Update app.py

app.py

@@ -10,12 +10,9 @@ from nltk.sentiment.vader import SentimentIntensityAnalyzer
 
 nltk.download('vader_lexicon')
 
-st.set_page_config(page_title = "Daily News with Sentiment Analysis", layout = "wide")
+st.set_page_config(page_title="Daily Stock Market News with Sentiment Analysis", layout="wide")
 st.title('Daily News with Sentiment Analysis')
 
-# Streamlit App
-#st.title('Daily News with Sentiment Analysis')
-
 # Sidebar inputs
 st.sidebar.title('Input Parameters')
 
@@ -26,29 +23,11 @@ st.sidebar.markdown("""
 3. **View Sentiment**: See articles with sentiment scores (-1 to 1).
 4. **Sort & Download**: Sort data and download as CSV if needed.
 """)
-                        
-ticker = st.sidebar.text_input('Enter Stock Ticker', 'AAPL')
-
-def get_finviz_news_raw(ticker):
-    finviz_url = f'https://finviz.com/quote.ashx?t={ticker}'
-    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:20.0) Gecko/20100101 Firefox/20.0'}
-    response = requests.get(finviz_url, headers=headers)
 
-    if response.status_code != 200:
-        st.error(f"Error fetching data for {ticker}")
-        return None
-
-    soup = BeautifulSoup(response.text, "html.parser")
-    news_table = soup.find("table", class_="fullview-news-outer")
+# Wrapping the stock ticker input in an expander
+with st.sidebar.expander("Stock Ticker Input", expanded=True):
+    ticker = st.text_input('Enter Stock Ticker', 'AAPL')
 
-    if not news_table:
-        st.error(f"No news found for {ticker}")
-        return None
-
-
-nltk.download('vader_lexicon')
-
-# Function to get news from Finviz
 def get_finviz_news_raw(ticker):
     finviz_url = f'https://finviz.com/quote.ashx?t={ticker}'
     headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:20.0) Gecko/20100101 Firefox/20.0'}
@@ -74,10 +53,7 @@ def get_finviz_news_raw(ticker):
         news_title_cell = row.find("a", class_="tab-link-news")
 
         date_time_str = date_time_cell.get_text().strip() if date_time_cell else ''
-        #news_source = news_source_cell.get_text().strip("()") if news_source_cell else ''
-        #news_source = news_source_cell.get_text().replace('(', '').replace(')', '') if news_source_cell else ''
         news_source = news_source_cell.get_text() if news_source_cell else ''
-        
         news_title = news_title_cell.get_text().strip() if news_title_cell else ''
         news_link = news_title_cell['href'] if news_title_cell else ''
 
@@ -104,7 +80,6 @@ def analyze_sentiment(text):
     sentiment = sia.polarity_scores(text)
     return sentiment['compound']  # Sentiment score between -1 (negative) and 1 (positive)
 
-
 # Fetch and display news when the button is pressed
 if st.sidebar.button('Get News'):
     news_df_raw = get_finviz_news_raw(ticker)
@@ -155,10 +130,8 @@ if st.sidebar.button('Get News'):
         df.drop(columns=['Cleaned_Title', 'Datetime', 'Source'], inplace=True)
         df = df.reset_index(drop=True)
         
-
         st.write(f"## News for {ticker}")
-        #st.dataframe(df, height=600, width=1000)  # Use st.dataframe with height and width to allow for resizing and better display
-        #st.table(df)
+        st.dataframe(df, use_container_width=True, height=800)  # Increased height to 800 pixels
 
         # Option to download data as CSV
         csv = df.to_csv(index=False).encode('utf-8')
@@ -168,15 +141,13 @@ if st.sidebar.button('Get News'):
             file_name=f'{ticker}_news_sentiment.csv',
             mime='text/csv',
         )
-        st.table(df)
     else:
         st.write(f"No news found for {ticker}")
 
-
 hide_streamlit_style = """
 <style>
 #MainMenu {visibility: hidden;}
 footer {visibility: hidden;}
 </style>
 """
-st.markdown(hide_streamlit_style, unsafe_allow_html=True) 
+st.markdown(hide_streamlit_style, unsafe_allow_html=True)