from binance.spot import Spot as Client1  # python3 -m pip install python-binance #pip install binance-connector
import pandas as pd
import numpy as np


spot_client = Client1(key="", secret="")
sembol = "BTCUSDT"
period = "1d"
candles = ( spot_client.klines(symbol=str(sembol), interval=str(period), limit = 1000))

df = pd.DataFrame(candles, columns=['open_time', 'open', 'high', 'low', 'close', 'volume', 'close_time',
                                             'quote_asset_volume', 'number_of_trades', 'tbbav', 'tbqav', 'ignore'],
                             dtype=float)

def vidya (dataframe=df, length = 4, source="close"):

    alpha = 2 / (length + 1)
    df['ud1'] = np.where(df[source] > df[source].shift(1), (df[source] - df[source].shift()), 0)
    df['dd1'] = np.where(df[source] < df[source].shift(1), (df[source].shift() - df[source]), 0)
    df['UD'] = df['ud1'].rolling(9).sum()
    df['DD'] = df['dd1'].rolling(9).sum()
    df['CMO'] = ((df['UD'] - df['DD']) / (df['UD'] + df['DD'])).fillna(0).abs()


    df['Var'] = 0.0
    for i in range(length, len(df)):
        df['Var'].iat[i] = (alpha * df['CMO'].iat[i] * df[source].iat[i]) + (1 - alpha * df['CMO'].iat[i]) * \
                           df['Var'].iat[
                               i - 1]
    print("vidya indicator\n", df['Var'])
    return df['Var']

vidya ()