Create app.py

app.py

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+
+import re
+import tweepy
+import pandas as pd
+import gradio as gr
+def search_hashtag1(hashtag_phrase):
+  #hashtag_phrase=input("Enter hashtahg")
+  consumer_key="30GAxNeTfZuPL5SfNhFBodmRF" 
+  consumer_secret="C6O64nP0XjtwaAnXYL9zCcDZKEIP2iL1yVdlsNJtwLiZ5AEEBs"
+  access_token="1246523558563471360-WrbCqO8phqjIzx393mrfOSKvDFPmey"
+  access_token_secret="u7B6yX6ZyTa5ph7xkCFnbzyuD9jbuHHJNL0Y4S7mdZb1J"
+  auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
+  auth.set_access_token(access_token, access_token_secret)
+  api = tweepy.API(auth)
+  fname = '_'.join(re.findall(r"#(\w+)", hashtag_phrase))
+  data_frame=pd.DataFrame(columns={"timestamp"})
+  timestamp=[]
+  tweet_text=[]
+  user_name=[]
+  for tweet in tweepy.Cursor(api.search, q=hashtag_phrase+' -filter:retweets',lang="en", tweet_mode='extended').items(200):
+    timestamp1=tweet.created_at
+    timestamp.append(timestamp1)
+    tweet_text1=tweet.full_text.replace('\n',' ').encode('utf-8')
+    tweet_text.append(tweet_text1)
+    user_name1=tweet.user.screen_name.encode('utf-8')
+    user_name.append(user_name1)
+  data2=pd.DataFrame(timestamp,columns={"timestamp"})
+  data1=pd.DataFrame(tweet_text,columns={"tweet_text"})
+  data3=pd.DataFrame(user_name,columns={"user_name"})
+  data4=pd.concat([data1,data2],axis=1)
+  data5=pd.concat([data4,data3],axis=1)
+  data5.to_csv("tweet_data.csv")
+  #data6=data5.head(10)
+  return data5
+iface = gr.Interface(search_hashtag1,inputs="text",outputs="dataframe",title='Sakil Tweetlib6 App',description="You can extract tweets based on Hashtag.e.g. Please enter #datascience. The app extracts top 500 recent tweets based on the hashtag.")
+iface.launch(inline=False)