Update app.py

app.py

@@ -1,31 +1,63 @@
+import streamlit as st
 import snscrape.modules.twitter as sntwitter
 import pandas as pd
-import gradio as gr
-from tqdm import tqdm
+import time
+import random
 
-def scrape_tweets(query, max_tweets):
+# Function to scrape tweets
+def scrape_tweets(keyword, num_tweets):
     tweets = []
-    for i, tweet in enumerate(tqdm(sntwitter.TwitterSearchScraper(query).get_items(), total=max_tweets)):
-        if i >= max_tweets:
-            break
-        tweets.append([tweet.date, tweet.content, tweet.user.username, tweet.likeCount, tweet.retweetCount])
+    
+    try:
+        scraper = sntwitter.TwitterSearchScraper(keyword).get_items()
 
-    df = pd.DataFrame(tweets, columns=["Date", "Tweet", "User", "Likes", "Retweets"])
-    filename = "twitter_dataset.csv"
-    df.to_csv(filename, index=False)
+        for i, tweet in enumerate(scraper):
+            if i >= num_tweets:
+                break
+            tweets.append([tweet.date, tweet.content, tweet.user.username, tweet.likeCount, tweet.retweetCount])
+            time.sleep(random.uniform(0.5, 1.5))  # Random delay to avoid rate limits
+        
+        if tweets:
+            df = pd.DataFrame(tweets, columns=["Date", "Tweet", "User", "Likes", "Retweets"])
+            return df
+        else:
+            return None
     
-    return filename
+    except Exception as e:
+        st.error(f"Error while scraping: {str(e)}")
+        return None
+
+# Streamlit UI
+st.title("Twitter Scraper")
+st.markdown("🔹 **Scrape & Download Tweets** (Political/Funny/Custom)")
+
+# Input fields
+keyword = st.text_input("Enter keyword(s) for tweets (e.g., 'funny OR meme OR politics'):")
+num_tweets = st.number_input("Number of tweets to scrape:", min_value=10, max_value=100000, value=1000, step=100)
 
-# Gradio UI for running the scraper
-iface = gr.Interface(
-    fn=scrape_tweets,
-    inputs=[
-        gr.Textbox(label="Search Query", placeholder="e.g., AI OR Machine Learning"),
-        gr.Number(label="Number of Tweets", value=1)
-    ],
-    outputs=gr.File(label="Download CSV"),
-    title="Twitter Scraper",
-    description="Enter a search query and scrape up to 100,000 tweets, then download them as a CSV.",
-)
+# Scrape button
+if st.button("Scrape Tweets"):
+    if keyword:
+        with st.spinner("Scraping tweets..."):
+            df = scrape_tweets(keyword, num_tweets)
+        
+        if df is not None:
+            st.success(f"✅ Scraped {len(df)} tweets!")
+            st.dataframe(df)  # Display table
+            
+            # Download CSV
+            csv = df.to_csv(index=False).encode('utf-8')
+            st.download_button(
+                label="Download CSV 📥",
+                data=csv,
+                file_name="tweets.csv",
+                mime="text/csv",
+            )
+        else:
+            st.warning("⚠ No tweets found. Try different keywords.")
+    else:
+        st.warning("⚠ Please enter a keyword.")
 
-iface.launch()
+# Footer
+st.markdown("---")
+st.markdown("📌 **Note**: This scraper is for educational purposes. Respect Twitter's terms of service.")