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import streamlit as st
import csv
import requests
from bs4 import BeautifulSoup
import pandas as pd
import pyperclip
def scrape_trends(url):
"""
This function scrapes the Twitter Trends webpage and returns a sorted
dataframe of the top hashtags along with their tweet count.
"""
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
data = [] # list to store scraped data
for li in soup.find_all('li'):
a_tag = li.find('a')
title = a_tag.text
tweet_count_tag = li.find('span', class_='tweet-count')
if tweet_count_tag:
tweet_count = tweet_count_tag.text
else:
tweet_count = ''
if title.startswith('#'):
data.append({'Title': title, 'Tweet Count': tweet_count})
# write data to CSV file
with open('trends.csv', mode='w', encoding='utf-8', newline='') as file:
writer = csv.DictWriter(file, fieldnames=['Title', 'Tweet Count'])
writer.writeheader()
writer.writerows(data)
df = pd.read_csv("trends.csv")
df_sorted = df.sort_values('Tweet Count', ascending=False)
df_sorted['Tweet Count'] = df_sorted['Tweet Count'].fillna(1)
df_sorted = df_sorted.reset_index(drop=True)
return df_sorted
def main():
st.title("Twitter Trends")
url = st.text_input("Enter the URL of Twitter Trends page:")
if not url:
st.warning("Please enter a valid URL!")
return
num_title = st.slider("How many titles to include in the output?", 1, 40, 5)
df_sorted = scrape_trends(url)
titles = df_sorted.iloc[:num_title, 0].tolist()
user_text = st.text_input("Enter some text:")
if not user_text:
st.warning("Please enter some text!")
return
for i in range(num_title):
output = user_text + ' ' + ' '.join(titles[:i+1])
st.write(output)
if st.button("Copy Output {}".format(i+1)):
pyperclip.copy(output)
st.success("Output {} copied to clipboard!".format(i+1))
if __name__ == "__main__":
main()
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