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Upload app.py

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