def calculate_previous_ema(ticker: yf.Ticker,
time_period="1mo",
days_previous=1) -> float:
time_period_days = len(ticker.history(period=time_period))
stock_history = ticker.history(period=time_period)
return stock_history.iloc[time_period_days - days_previous - 1].to_dict(
)['Close'] * (2.5 / (1 + time_period_days)) + calculate_sma(
ticker, time_period) * (1 - (2.5 / (1 + time_period_days)))
def historicaltest():
if request.method == 'GET':
obj = ''
try:
obj = Ticker('msft')
except Exception as ex:
print(ex)
val = ''
try:
val = obj.history(period='max', interval='1d')
val = val.reset_index()
except Exception as ex:
print(ex)
data = dict()
data['date'] = val['Date'].astype(str).tolist()
data['open'] = val['Open'].tolist()
data['high'] = val['High'].tolist()
data['low'] = val['Low'].tolist()
data['close'] = val['Close'].tolist()
data['volume'] = val['Volume'].tolist()
for i in range(0, len(data['date'])):
year = data['date'][i][:4]
month = data['date'][i][5:7]
day = data['date'][i][8:]
dt = datetime.datetime(int(year), int(month), int(day))
timestamp = int(dt.replace(tzinfo=timezone.utc).timestamp())
data['date'][i] = timestamp
outputdata = jsonify(data)
outputdata.headers.add("Access-Control-Allow-Origin", "*")
return outputdata
def getStock(ticker, time):
# get current prices
c = Ticker(ticker)
t = c.history(time)
ans = {}
# return based on change
a = t.to_dict()["Open"].keys()
days = [str(i.to_pydatetime()).split(" ")[0] for i in a]
try:
c = c.info
mc = intword(c['marketCap'], format="%0.3f")
inf = ticker + ": " + c["longName"] + "!Sector: " + \
c['sector'] + "!Market Cap: $" + mc
except:
inf = ticker[1:] + " Index"
if t["Close"][-1] > t["Close"][-2]:
ans["price"] = "{: .2f}".format(t["Close"][-1])
ans["change"] = "+{:.2f}%".format(
(1 - (t["Close"][-2] / t["Close"][-1])) * 100)
ans["change"] += " " * (7 - len(ans["change"])) + "⬆"
ans["history"] = inf + "|" + str(list(zip(days, t["Close"])))
else:
ans["price"] = "{: .2f}".format(t["Close"][-1])
ans["change"] = "-{:.2f}%".format(
((t["Close"][-2] / t["Close"][-1]) - 1) * 100)
ans["change"] += " " * (7 - len(ans["change"])) + "⬇"
ans["history"] = inf + "|" + str(list(zip(days, t["Close"])))
print(ticker)
return ans
def main():
gran = [('2y', '60m'), ('60d', '15m'), ('30d', '5m'), ('7d', '1m')]
config = ConfigParser()
config.read('/opt/market/market.ini')
stocks = config.get('general', 'stocks')
db = "postgres://[email protected]:5432/stocks"
session = market.session.Session(db)
for stock in stocks.split():
print(stock)
if session.check_table(stock):
continue
dfs = list()
ticker = Ticker(stock)
for period, interval in gran:
df = ticker.history(period=period, interval=interval)
dfs.append(df)
df = pd.concat(dfs)
df = market.df.deduplicate(df)
session.push_df(dataframe=df, name=stock)
def previous_high(ticker: yf.Ticker, time_period: str) -> float:
high = 0
stock_history = ticker.history(time_period)
for i in range(0, len(stock_history) - 2):
temp_high = stock_history.iloc[i].to_dict()['High']
if temp_high > high:
high = temp_high
return high
def download_hist(stock_to_download):
try:
ticker_obj = Ticker(stock_to_download)
hist = ticker_obj.history(period="max")
hist.to_csv("data/stocks/" + stock_to_download + ".csv")
except:
error = sys.exc_info()[0]
logger.debug("Unable to download historical stock data for: %s %s",
stock_to_download, str(error))
raise
def run(self):
company = Ticker(self.ticker)
if (company == None):
return
# Get prices using yfinance package.
quotes = company.history(period="max")
# Save results to csv.
with self.output().open("w") as out_file:
quotes.to_csv(out_file, index=False, compression="gzip")
def __get_history(self):
from yfinance import Ticker
from pandas import DataFrame
from datetime import datetime, timedelta, date
# Get stock data from yfinance module from 60 days before 01/01 to today
stock_data = Ticker(self.stock)
df = DataFrame(stock_data.history(start=str(datetime.now().date().replace(month=1, day=1) - timedelta(60)),
end=str(date.today())))
return df
class EquityYFinance(Asset):
def __init__(self, ticker):
from yfinance import Ticker
super().__init__(ticker, None)
self.y = Ticker(ticker)
self.h = self.y.history(period="max")
def price(self, t: Date) -> float:
return self.h.Close[t]
def coupon(self, t: Date) -> float:
return self.h.Dividends[t]
def calculate_sma(ticker: yf.Ticker,
time_period="1mo",
interval="1d") -> float:
stock_history = ticker.history(period=time_period, interval=interval)
summation = 0
time_period_days = 0
for i in range(0, len(stock_history) - 1):
summation += stock_history.iloc[i].to_dict()['Close']
time_period_days += 1
if time_period_days > 0:
return summation / time_period_days
return sys.maxsize
def processHist(ticker: yf.Ticker):
hist = {}
info = {}
data = ticker.history(period='max', interval='5d')
data = data.where(pd.notnull(data), None)
try:
for item in data.T.iteritems():
stuff = dict(item[1])
try:
hist[item[0].value] = stuff
except Exception as e:
hist[item[0]] = stuff
except Exception as e:
hist['error'] = e
return hist
def main():
config = ConfigParser()
config.read('/opt/market/market.ini')
stocks = config.get('general', 'stocks')
db = "postgres://[email protected]:5432/stocks"
session = market.session.Session(db)
for stock in stocks.split():
print(stock)
if not session.check_table(stock):
continue
ticker = Ticker(stock)
df = ticker.history(period='15m', interval='1m')
session.push_df(dataframe=df, name=stock)
def historical():
if request.method == 'POST':
data = json.loads(request.data)
stock = str(data['stock'])
period = str(data['period'])
interval = str(data['interval'])
obj = ''
try:
obj = Ticker(stock)
except Exception as ex:
print(ex)
val = ''
try:
val = obj.history(period=period, interval=interval)
val = val.reset_index()
except Exception as ex:
print(ex)
data = dict()
data['date'] = val['Date'].astype(str).tolist()
data['open'] = val['Open'].tolist()
data['high'] = val['High'].tolist()
data['low'] = val['Low'].tolist()
data['close'] = val['Close'].tolist()
data['volume'] = val['Volume'].tolist()
for i in range(0, len(data['date'])):
year = data['date'][i][:4]
month = data['date'][i][5:7]
day = data['date'][i][8:]
dt = datetime.datetime(int(year), int(month), int(day))
timestamp = int(dt.replace(tzinfo=timezone.utc).timestamp())
data['date'][i] = timestamp
outputdata = jsonify(data)
#outputdata.headers.add("Access-Control-Allow-Origin", "*")
#outputdata.headers.add("Access-Control-Allow-Headers", "*")
#outputdata.headers.add("Access-Control-Allow-Methods", "*")
return outputdata
def get_direction(ticker: yf.Ticker) -> float:
stock_history = ticker.history(period="1d", interval="1m")
return (stock_history.iloc[len(stock_history) - 1].to_dict()['Close'] -
stock_history.iloc[len(stock_history) - 2].to_dict()['Close']
) / stock_history.iloc[len(stock_history) - 2].to_dict()['Close']
def get_high2current_price_change_percent(ticker: yf.Ticker) -> float:
stock_info = ticker.history("1d").iloc[0].to_dict()
return (stock_info['Close'] - stock_info['High']) / stock_info['High']
def calculate_ema(ticker: yf.Ticker, time_period="1mo") -> float:
stock_history = ticker.history(period=time_period)
return stock_history.iloc[len(stock_history) - 1].to_dict()['Close'] * (
2.5 / (1 + len(stock_history))) + calculate_sma(
ticker, time_period) * (1 - (2.5 / (1 + len(stock_history))))
def get_stock_state(ticker: yf.Ticker) -> {}:
stock_info = ticker.history("1d").iloc[0].to_dict()
stock_info['Time'] = datetime.now().strftime("%H:%M:%S")
del stock_info['Dividends']
del stock_info['Stock Splits']
return stock_info
def get_historical_stonk_price_in_usd(stonk: yf.Ticker):
price_data = stonk.history(start='2013-10-01')
return price_data
def get_stonk_price_since_date_in_usd(stonk: yf.Ticker,
since_date: datetime.datetime):
price_data = stonk.history(start=since_date.strftime('%Y-%m-%d'))
return price_data
