"""
Dataprovider
Responsible to provide data to the bot
including Klines, tickers, historic data
Common Interface for bot and strategy to access data.
"""
import logging
from pathlib import Path
from typing import List, Tuple

from pandas import DataFrame

from freqtrade.data.history import load_pair_history
from freqtrade.exchange import Exchange
from freqtrade.state import RunMode

logger = logging.getLogger(__name__)


class DataProvider:

    def __init__(self, config: dict, exchange: Exchange) -> None:
        self._config = config
        self._exchange = exchange

    def refresh(self,
                pairlist: List[Tuple[str, str]],
                helping_pairs: List[Tuple[str, str]] = None) -> None:
        """
        Refresh data, called with each cycle
        """
        if helping_pairs:
            self._exchange.refresh_latest_ohlcv(pairlist + helping_pairs)
        else:
            self._exchange.refresh_latest_ohlcv(pairlist)

    @property
    def available_pairs(self) -> List[Tuple[str, str]]:
        """
        Return a list of tuples containing pair, ticker_interval for which data is currently cached.
        Should be whitelist + open trades.
        """
        return list(self._exchange._klines.keys())

    def ohlcv(self, pair: str, ticker_interval: str = None, copy: bool = True) -> DataFrame:
        """
        Get ohlcv data for the given pair as DataFrame
        Please use the `available_pairs` method to verify which pairs are currently cached.
        :param pair: pair to get the data for
        :param ticker_interval: ticker interval to get data for
        :param copy: copy dataframe before returning if True.
                     Use False only for read-only operations (where the dataframe is not modified)
        """
        if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
            return self._exchange.klines((pair, ticker_interval or self._config['ticker_interval']),
                                         copy=copy)
        else:
            return DataFrame()

    def historic_ohlcv(self, pair: str, ticker_interval: str = None) -> DataFrame:
        """
        Get stored historic ohlcv data
        :param pair: pair to get the data for
        :param ticker_interval: ticker interval to get data for
        """
        return load_pair_history(pair=pair,
                                 ticker_interval=ticker_interval or self._config['ticker_interval'],
                                 datadir=Path(self._config['datadir'])
                                 )

    def get_pair_dataframe(self, pair: str, ticker_interval: str = None) -> DataFrame:
        """
        Return pair ohlcv data, either live or cached historical -- depending
        on the runmode.
        :param pair: pair to get the data for
        :param ticker_interval: ticker interval to get data for
        """
        if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
            # Get live ohlcv data.
            data = self.ohlcv(pair=pair, ticker_interval=ticker_interval)
        else:
            # Get historic ohlcv data (cached on disk).
            data = self.historic_ohlcv(pair=pair, ticker_interval=ticker_interval)
        if len(data) == 0:
            logger.warning(f"No data found for ({pair}, {ticker_interval}).")
        return data

    def ticker(self, pair: str):
        """
        Return last ticker data
        """
        # TODO: Implement me
        pass

    def orderbook(self, pair: str, maximum: int):
        """
        return latest orderbook data
        :param pair: pair to get the data for
        :param maximum: Maximum number of orderbook entries to query
        :return: dict including bids/asks with a total of `maximum` entries.
        """
        return self._exchange.get_order_book(pair, maximum)

    @property
    def runmode(self) -> RunMode:
        """
        Get runmode of the bot
        can be "live", "dry-run", "backtest", "edgecli", "hyperopt" or "other".
        """
        return RunMode(self._config.get('runmode', RunMode.OTHER))