My python program to pick swing stocks

I put the NASDAQ list of stocks in a text file that it reads and tells me which stocks are over 200 day moving average were the macd crossed for swing trading.

Please let me know if anyone has ideas for indicators to improve the output as this is a work in progress. Thanks
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Code:

import yfinance as yf
import pandas as pd
import ta
import talib
masterList = []
master = open("c:\\Stock Auto\\Volume\\master.txt", "r")
masterSymbols = master.readlines()
for masterSymbol in masterSymbols:
    masterSymbol = ''.join(char for char in masterSymbol if char.isalnum())
    masterList.append(masterSymbol)
master.close()

symbols = masterList
#symbols = ["GOOG"]
symbolList = []

for symbol in symbols:
    try:
        ticker = yf.Ticker(symbol)
        # get stock info
        # print(msft.info)
        # get historical market data
        # 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo
        hist = ticker.history(period="6mo")
        closeHistory = hist["Close"]
        volumeHistory = hist["Volume"]
        currentPrice = hist["Close"][-1]

        # ---------------------------------------------------------
        # Indicators
        # ---------------------------------------------------------

        # MACD: Calculate the MACD indicator using a 12-day and 26-day exponential moving average
        exp1 = hist["Close"].ewm(span=12, adjust=False).mean()
        exp2 = hist["Close"].ewm(span=26, adjust=False).mean()
        macd = exp1 - exp2

        # EMA 9: Calculate the signal line using a 9-day exponential moving average of the MACD
        signal = macd.ewm(span=9, adjust=False).mean()

        # EMA 200: Calculate the 200-day exponential moving average using the ewm() function
        ema200 = hist['Close'].ewm(span=200, adjust=False).mean()

        # RSI: Calculate the Relative Strength Index 
        delta = hist['Close'].diff()
        gain = delta.where(delta > 0, 0)
        loss = -delta.where(delta < 0, 0)
        avg_gain = gain.rolling(window=14).mean()
        avg_loss = loss.rolling(window=14).mean()
        rs = avg_gain / avg_loss
        rsiArray = 100 - (100 / (1 + rs))
        rsi = rsiArray.iloc[-1]

        # Bollinger Bands: Calculate the rolling mean and standard deviation of the closing prices
        rolling_mean = hist['Close'].rolling(window=20).mean()
        rolling_std = hist['Close'].rolling(window=20).std()
        upper_band = rolling_mean + 2 * rolling_std
        lower_band = rolling_mean - 2 * rolling_std
       
        # Stock is in UpTrend
        hist['ema20'] = ta.trend.EMAIndicator(close=hist['Close'], window=20).ema_indicator()
        current_close = hist['Close'].iloc[-1]
        current_ema20 = hist['ema20'].iloc[-1]

        # Breakout Indicators
        atr_period = 14
        hist['ATR'] = talib.ATR(hist['High'], hist['Low'], hist['Close'], timeperiod=atr_period)
        ema_period = 5
        hist['ATR_EMA'] = talib.EMA(hist['ATR'], timeperiod=ema_period)
        multiplier = 2.5
        hist['upper_band'] = hist['Close'] + multiplier * hist['ATR_EMA']
        hist['lower_band'] = hist['Close'] - multiplier * hist['ATR_EMA']

        # --------------------------------------------------------
        # Conditions
        #---------------------------------------------------------

        # Price broke upper indicator
        priceBrokeUpperInd = current_close>hist['upper_band'][-1]

        # Price broke lower Indicator
        priceBrokeLowerInd = current_close<hist['lower_band'][-1]

        # UpTrend: Check if the current closing price is above the 20-day EMA
        upTrend = current_close > current_ema20

        # Bollinger Band price is in the lower band
        priceInLowerBollingerBand = currentPrice <= lower_band[-1]

        # RSI < 30
        rsiLessThan30 = rsi<30

        # Condition: Determine if the MACD has crossed the signal line (a bullish signal)
        macdAboveSignalLine = macd[-1] > signal[-1] and macd[-2] < signal[-2]

        # Condition: Last close price above 200 day moving average
        priceAbove200ema = currentPrice > ema200[-1]

        allMatch = upTrend\
                and macdAboveSignalLine\
                and priceAbove200ema\
                and rsiLessThan30\
                and priceInLowerBollingerBand\
                and (priceBrokeUpperInd or priceBrokeLowerInd)
               
        matchCount = 0
       
        # Check Indicators
        if(upTrend):
            matchCount+=1
        if(macdAboveSignalLine):
            matchCount+=1
        if(priceAbove200ema):
            matchCount+=1
        if(rsiLessThan30):
            matchCount+=1
        if(priceInLowerBollingerBand):
            matchCount+=1
        if(priceBrokeLowerInd):
            matchCount+=1
        if(priceBrokeUpperInd):
            matchCount+=1
       
       
        if(matchCount>=3):
            symbolList.append(symbol)
            if(allMatch):
                print(symbol + ": ALL MATCH")
            else:
                if(upTrend):
                    print(symbol + ": Uptrend")
                if(macdAboveSignalLine):
                    print(symbol + ": MacD above Signal")
                if(priceAbove200ema):
                    print(symbol + ": Price above 200 ema")
                if(rsiLessThan30):
                    print(symbol + ": RSI less than 30")
                if(priceInLowerBollingerBand):
                    print(symbol + ": price in lower bollinger") 
                if(priceBrokeUpperInd):
                    print(symbol +": Price broke upper indicator")
                if(priceBrokeLowerInd):
                    print(symbol +": Price broke lower indicator")
    except:
        print("Fail")
        pass
   
print("")
for s in symbolList:
    print(s)
print("Finished")