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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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st.markdown(""" |
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<style> |
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.main { background-color: #f9fbfc; } |
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.stTextInput>div>div>input, .stTextArea textarea { |
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font-size: 16px; |
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padding: 0.5rem; |
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} |
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.stButton>button { |
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background-color: #4CAF50; |
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color: white; |
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font-size: 16px; |
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padding: 0.5rem 1rem; |
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border-radius: 8px; |
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} |
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.stButton>button:hover { |
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background-color: #45a049; |
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} |
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</style> |
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""", unsafe_allow_html=True) |
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st.title("\U0001F4CA Stock News Sentiment Analysis") |
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st.markdown(""" |
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This tool analyzes the sentiment of news articles related to companies you mention in text. |
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\U0001F4A1 *Try input like:* `I want to check Apple, Tesla, and Microsoft.` |
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**Note:** If news fetching fails, it may be due to changes in the Finviz website or access restrictions. |
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""") |
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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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cleaned_input = ", ".join(tickers) |
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st.markdown(f"\U0001F50E **Identified Tickers:** `{cleaned_input}`") |
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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.write(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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