import yfinance as yf # yahoo stock
import csv
import pandas as pd

tsmc = yf.download('2330.TW',
        start='2021-01-01',
        end='2021-12-05',
        progress=False,)

file = './tsmc.csv'
tsmc.to_csv(file, index=True)

#Date,Open,High,Low,Close,Adj Close,Volume

df = pd.read_csv(file,parse_dates=['Date'],index_col=0).dropna()

df_kd = df[['Open','High','Low','Close']] # local header

def KD(data):
        data_df = data.copy() #local copy

        data_df['min'] = data_df['Low'].rolling(9).min() # KD usually  get 9 days
        data_df['max'] = data_df['High'].rolling(9).max()
        data_df['RSV'] = (data_df['Close'] - data_df['min'])/(data_df['max'] - data_df['min']) * 100

        data_df = data_df.dropna() #clean it up

        # init K as 50 days
        K_list = [50]
        for num,rsv in enumerate(list(data_df['RSV'])):
                K_yestarday = K_list[num]
                K_today = 2/3 * K_yestarday + 1/3 * rsv
                K_list.append(K_today)
        data_df['K'] = K_list[1:] #skip header

        # init D as 50
        D_list = [50]
        for num,K in enumerate(list(data_df['K'])):
                D_yestarday = D_list[num]
                D_today = 2/3 * D_yestarday + 1/3 * K
                D_list.append(D_today)
        data_df['D'] = D_list[1:]

        use_df = pd.merge(data,data_df[['K','D','RSV']],left_index=True,right_index=True,how='left')
        return use_df
#end KD

# main start

r = KD(df_kd)
print(r)