import numpy as np
import yfinance as yf
import pandas as pd

def calculate_wma(src, length):
    weights = np.arange(1, length + 1)
    wma = np.convolve(src, weights, mode='full') / weights.sum()
    return wma[:-(length-1)]

def calculate_dev(src, length):
    mean = np.mean(src[-length:])
    dev = np.sqrt(np.mean((src[-length:] - mean) ** 2))
    return dev

def calculate_ema(data, window):
    c = 2.0 / (window + 1)
    ema = np.zeros_like(data)
    ema[0] = data[0]
    for i in range(1, len(data)):
        ema[i] = (data[i] - ema[i-1]) * c + ema[i-1]
    return ema

def analyze_symbol(symbol, cci_length, ema_length):
    try:
        data = yf.download(symbol, start="2024-03-01", end="2024-04-25", interval="1h")
        if data.empty:
            raise ValueError(f"No price data found for symbol {symbol}")
        
        src = data['Close'].values

        ma1 = calculate_wma(src, cci_length)
        cci1 = (src - ma1) / (0.015 * calculate_dev(src, cci_length))
        ema_cci1 = calculate_ema(cci1, ema_length)

        crossings = np.where(np.diff(np.sign(cci1 - ema_cci1)))[0]

        if len(crossings) > 0 and cci1[crossings[-1]] > ema_cci1[crossings[-1]]:
            return symbol
    except Exception as e:
        raise ValueError(f"Failed analysis for {symbol} with error: {e}")

def filter_symbols(symbols_df, cci_length, ema_length):
    filtered_symbols = []
    total_symbols = len(symbols_df)
    for i, symbol in enumerate(symbols_df['Symbol'], 1):
        print(f"Analyzing symbol {i}/{total_symbols}: {symbol}")
        try:
            result = analyze_symbol(symbol, cci_length, ema_length)
            if result:
                filtered_symbols.append(result)
        except ValueError as e:
            print(e)  # Hata mesajını ekrana yazdır
    return filtered_symbols

def save_symbols_to_excel(filtered_symbols, output_file):
    filtered_symbols_df = pd.DataFrame(filtered_symbols, columns=['Symbol'])
    filtered_symbols_df.to_excel(output_file, index=False)

def main():
    print("Merhaba Ben Filtreleme Sorgusu Lütfen Excel Dosya Yolunu Aşağıya Girin")
    symbol_file = input("Enter the path to the Excel file containing stock symbols: ")
    symbols_df = pd.read_excel(symbol_file)
    
    cci_length = int(input("Enter the CCI Length: "))
    ema_length = int(input("Enter the EMA Length: "))
    
    print("Filtering symbols...")
    filtered_symbols = filter_symbols(symbols_df, cci_length, ema_length)
    
    output_file = 'CCİ-Hisseler.xlsx'
    save_symbols_to_excel(filtered_symbols, output_file)
    print(f"Filtered symbols saved to {output_file}")

if __name__ == "__main__":
    main()

study(title="CCIEMA", shorttitle="CCI+EMA by perrito Blacky")
length1 = input(20, minval=1, title="CCI")
ma_length = input(13, minval=1, title="EMA")
src = input(close, title="Source")
ma1 = wma(src, length1)
cci1 = (src - ma1) / (0.015 * dev(src, length1))
//plot(ema(cci1, ma_length), color=green, linewidth=2)
plot(ema(cci1, ma_length), linewidth=2)

plotColour = (cci1 > ema(cci1, ma_length)) ? green : red
plotCCIEMA = plot(series=cci1, color=plotColour, linewidth=2)
//plotHoriz  = plot(series=0, color=blue, style=circles)
//fill(plot1=plotCCIEMA, plot2=plotHoriz, color=blue, transp=90)

band0 = hline(200, color=red)
band1 = hline(100, color=blue)
band2 = hline(0,title="zero")
band3 = hline(-100, color=blue)
band4 = hline(-200, color=red)
fill(band1, band3, color=blue, transp=95)