def rsiAlgorithm():

for script in script_list:

data = {\"symbol\":f\"{exchange}:{script}\",\"resolution\": timeframe,\"date_format\":\"1\",\"range_from\": from_date,\"range_to\": today,\"cont_flag\":\"0\"}

try:

hist_data = fyers.history(data)

except Exception as e:

raise e

df = pd.DataFrame(hist_data[\"candles\"], columns=['date', 'open', 'high', 'low', 'close', 'volume'])

df['date'] = pd.to_datetime(df['date'], unit = \"s\", utc=True)

df['date'] = df['date'].dt.tz_convert('Asia/Kolkata')

# df[\"rsi\"] = ta.RSI(df[\"close\"], timeperiod=14).round(2)

df[\"macd\"],df[\"macdsignal\"],df[\"macdhist\"]=ta.MACD(df[\"close\"],fastperiod=12,slowperiod=26,signalperiod=9)

df.dropna(inplace=True)

if not df.empty:

macd_value = df.macd.values[-1]

# print(df)

if(macd_value>macd_overbought) and (df.macd.values[-2]>df.macdsignal.values[-2]) and(df.macd.values[-1]<df.macdsignal.values[-1])and (script not in buy_traded_stock):

buy_traded_stock.append(script)

placeOrder(script, \"buy\")

if (macd_value>macd_oversold)and (df.macd.values[-2]<df.macdsignal.values[-2]) and(df.macd.values[-1]>df.macdsignal.values[-1])and (script not in sell_traded_stock):

sell_traded_stock.append(script)

placeOrder(script, \"sell\")

macd crossover condition