# type: ignore

if __name__ == "__main__":

    import datetime
    import time

    import pandas as pd

    from fincal.fincal import TimeSeries

    df = pd.read_csv('test_files/msft.csv')
    df = df.sort_values(by='Date')  # type: ignore
    data_list = [(i.Date, i.Close) for i in df.itertuples()]

    start = time.time()
    ts_data = TimeSeries(data_list, frequency='D', date_format='%d-%m-%Y')
    print(f"Instantiation took {round((time.time() - start)*1000, 2)} ms")
    # ts_data.fill_missing_days()
    start = time.time()
    # ts_data.calculate_returns(as_on=datetime.datetime(2022, 1, 4), closest='next', years=1)
    rr = ts_data.calculate_rolling_returns(datetime.datetime(1994, 1, 1),
                                        datetime.datetime(2022, 2, 17),
                                        frequency='D',
                                        as_on_match='next',
                                        prior_match='previous',
                                        closest='previous',
                                        years=1)

    # ffill_data = ts_data.bfill()
    print(f"Calculation took {round((time.time() - start)*1000, 2)} ms")
    rr.sort()
    for i in rr[:10]:
        print(i)
    # print(ffill_data)
    # print(ts_data)
    # print(repr(ts_data))