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import streamlit as st |
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from func import fetch_news, analyze_sentiment, extract_org_entities |
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import time |
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st.set_page_config(page_title="Stock News Sentiment Analysis", layout="centered") |
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col1, col2 = st.columns([1, 10]) |
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with col1: |
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st.image( |
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"https://upload.wikimedia.org/wikipedia/commons/thumb/e/e8/Finance_Icon_Set_2013_-_Analytics.svg/1024px-Finance_Icon_Set_2013_-_Analytics.svg.png", |
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width=48 |
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) |
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with col2: |
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st.markdown("<h1 style='margin-bottom: 0;'>Stock News Sentiment Analysis</h1>", unsafe_allow_html=True) |
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st.markdown(""" |
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<p style='font-size:17px; margin-top: 0.5rem;'> |
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Analyze the latest news sentiment of companies mentioned in your input. |
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</p> |
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<p style='font-size:17px;'> |
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<strong>💡 Try input like:</strong> <em>I want to check Apple, Tesla, and Microsoft.</em> |
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</p> |
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<p style='font-size:17px;'> |
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<strong>Note:</strong> News may fail to load if the Finviz website structure changes or access is restricted. |
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</p> |
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""", unsafe_allow_html=True) |
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free_text = st.text_area("Enter text mentioning companies:", height=100) |
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tickers = extract_org_entities(free_text) |
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if tickers: |
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st.markdown(f"\U0001F50E **Identified Tickers:** `{', '.join(tickers)}`") |
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else: |
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tickers = [] |
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if st.button("Get News and Sentiment"): |
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if not tickers: |
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st.warning("Please mention at least one recognizable company.") |
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else: |
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progress_bar = st.progress(0) |
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total_stocks = len(tickers) |
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for idx, ticker in enumerate(tickers): |
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st.subheader(f"🔍 Analyzing {ticker}") |
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news_list = fetch_news(ticker) |
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if news_list: |
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sentiments = [] |
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for news in news_list: |
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sentiment = analyze_sentiment(news['title']) |
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sentiments.append(sentiment) |
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positive_count = sentiments.count("Positive") |
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negative_count = sentiments.count("Negative") |
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total = len(sentiments) |
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positive_ratio = positive_count / total if total else 0 |
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negative_ratio = negative_count / total if total else 0 |
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if positive_ratio >= 0.4: |
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overall_sentiment = "Positive" |
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elif negative_ratio >= 0.6: |
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overall_sentiment = "Negative" |
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else: |
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overall_sentiment = "Neutral" |
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st.write(f"**Top 3 News Articles for {ticker}:**") |
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for i, news in enumerate(news_list[:3], 1): |
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sentiment = sentiments[i - 1] |
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st.markdown(f"{i}. [{news['title']}]({news['link']}) — **{sentiment}**") |
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st.success(f"**Overall Sentiment for {ticker}: {overall_sentiment}**") |
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else: |
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st.write(f"No news available for {ticker}.") |
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progress_bar.progress((idx + 1) / total_stocks) |
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time.sleep(0.1) |
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