import os

import pandas
import yfinance as yf
from get_all_tickers.get_tickers import get_tickers
from pandas import DataFrame

PROJ_PATH = os.path.dirname(__file__)
ticker_data_file = os.path.join(PROJ_PATH, "ticker_data_NYSE.hdf")


def main():
    all_tickers = get_tickers(NASDAQ=False, AMEX=False)
    print(all_tickers)

    data = yf.download(tickers="SPL AAPL", start="2017-01-01", end="2017-04-30", interval="60m", )
    # data = yf.download(tickers="SPL AAPL", start="2017-01-01", end="2017-04-30", interval="1d", )
    data = yf.download(tickers=" ".join(all_tickers), interval="1d")
    # yf.download()

    print(data)
    print(type(data))

    # data.to_csv(ticker_data_file)


def test():
    nyse_tickers = get_tickers(NASDAQ=False, AMEX=False)
    print(nyse_tickers)
    # data = yf.download(tickers="SPL AAPL", start="2017-01-01", end="2017-04-30", interval="60m", )
    data = yf.download(tickers="SPL AAPL", start="2017-01-01", end="2017-04-30", interval="1d", )
    print(data)
    print(data.keys())
    data.to_hdf(ticker_data_file, key='Date')
    exit()


def download_test_data():
    if os.path.exists(ticker_data_file):
        print("file already exists, won't download")
        return
    nyse_tickers = get_tickers(NASDAQ=False, AMEX=False)
    data = yf.download(tickers=" ".join(nyse_tickers), interval="1d")
    print("storing data ...")
    data.to_hdf(ticker_data_file, key="Date")
    print("storing data Done")


def transform_data() -> DataFrame:
    print("reading data ...")
    data = pandas.read_hdf(ticker_data_file)
    print("reading done ...")

    return data


def get_day_x_delta_data(df: DataFrame, day_delta: int = 1, absolute=False) -> DataFrame:
    if absolute:
        return df.diff(day_delta).add_suffix('_{}d'.format(day_delta))
    return (df.diff(day_delta) * 100 / df).add_suffix('_{}d%'.format(day_delta))


if __name__ == '__main__':
    # main()
    try:
        data = transform_data()
    except FileNotFoundError:
        download_test_data()
        data = transform_data()

    print("keys:")
    print(data.keys())
    print("index:")
    print(data.index)

    print(data)

    print(get_day_x_delta_data(data, 1, True))
    print(get_day_x_delta_data(data, 1))
    exit()
    print(data.isnull().sum() / data.shape[0] * 100)


    first_loc = data.index.get_loc(data.index[0])

    print(type(data))
    # print(data.diff())
    for day_diff in range(1, 8):  # one to 7 days
        d_day = data.diff(day_diff) / data
        d_day = d_day.add_suffix('-1%')
        print(d_day)
        print(data.diff(2) / data)

        print(pandas.concat([data, d_day]))
    # print(data["-1"])