def getCurrencyDaily(symbol, currency):
fileName = 'E:\\scrapy\\phoenixHealth\\code\\scapy\\newCryptoCompare\\currency-daily\\' + symbol + currency + '.csv'
if os.path.isfile(fileName):
print(coinName + " has been downloaded.")
return
test = price.get_historical_data(symbol,
currency,
'day',
info='full',
aggregate=1,
limit=2000)
with open(fileName, 'w', newline="", encoding='utf-8') as datacsv:
csvwriter = csv.writer(datacsv, dialect=("excel"))
firstLine = [
"date", "cryptocurrrency", "open", "high", "low", "close",
"volume-from", "volume-to"
]
csvwriter.writerow(firstLine)
for i in test:
if i['high'] == 0 and i['low'] == 0 and i['open'] == 0 and i[
'close'] == 0 and i['volumeto'] == 0:
continue
data = []
date = i['time'].split(' ')[0].replace('-', '/')
data.append(date)
data.append(symbol + currency)
data.append(i['open'])
data.append(i['high'])
data.append(i['low'])
data.append(i['close'])
data.append(i['volumefrom'])
data.append(i['volumeto'])
csvwriter.writerow(data)
print("Generate " + symbol + currency + ".csv successfully.")
def test_get_historical_data_timestamp(to_ts):
datas = price.get_historical_data('BTC', 'USD', 'minute', to_ts=to_ts)
assert len(datas) == 1441
data = datas[0]
assert data['time'] == '2019-05-15 18:01:00'
def gen_crypto_data(item_id):
result = MySQL(item_id).searchTweetsByHour()
fsym = item_id.upper()
price_data = price.get_current_price(
fsym, 'USD', e='all', try_conversion=True, full=True, format='raw')[fsym]['USD']
result['price'] = price_data['PRICE']
result['coin_supply'] = price_data['SUPPLY']
result['market_cap'] = price_data['MKTCAP']
result['velocity'] = result['price'] * \
result['coin_supply'] / result['market_cap']
result['high'] = 0
result['low'] = float("inf")
result['volume_sold'] = 0
for data in price.get_historical_data(
fsym, 'USD', 'minute', aggregate=10, limit=6):
result['high'] = data['high'] if data['high'] > result['high'] else result['high']
result['low'] = data['low'] if data['low'] < result['low'] else result['low']
result['volume_sold'] += data['volumeto']
file_path = './out/' + fsym + '_crypto.xlsx'
if not os.path.isfile(file_path):
wb = Workbook()
ws = wb.active
ws.append(['price',
'high',
'low',
'volume_sold',
'coin_supply',
'market_cap',
'velocity',
'amount_hour',
'amount_avg',
'amount_spike',
'sentiment_hour',
'sentiment_avg',
'sentiment_spike'])
wb.save(file_path)
else:
wb = load_workbook(file_path)
ws = wb.active
ws.append([time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),
result['price'],
result['high'],
result['low'],
result['volume_sold'],
result['coin_supply'],
result['market_cap'],
result['velocity'],
result['amount_hour'],
result['amount_avg'],
result['amount_spike'],
result['sentiment_hour'],
result['sentiment_avg'],
result['sentiment_spike']])
wb.save(file_path)
return result
def test_get_high_historical_data():
datas = price.get_historical_data('BTC', 'USD', 'minute', info='high')
data = datas[0]
assert data.keys() == set(['time', 'high'])
data['time'] == '2018-09-29 00:30:00'
data['high'] == 6537.44
def get_price():
money = price.get_historical_data('BTC',
'USD',
'hour',
aggregate=1,
limit=(1000))
print(len(money))
print(money)
return 0
def get_past_hour_price(currency):
data = price.get_historical_data(currency, 'USD', 'hour', aggregate=1, limit=(500*24))
price_vec = []
time_vec = []
data_dictionary = {"time": time_vec, "price": price_vec}
for idx in data:
price_vec.append(idx["close"])
time_vec.append(idx["time"])
#print("Time: ", idx["time"], "Close: ", idx["close"])
return data_dictionary
def get_data(self, minutes):
xrp = price.get_historical_data('XRP',
'KRW',
'minute',
e='Bithumb',
aggregate=minutes,
limit=2000)
eth = price.get_historical_data('ETH',
'KRW',
'minute',
e='Bithumb',
aggregate=minutes,
limit=2000)
btc = price.get_historical_data('BTC',
'KRW',
'minute',
e='Bithumb',
aggregate=minutes,
limit=2000)
XRP = pd.DataFrame(xrp)
ETH = pd.DataFrame(eth)
BTC = pd.DataFrame(btc)
return XRP, ETH, BTC
def get_graph_data(coin, currency, period):
times = []
prices = []
historical = price.get_historical_data(coin,
currency,
timeList[period]["period"],
info='close',
aggregate=1,
limit=timeList[period]["count"])
for data in historical:
dt = datetime.datetime.strptime(data["time"], "%Y-%m-%d %H:%M:%S")
times.append(dt)
prices.append(data["close"])
return times, prices
def test_get_historical_data():
datas = price.get_historical_data('BTC', 'USD', 'minute')
assert len(datas) == 1441
data = datas[0]
data['time'] == '2018-09-29 00:30:00'
data['close'] == 6655.97
data['high'] == 6655.99
data['low'] == 6655.58
data['open'] == 6655.99
data['volumefrom'] == 5.21
data['volumeto'] == 34791.94
def get_daily_data(ticker, quantity, plot=False, display=False):
hist = price.get_historical_data(ticker,
'USD',
'day',
aggregate=1,
limit=quantity)
data = pd.DataFrame.from_dict(hist)
if display:
print(data.head())
print(data.tail())
if plot:
plt.plot(data.time, data.close, label="Close")
plt.plot(data.time, data.high, label="High")
plt.plot(data.time, data.open, label="Open")
plt.legend()
plt.grid(True)
plt.show()
return data
def fig300btc():
from cryptocompy import coin, price
fig = plt.figure(figsize=(15, 7.5))
r = price.get_historical_data('BTC', 'USD', 'day', info='close', aggregate=1, limit=300)
axis = fig.add_subplot(1, 1, 1)
prices = []
for value in r:
price = value['close']
price = int(price)
prices.append(price)
dates = []
for value in r:
date = value['time']
date = date[5:]
date = date[:5]
date = date[:2] + date[2:]
dates.append(date)
minprice = min(prices) - 25
axis.plot(dates, prices, 'm')
xticks = axis.get_xticks()
axis.set_xticks(xticks[::30])
axis.tick_params(axis='x', labelsize=13, labelrotation=45)
axis.tick_params(axis='y', labelsize=13)
axis.fill_between(dates, prices, minprice, facecolor='blue', alpha=0.5)
plt.margins(0)
plt.style.use('seaborn-darkgrid')
canvas = FigureCanvas(fig)
output = io.BytesIO()
canvas.print_png(output)
response = make_response(output.getvalue())
response.mimetype = 'image300btc/png'
img = io.BytesIO()
fig.savefig(img, bbox_inches="tight")
img.seek(0)
return send_file(img, mimetype='image300btc/png')
def download(self,
instrument,
period,
number_of_periods,
fromDate,
toDate=None):
logger.debug("Downloading %s" % instrument)
crypto_period = self.period_dict[period]
dict_downloaded = price.get_historical_data(
instrument.symbol,
instrument.currency,
crypto_period,
aggregate=number_of_periods)
if len(dict_downloaded) == 0:
logger.error(
'Cant download cryptocompare %s_%s for %s return None' %
(instrument.symbol, instrument.currency, period))
return None
outputComplete = self.formatHistorical(dict_downloaded)
# Already added
# outputComplete = self.setTimeCorrect(outputComplete, period=period, instrument=instrument)
return outputComplete
