def handle(self, *args, **options):
logger.info('Seeding Stock price data...')
for stock in Stock.objects.all():
logger.info('Seeding {}...'.format(stock.ticker))
service = StockDataService(ticker=stock.ticker, name=stock.name, exchange=stock.exchange)
df_util.bulk_stock_price_data_to_model(service.get_stock_data())
logger.info('Finished seeding {}...'.format(stock.ticker))
logger.info('Finished seeding stock data.')
def get_latest_stock_data(ticker):
"""
Method that gets the latest data for a Stock
:param ticker: Ticker of Stock to get data for
"""
from stock.models import StockPriceData
from stock.services import StockDataService
df = StockDataService.get_stock_data(ticker, period='1d', interval='1m')
StockPriceData.objects.create_df_data(df)
print('Added {} minute data'.format(ticker))
def get_bulk_day_stock_data(ticker):
"""
Method that that gets the day data for a Stock
:param ticker: Stock symbool to get data for
"""
from stock.models import StockPriceData
from stock.services import StockDataService
df = StockDataService.get_stock_data(ticker, period='1y', interval='1d')
StockPriceData.objects.create_bulk_data(df)
print('Added {} daily data'.format(ticker))
def create_stocks(self):
""" Method for creating all of the classes listed stocks """
for link in self._stock_links:
resp = requests.get(link)
soup = bs.BeautifulSoup(resp.text, "lxml")
table = soup.find('table', {'class': 'quotes'})
for row in table.findAll('tr')[1:]:
ticker = row.findAll('td')[0].text
mapping = str.maketrans(".", "-")
ticker = ticker.translate(mapping) + ".L"
name = row.findAll('td')[1].text
StockDataService(ticker=ticker,
name=name,
exchange=self._symbol).create_stock()
def bulk_get_exchanges_minute_data(exchange_symbol):
"""
Method that gets a specific exchanges listed stocks minute price data and
creates them in bulk
:param exchange_symbol: Exchange symbol to get data for
"""
from exchange.models import Exchange
from stock.models import Stock, StockPriceData
from stock.services import StockDataService
exchange = Exchange.objects.get(symbol=exchange_symbol)
stocks = Stock.objects.filter(exchange=exchange).order_by('symbol')
for stock in stocks:
df = StockDataService.get_stock_data(stock.symbol, 'max', '1m')
StockPriceData.objects.create_bulk_data(df)
print('Added {} daily minute data'.format(stock.symbol))
def get_exchanges_minute_data(exchange_symbol):
"""
Method that iterates through an exchange and all of its listed stocks
and runs the stock_tasks get_day_stock_data method to get the minute data
for that stock.
:param exchange_symbol: Exchange symbol to get stocks for
"""
from exchange.models import Exchange
from stock.models import Stock, StockPriceData
from stock.services import StockDataService
exchange = Exchange.objects.get(symbol=exchange_symbol)
stocks = Stock.objects.filter(exchange=exchange)
for stock in stocks:
df = StockDataService.get_stock_data(stock.ticker, '1d', '1m')
StockPriceData.objects.create_df_data(df)
print('Added {} minute data')
def compile_stocks_close_data(self):
"""
Compiles the closing price data of the stocks and returns a
dataframe with dates and the stocks respective closing price
on that date.
:return: Dataframe of stock closing prices on dates
"""
main_df = pd.DataFrame()
# Iterates through the stocks and gets their relevant price information and puts it into
# a combined df, main_df
for stock in self._stocks:
df = StockDataService(ticker=stock).get_price_data()
# Check that the stock has any price data available
if not df.empty:
# Format the df to have the timestamp column as the index and then name the close column
# the stocks symbol so it can be identified and then drop the data that's not needed
df.set_index('timestamp', inplace=True)
df.rename(columns={'close': stock}, inplace=True)
df.drop([
'id', 'stock_id', 'open', 'high', 'low', 'volume',
'change', 'change_perc', 'ml_prediction'
],
1,
inplace=True)
# Set the column to the float dtype instead of object, this is needed unlike
# index example as thats read from csv into float dtype automatically
df[stock] = df[stock].astype(float)
# If main df is empty set it to the df otherwise add it to the
# existing main df
if main_df.empty:
main_df = df
else:
main_df = main_df.join(df, how='outer')
main_df.reset_index(drop=True, inplace=True)
return main_df