def main():
# EXAMPLE VideoId = 'tCXGJQYZ9JA'
link = input("Enter Video : ")
# link=H.my_form_post()
i = 0
while (link[i] != '='):
i = i + 1
id = link[i + 1:]
# Fetch the number of comments
# if count = -1, fetch all comments
# count = int(input("Enter no. of comments to extract : "))
comments = CE.commentExtract(id, 100)
possent = SYT.sentiment(comments)
age = x.main()
print('age is', age)
print('positive content % is', possent)
if (age > 0 and age < 5 and possent == 100):
webbrowser.open(link)
elif (age > 5 and age < 10 and possent > 90):
webbrowser.open(link)
elif (age > 10 and age < 15 and possent > 80):
webbrowser.open(link)
elif (age > 15 and age < 18 and possent > 75):
webbrowser.open(link)
elif (age > 18):
webbrowser.open(link)
else:
print('not accessible')
def main():
# EXAMPLE VideoId = 'tCXGJQYZ9JA'
videoId = input("Enter VideoId : ")
# Fetch the number of comments
# if count = -1, fetch all comments
count = int(input("Enter no. of comments to extract : "))
comments = CE.commentExtract(videoId, count)
SYT.sentiment(comments)
def main():
# Sample VideoId = '6lAUk0uQWEc'
videoId = input("Enter VideoId : ")
# Sample Tweets Keyword = 'Death Stranding'
twitterQuery = input("Enter Twitter Hashtag/Keyword: ")
# Fetch the number of comments
# if count = -1, fetch all comments
count = int(input("Enter no. of comments/tweets to extract : "))
comments = CE.commentExtract(videoId, count)
SYT.sentiment(comments, twitterQuery, count)
def main():
userpositive = open("userpositive.txt", "w")
userpositive.write("")
userpositive.close()
usernegative = open("usernegative.txt", "w")
usernegative.write("")
usernegative.close()
# EXAMPLE VideoId = 'tCXGJQYZ9JA'
videoId = input("Enter VideoId : ")
# Fetch the number of comments
# if count = -1, fetch all comments
count = int(input("Enter no. of comments to extract : "))
comments = CE.commentExtract(videoId, count)
SYT.sentiment(comments)
def main():
videoId = sys.argv[1]
count = 20
comments = CE.commentExtract(videoId, count)
SYT.sentiment(comments)
tags.append("No Tags")
youtube_dict = {'pubDate': pubDate,'tags': tags,'channelId': channelId,'channelTitle': channelTitle,'categoryId':categoryId,'title':title,'videoId':videoId,'viewCount':viewCount,'likeCount':likeCount,'dislikeCount':dislikeCount,'favoriteCount':favoriteCount, 'commentCount':commentCount, 'keyword':keyword, 'url':url}
df = pd.DataFrame(youtube_dict)
df.sort_values(by='viewCount',ascending=False)
import sentimentYouTube as SYT
import comment_extract as CE
import pandas as pd
df['positive']=''
df['negative']=''
for i in df['videoId']:
print(i)
comments = CE.commentExtract(i,100)
pos, neg = SYT.sentiment(comments)
df.loc[df['videoId']==i,['positive']] = pos
df.loc[df['videoId']==i,['negative']] = neg
df = df[(df['positive']!='') | (df['negative']!='')]
df.loc[:,'positive'] =df['positive'].astype(int)
df.loc[:,'negative'] =df['negative'].astype(int)
df.drop_duplicates(['videoId'])
df['pubDate'] = pd.to_datetime(df.pubDate)
df['publishedDate'] = df['pubDate'].dt.strftime('%d/%m/%Y')
df1 = df[['keyword','publishedDate','title','viewCount','channelTitle','commentCount','likeCount','dislikeCount','tags','favoriteCount','videoId','channelId','categoryId','url','positive','negative']]
df1.columns = ['keyword','publishedDate','Title','viewCount','channelTitle','commentCount','likeCount','dislikeCount','tags','favoriteCount','videoId','channelId','categoryId','URL','positive','negative']
export_csv = df1.to_csv (r'/home/YoutubeAPI/Result/youtube_search_keyword_{}.csv'.format(str(HariIni)), index = None, header=True)