def test_get_last_LTPs(self):
m = MongoManager(use_archive=True)
m.reconnect(use_archive=False)
now = datetime.datetime.strptime('2018-02-28 16:54:15',
"%Y-%m-%d %H:%M:%S")
LTPs = m.get_last_LTPs(selection_id=16377754,
amount_of_prices=3,
now=now)
self.assertEqual(len(LTPs), 3)
def lay_saftey_check(selection_id, last_price, current_lay_price, best_back):
""" takes election ID and last scraped LTP as input, returns maximum lay """
m = MongoManager()
ltps = m.get_last_LTPs(selection_id, amount_of_prices=5)
ltps.append(last_price)
log.info("LTPs from db (not used): {}".format(ltps))
try:
# cap the value of the list to 500 and clean ltps from any erroneous/non-numerical value
ltps = [
min(x, 500) for x in ltps
if isinstance(x, numbers.Number) and not np.isnan(x)
]
# take the median
median = np.median(ltps)
except:
log.warning(
"Unable to calculate median from ltps: {}. Assigning a safety threshold"
.format(ltps))
median = 500
last_price_multiplier = config.getfloat("Restrictions",
"last_price_multiplier")
multiple_to_best_competitor = config.getfloat(
"Restrictions", "multiple_to_best_compatitor")
absolute_maximum = config.getfloat("Restrictions", "absolute_maximum")
max_lay = min(current_lay_price, absolute_maximum,
last_price * last_price_multiplier,
best_back * multiple_to_best_competitor)
if max_lay < current_lay_price:
log.warning(
"Restrict lay from {0} to {1}. | LTPs: {2} | best back: {3}".
format(current_lay_price, max_lay, ltps, best_back))
log.info(
"current_lay_price (back level n for replacing_unfilled): {}".format(
current_lay_price))
log.info("LTP median (not used): {}".format(median))
log.info("Last price (ltp or back): {}".format(last_price))
log.info("best back (=best competitor): {}".format(best_back))
return max_lay