#!/usr/bin/env python3
"""
Script to display when the bot will buy a specific pair

Mandatory Cli parameters:
-p / --pair: pair to examine

Optional Cli parameters
-s / --strategy: strategy to use
-d / --datadir: path to pair backtest data
--timerange: specify what timerange of data to use.
-l / --live: Live, to download the latest ticker for the pair
"""
import logging
import sys
from argparse import Namespace

from typing import List

from plotly import tools
from plotly.offline import plot
import plotly.graph_objs as go

from freqtrade.arguments import Arguments
from freqtrade.analyze import Analyze
from freqtrade import exchange
import freqtrade.optimize as optimize

from typing import Dict, List, Any
from freqtrade import persistence
from sqlalchemy import create_engine
from freqtrade.persistence import Trade

logger = logging.getLogger(__name__)
_CONF: Dict[str, Any] = {}

def plot_analyzed_dataframe(args: Namespace) -> None:
    """
    Calls analyze() and plots the returned dataframe
    :return: None
    """
    pair = args.pair.replace('-', '_')
    timerange = Arguments.parse_timerange(args.timerange)

    # Init strategy
    try:
        analyze = Analyze({'strategy': args.strategy})
    except AttributeError:
        logger.critical(
            'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
            args.strategy
        )
        exit()

    tick_interval = analyze.strategy.ticker_interval

    tickers = {}
    if args.live:
        logger.info('Downloading pair.')
        # Init Bittrex to use public API
        exchange.init({'key': '', 'secret': ''})
        tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
    else:
        tickers = optimize.load_data(
            datadir=args.datadir,
            pairs=[pair],
            ticker_interval=tick_interval,
            refresh_pairs=False,
            timerange=timerange
        )
    dataframes = analyze.tickerdata_to_dataframe(tickers)
    dataframe = dataframes[pair]
    dataframe = analyze.populate_buy_trend(dataframe)
    dataframe = analyze.populate_sell_trend(dataframe)

    trades = {}
    if args.db_url:
        engine = create_engine('sqlite:///' + args.db_url)
        persistence.init(_CONF, engine)
        trades = Trade.query.filter(Trade.pair.is_(pair)).all()

    if len(dataframe.index) > 750:
        logger.warning('Ticker contained more than 750 candles, clipping.')
    data = dataframe.tail(750)

    candles = go.Candlestick(
        x=data.date,
        open=data.open,
        high=data.high,
        low=data.low,
        close=data.close,
        name='Price'
    )

    df_buy = data[data['buy'] == 1]
    buys = go.Scattergl(
        x=df_buy.date,
        y=df_buy.close,
        mode='markers',
        name='buy',
        marker=dict(
            symbol='triangle-up-dot',
            size=9,
            line=dict(width=1),
            color='green',
        )
    )
    df_sell = data[data['sell'] == 1]
    sells = go.Scattergl(
        x=df_sell.date,
        y=df_sell.close,
        mode='markers',
        name='sell',
        marker=dict(
            symbol='triangle-down-dot',
            size=9,
            line=dict(width=1),
            color='red',
        )
    )

    trade_buys = go.Scattergl(
        x=[t.open_date.isoformat() for t in trades],
        y=[t.open_rate for t in trades],
        mode='markers',
        name='trade_buy',
        marker=dict(
            symbol='square-open',
            size=11,
            line=dict(width=2),
            color='green'
        )
    )
    trade_sells = go.Scattergl(
        x=[t.close_date.isoformat() for t in trades],
        y=[t.close_rate for t in trades],
        mode='markers',
        name='trade_sell',
        marker=dict(
            symbol='square-open',
            size=11,
            line=dict(width=2),
            color='red'
        )
    )

    bb_lower = go.Scatter(
        x=data.date,
        y=data.bb_lowerband,
        name='BB lower',
        line={'color': "transparent"},
    )
    bb_upper = go.Scatter(
        x=data.date,
        y=data.bb_upperband,
        name='BB upper',
        fill="tonexty",
        fillcolor="rgba(0,176,246,0.2)",
        line={'color': "transparent"},
    )
    macd = go.Scattergl(x=data['date'], y=data['macd'], name='MACD')
    macdsignal = go.Scattergl(x=data['date'], y=data['macdsignal'], name='MACD signal')
    volume = go.Bar(x=data['date'], y=data['volume'], name='Volume')

    fig = tools.make_subplots(
        rows=3,
        cols=1,
        shared_xaxes=True,
        row_width=[1, 1, 4],
        vertical_spacing=0.0001,
    )

    fig.append_trace(candles, 1, 1)
    fig.append_trace(bb_lower, 1, 1)
    fig.append_trace(bb_upper, 1, 1)
    fig.append_trace(buys, 1, 1)
    fig.append_trace(sells, 1, 1)
    fig.append_trace(volume, 2, 1)
    fig.append_trace(macd, 3, 1)
    fig.append_trace(macdsignal, 3, 1)
    fig.append_trace(trade_buys, 1, 1)
    fig.append_trace(trade_sells, 1, 1)

    fig['layout'].update(title=args.pair)
    fig['layout']['yaxis1'].update(title='Price')
    fig['layout']['yaxis2'].update(title='Volume')
    fig['layout']['yaxis3'].update(title='MACD')

    plot(fig, filename='freqtrade-plot.html')


def plot_parse_args(args: List[str]) -> Namespace:
    """
    Parse args passed to the script
    :param args: Cli arguments
    :return: args: Array with all arguments
    """
    arguments = Arguments(args, 'Graph dataframe')
    arguments.scripts_options()
    arguments.common_args_parser()
    arguments.optimizer_shared_options(arguments.parser)
    arguments.backtesting_options(arguments.parser)

    return arguments.parse_args()


def main(sysargv: List[str]) -> None:
    """
    This function will initiate the bot and start the trading loop.
    :return: None
    """
    logger.info('Starting Plot Dataframe')
    plot_analyzed_dataframe(
        plot_parse_args(sysargv)
    )


if __name__ == '__main__':
    main(sys.argv[1:])