tweetlib6_app / app.py
Sakil's picture
Update app.py
be53401
raw
history blame
1.75 kB
import re
import tweepy
import pandas as pd
import gradio as gr
import itertools
import collections
from collections import Counter
import numpy as np
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)