<gh_stars>1-10
from PyQt5.QtWidgets import QApplication, QMainWindow, QMenu, QVBoxLayout, QSizePolicy, QMessageBox, QWidget, QPushButton
from PyQt5.QtGui import QIcon
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.figure import Figure
import matplotlib.pyplot as plt
from itertools import chain
import requests
import datetime
import json
from crypto.backend.bot import Bot

class PlotCanvas(FigureCanvas):
    def __init__(self, parent=None, width=5, height=4, dpi=100):
        fig = Figure(figsize=(width, height), dpi=dpi)
        self.axes = fig.add_subplot(111)

        FigureCanvas.__init__(self, fig)
        self.setParent(parent)

        FigureCanvas.setSizePolicy(self,
                                   QSizePolicy.Expanding,
                                   QSizePolicy.Expanding)
        FigureCanvas.updateGeometry(self)
        self.bitcoinTrack('btc', 50)

    def bitcoinTrack(self, coin, time):
        '''live bitcoin tracking'''

        self.baseURL = 'https://api.coindesk.com/v1/bpi/'
        self.today = datetime.date.today()
        print(self.today)
        self.historical_date = datetime.date.today()-datetime.timedelta(days=time)
        self.coin = 'btc'
        self.get_historical_data(self.coin, self.historical_date, self.today)

    def get_historical_data(self, coin, start, end):
        '''gathers historical data with given currency, start, end'''

        start = f'{start.year:#02d}-{start.month:#02}-{start.day:#02}'
        end = f'{end.year:#02}-{end.month:#02d}-{end.day:#02d}'
        url = f'{self.baseURL}historical/close.json?currency={coin}&start={start}&end={end}'
        r = requests.get(url).json()['bpi']

        # dates and prices in list format (originally in dict keys and values)
        dates = [x for x in chain(r) if x]
        prices = [x for x in chain(r.values()) if x]

        # identify max positions/values
        price_max = max(prices)
        date_pos = prices.index(price_max)
        date_max = dates[date_pos]

        # identify min positions/values
        price_min = min(prices)
        date_min_pos = prices.index(price_min)
        date_min = dates[date_min_pos]

        # add plot to axis
        self.figure.clear()
        ax = self.figure.add_subplot(111)
        self.figure.set_facecolor('lightgray')

        # sort and compress data to plottable format
        lists = sorted(r.items())
        x, y = zip(*lists)

        # graph visuals
        ax.plot(x, y, 'tab:blue')
        ax.set_title('BTC Tracker')
        ax.set_xlabel('Date UTC')
        ax.set_ylabel('Price (USD)')

        # add arrows for high, low, and current price
        ax.annotate(f'Local Max of{price_max} on {date_max}', xy=(date_max, price_max), xytext=(date_max, price_max+5000),
                    arrowprops=dict(facecolor='green', shrink=0.05),
                    )
        ax.annotate(f'Local Min of {price_min} on {date_min}', xy=(date_min, price_min), xytext=(date_min, price_min-7000),
                    arrowprops=dict(facecolor='red', shrink=0.05),
                    )
        ax.annotate(f'Current Price: {prices[-1]}', xy=(dates[-1], prices[-1]), xytext=(dates[-20], prices[-1]-5000),
                    arrowprops=dict(facecolor='blue', shrink=0.15),
                    )
        ax.set_ylim(0, 20_000)   

        self.draw()

    


