Delete main.py

main.py

@@ -1,91 +0,0 @@
-from stocks import *
-from functions import *
-from datetime import datetime
-import streamlit as st
-
-st.set_page_config(layout="wide")
-
-st.title("Tech Stocks Trading Assistant")
-
-left_column, right_column = st.columns(2)
-
-with left_column:
-
-    all_tickers = {
-                "Apple":"AAPL", 
-                "Microsoft":"MSFT", 
-                "Nvidia":"NVDA", 
-                "Paypal":"PYPL",
-                "Amazon":"AMZN",
-                "Spotify":"SPOT",
-                "Twitter":"TWTR",
-                "AirBnB":"ABNB",
-                "Uber":"UBER",
-                "Google":"GOOG"
-                }
-
-    st.subheader("Technical Analysis Methods")
-    option_name = st.selectbox('Choose a stock:', all_tickers.keys())
-    option_ticker = all_tickers[option_name]
-    execution_timestamp = datetime.now()
-    'You selected: ', option_name, "(",option_ticker,")"
-    'Last execution:', execution_timestamp
-
-    s = Stock_Data()
-    t = s.Ticker(tick=option_ticker)  
-
-    m = Models()
-
-    with st.spinner('Loading stock data...'):
-
-        technical_analysis_methods_outputs = {
-            'Technical Analysis Method': [
-                'Bollinger Bands (20 days & 2 stand. deviations)', 
-                'Bollinger Bands (10 days & 1.5 stand. deviations)', 
-                'Bollinger Bands (50 days & 3 stand. deviations)', 
-                'Moving Average Convergence Divergence (MACD)'
-                ],
-                'Outlook': [
-                    m.bollinger_bands_20d_2std(t),         
-                    m.bollinger_bands_10d_1point5std(t), 
-                    m.bollinger_bands_50d_3std(t), 
-                    m.MACD(t)
-                    ],
-                'Timeframe of Method': [
-                    "Medium-term",         
-                    "Short-term", 
-                    "Long-term", 
-                    "Short-term"
-                    ]
-                }
-
-        df = pd.DataFrame(technical_analysis_methods_outputs)
-
-
-    def color_survived(val):
-        color = ""
-        if (val=="Sell" or val=="Downtrend and sell signal" or val=="Downtrend and no signal"):
-            color="#EE3B3B"
-        elif (val=="Buy" or val=="Uptrend and buy signal" or val=="Uptrend and no signal"):
-            color="#3D9140"
-        else:
-            color="#CD950C"
-        return f'background-color: {color}'
-    
-    
-    st.table(df.sort_values(['Timeframe of Method'], ascending=False).
-               reset_index(drop=True).style.applymap(color_survived, subset=['Outlook']))
-    
-with right_column:
-
-    st.subheader("FinBERT-based Sentiment Analysis")
-
-    with st.spinner("Connecting with www.marketwatch.com..."):
-        st.plotly_chart(m.finbert_headlines_sentiment(t)["fig"])
-        "Current sentiment:", m.finbert_headlines_sentiment(t)["current_sentiment"], "%"
-
-    st.subheader("LSTM-based 7-day stock price prediction model")
-
-    with st.spinner("Compiling LSTM model.."):
-        st.plotly_chart(m.LSTM_7_days_price_predictor(t))
-