from typing import List

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

"""Reference: https://github.com/AI4Finance-LLC/FinRL"""

try:
    import exchange_calendars as tc
except:
    print(
        "Cannot import exchange_calendars.",
        "If you are using python>=3.7, please install it.",
    )
    import trading_calendars as tc

    print("Use trading_calendars instead for yahoofinance processor..")
# from basic_processor import _Base
from meta.data_processors._base import _Base
from meta.data_processors._base import calc_time_zone

from meta.config import (
    TIME_ZONE_SHANGHAI,
    TIME_ZONE_USEASTERN,
    TIME_ZONE_PARIS,
    TIME_ZONE_BERLIN,
    TIME_ZONE_JAKARTA,
    TIME_ZONE_SELFDEFINED,
    USE_TIME_ZONE_SELFDEFINED,
    BINANCE_BASE_URL,
)

TIME_ZONE_SELFDEFINED = TIME_ZONE_USEASTERN  # If neither of the above is your time zone, you should define it, and set USE_TIME_ZONE_SELFDEFINED 1.
USE_TIME_ZONE_SELFDEFINED = 1  # 0 (default) or 1 (use the self defined)


class Quandl(_Base):
    def __init__(
        self,
        data_source: str,
        start_date: str,
        end_date: str,
        time_interval: str,
        **kwargs,
    ):
        super().__init__(data_source, start_date, end_date, time_interval, **kwargs)

    def download_data(
        self, ticker_list: List[str], save_path: str = "./data/dataset.csv"
    ):
        self.time_zone = calc_time_zone(
            ticker_list, TIME_ZONE_SELFDEFINED, USE_TIME_ZONE_SELFDEFINED
        )

        # Download and save the data in a pandas DataFrame:
        # data_df = pd.DataFrame()
        # # set paginate to True because Quandl limits tables API to 10,000 rows per call
        # data = quandl.get_table('ZACKS/FC', paginate=True, ticker=ticker_list, per_end_date={'gte': '2021-09-01'}, qopts={'columns': ['ticker', 'per_end_date']})
        # data = quandl.get('ZACKS/FC', ticker=ticker_list,  start_date="2020-12-31", end_date="2021-12-31")
        self.dataframe = quandl.get_table(
            "ZACKS/FC",
            ticker=ticker_list,
            qopts={"columns": ["ticker", "date", "adjusted_close"]},
            date={"gte": self.start_date, "lte": self.end_date},
            paginate=True,
        )
        self.dataframe.dropna(inplace=True)
        self.dataframe.reset_index(drop=True, inplace=True)
        print("Shape of DataFrame: ", self.dataframe.shape)
        # print("Display DataFrame: ", data_df.head())

        self.dataframe.sort_values(by=["date", "ticker"], inplace=True)
        self.dataframe.reset_index(drop=True, inplace=True)

        self.save_data(save_path)

        print(
            f"Download complete! Dataset saved to {save_path}. \nShape of DataFrame: {self.dataframe.shape}"
        )

    # def get_trading_days(self, start, end):
    #