) for text in result]
print(corpus)
ldamodel = gensim.models.ldamodel.LdaModel(corpus, num_topics=5, id2word = dictionary, passes=20)
print(ldamodel.print_topics(num_topics=5,num_words=2))
form.save()
posts=comments.objects.all()
args={'form':form,'posts':posts}
return render(request,'Form.html',args)
else:
positive=[]
posper=[]
negper=[]
def split_line(line):
cols = line.split("\t")
return cols
def get_words(cols):
words_ids = cols[4].split(" ")
words = [w.split("#")[0] for w in words_ids]
return words
def get_positive(cols):
return cols[2]
def get_negative(cols):
return cols[3]
def get_objective(cols):
return 1 - (float(cols[2]) + float(cols[3]))
def get_gloss(cols):
return cols[5]
def get_scores(filepath, sentiword):
f = open(filepath)
totalobject = 0.0
count = 0.0
totalpositive = 0.0
totalnegative = 0.0
for line in f:
if not line.startswith("#"):
cols = split_line(line)
words = get_words(cols)
for word in sentiword:
if word in words:
if word == "not":
totalobject = totalobject + 0
totalpositive = totalpositive +0
totalnegative = totalnegative + 16
count =count + 1
else:
totalobject = totalobject + get_objective(cols)
totalpositive = totalpositive + float(get_positive(cols))
totalnegative = totalnegative + float(get_negative(cols))
count =count + 1
if count >0:
if totalpositive > totalnegative :
positive.append(1)
posper.append(totalpositive)
print("Positive word : 1")
print("Positive value : ",totalpositive)
print("Negative value : ",totalnegative)
else :
positive.append(-1)
negper.append(totalnegative)
print("Negative : -1")
print("Positive value : ",totalpositive)
print("Negative value : ",totalnegative)
print("average object Score : ",totalobject/count)
print("Etered")
reviews=comments.objects.all()
l=list()
com=""
print(len(reviews))
for rev in reviews:
com=(rev.comment)
l.append(com)
print(l)
for i in l:
comment = i
sentiword = ' '.join(re.sub("(@[A-Za-z0-9]+)|([^0-9A-Za-z \t]) |(\w+:\/\/\S+)", " ", comment).split())
stop_words = set(stopwords.words('english'))
sentiword = sentiword.lower().split(" ")
filtered_sentence = [w for w in sentiword if not w in stop_words ]
get_scores("C:/Users/HP/Desktop/forum/discussion/SentiWordNet_3.0.0_20130122.txt",filtered_sentence)
if len(posper)==0:
posi=0
else:
posi=sum(posper)/len(posper)
if len(negper)==0:
negi=0
else:
negi=sum(negper)/len(negper)
print(posi,negi)
str=""
for i in filtered_sentence:
str=str+" "+i
print(str)
wordcloud = WordCloud(width=2500,height=2000).generate(str)
if os.path.isfile("C:/Users/HP/Desktop/forum - Copy/discussion/static/images/bar.png"):
os.remove("discussion/static/images/bar.png")
if os.path.isfile("C:/Users/HP/Desktop/forum - Copy/discussion/static/images/wordcloud.png"):
os.remove("discussion/static/images/wordcloud.png")
f1=plt.figure(1)
plt.imshow(wordcloud, interpolation="bilinear")
plt.axis("off")
f1.savefig("C:/Users/HP/Desktop/forum - Copy/discussion/static/images/wordcloud.png")
f2=plt.figure(2)
label=['Positive','Negitive']
percentage=[posi,negi]
index = np.arange(len(label))
plt.bar(index,percentage)
plt.xticks(index, label, fontsize=5, rotation=30)
plt.title('Reaction')
f2.savefig("C:/Users/HP/Desktop/forum - Copy/discussion/static/images/bar.png")
form=CommentForm()
posts=comments.objects.all()
args={'form':form,'posts':posts}
return render(request,'Form.html',args)
import profanity
# def check_profanity(text):
# from profanity.profanity import contains_profanity
# profanity.contains_profanity("You smell like shit.")
from profanity import profanity
profanity.contains_profanity("You smell like shit.")
profanity.censor("You smell like shit.")