def get_stock_value(ticker):
bl = create_business_logic()
prediction = bl.do_predictions_for(ticker)
last_close = get_last_price(ticker)
live_price = get_live_price(ticker)
return f'<br/><br/>{ticker} prediction: {prediction}<br/><br/>{ticker} last close: {last_close}' \
f'<br/><br/>{ticker} live price: {live_price}<br/><br/>'
def get_stock_value(ticker):
createbl = create_business_logic()
applybl = BusinessLogic(ticker)
prediction = createbl.do_predictions_for(ticker)
buyorsellreco = applybl.classificationbuysell(ticker)
#return f'Tomorrow, we predict a value of: {prediction}$.\n We recommend to {buyorsellreco}\n'
return buyorsellreco
def get_stock_value(ticker):
bl = create_business_logic(ticker)
prediction = bl.do_predictions_for(ticker)
recommendation = prediction[1]
ba_score_test = prediction[0]
answer = "Tomorrow's prediction for " + str(ticker) + ": " \
+ "we recommend you to " + recommendation + " it." \
+" Note that our latest accuracy score for this ticker is: " + ba_score_test
return recommendation
def get_stock_val_with_accuracy(ticker):
bl = create_business_logic()
prediction_and_score = bl.do_predictions_for(ticker)
last_close_price = get_last_close_price(ticker)
result = {
"ticker": f'{ticker}',
"last_close_price": f'{last_close_price.get("close")}',
"prediction": f'{prediction_and_score.get("prediction")}',
"balanced_accuracy": f'{prediction_and_score.get("balanced_accuracy")}'
}
return f'{result}'
def get_stock_value(ticker):
bl = create_business_logic()
bl2 = create_business_logic2()
prediction = bl.do_predictions_for(ticker)
prediction2 = bl2.do_predictions_for(ticker)
last_close = get_last_close(ticker)
live_price = get_live_price(ticker)
before_yesterday_close = get_last_last_close(ticker)
return f'<br/><br/>{ticker} prediction for last close: {prediction}' \
f'<br/><br/>{ticker} last close: {last_close}' \
f'<br/><br/>{ticker} prediction for next close: {prediction2}' \
f'<br/><br/>{ticker} live price: {live_price}' \
f'<br/><br/>{ticker} previous close: {before_yesterday_close}<br/><br/>'
def get_stock_value(ticker):
bl = create_business_logic()
prediction = bl.do_predictions_for(ticker)
return f'{prediction}\n'
def get_stock_value(ticker):
bl = create_business_logic()
prediction = bl.do_predictions_for(ticker)
output = prediction
# return prediction
return render_template('results.html', output=output)
def get_stock_value(ticker):
bl = create_business_logic()
prediction_and_score = bl.do_predictions_for(ticker)
return prediction_and_score.get("prediction")