def process_balance(self, timestamp, prices):
try:
metrics = []
values = self.__context.fetch_balances(timestamp)
for dto in values if values is not None else []:
amount = dto.balance.bc_amnt
rate = self._calculate_evaluation(dto.evaluation, prices)
if dto.account is None or amount is None or rate is None:
continue
metric = Metric()
metric.mc_type = 'balance'
metric.mc_name = dto.account.ac_disp
metric.mc_time = timestamp
metric.mc_amnt = amount * rate
metrics.append(metric)
self.__context.save_metrics(metrics)
except BaseException as e:
self.__logger.warn('Balance : %s : %s', type(e), e.args)
def _convert_ticker(self, timestamp, prices, dto):
threshold_minutes = self.__context.get_property(self._ID, 'ticker_threshold', 3)
threshold_cutoff = timestamp - timedelta(minutes=int(threshold_minutes))
if dto.ticker.tk_time.replace(tzinfo=threshold_cutoff.tzinfo) < threshold_cutoff:
return None
price = prices.get(dto.ticker.tk_site, {}).get(dto.ticker.tk_code)
if price is None or price == self._ZERO or dto.product is None:
return None
expiry = dto.product.pr_expr
if expiry is not None and expiry.astimezone(timestamp.tzinfo) < timestamp:
return None
rate = self._calculate_evaluation(dto.fund, prices)
if rate is None:
return None
metric = Metric()
metric.mc_type = 'ticker'
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = price * rate
return metric
def test_save_metrics(self):
self.target._create_all()
dt = datetime.now()
m1 = Metric()
m1.mc_type = 't1'
m1.mc_time = dt + timedelta(minutes=1)
m1.mc_name = 'n1'
m1.mc_amnt = Decimal('1.2')
m2 = Metric()
m2.mc_type = 't2'
m2.mc_time = dt + timedelta(minutes=2)
m2.mc_name = 'n2'
m2.mc_amnt = Decimal('2.3')
m3 = copy(m1)
m3.mc_amnt = Decimal('3.4')
m4 = copy(m2)
m4.mc_amnt = Decimal('4.5')
m5 = copy(m1)
m5.mc_name = None
# All new records
results = self.target.save_metrics([m1, m2])
self.assertEqual(len(results), 2)
self.assertTrue(m1 in results)
self.assertTrue(m2 in results)
# Existing records
results = self.target.save_metrics([m3, None, m4])
self.assertEqual(len(results), 2)
self.assertTrue(m3 in results)
self.assertTrue(m4 in results)
# PK Failure
with self.assertRaises(BaseException):
self.target.save_metrics([m5])
# Read-only
self.target._is_read_only = lambda: True
results = self.target.save_metrics([m1])
self.assertEqual(len(results), 0)
def process_position(self, timestamp, prices):
try:
metrics = []
values = self.__context.fetch_positions(timestamp)
for dto in values if values is not None else []:
amount = dto.position.ps_fund
rate = self._calculate_evaluation(dto.fund, prices)
if dto.product is None or amount is None or rate is None:
continue
metric = Metric()
metric.mc_type = 'position@upl'
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = amount * rate
metrics.append(metric)
for dto in values if values is not None else []:
amount = dto.position.ps_inst
rate = self._calculate_evaluation(dto.inst, prices)
if dto.product is None or amount is None or rate is None:
continue
metric = Metric()
metric.mc_type = 'position@qty'
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = amount * rate
metrics.append(metric)
self.__context.save_metrics(metrics)
except BaseException as e:
self.__logger.warn('Position : %s : %s', type(e), e.args)
def test_Metric(self):
value = Metric()
self.assertEqual("{'table': 't_metric', 'type': 'None', "
"'time': 'None', 'name': 'None', 'amnt': 'None'}", str(value))
value.mc_type = 'foo'
value.mc_time = datetime.fromtimestamp(1234567890.123456, tz=utc)
value.mc_name = 'bar'
value.mc_amnt = Decimal('1.2')
self.assertEqual("{'table': 't_metric', 'type': 'foo', "
"'time': '2009-02-13 23:31:30.123456 UTC', 'name': 'bar', 'amnt': '1.2'}", str(value))
def process_transaction_trade(self, timestamp, prices):
try:
metrics = []
offset = timedelta(minutes=int(
self.__context.get_property(self._ID, 'offset', 9 * 60)))
t = timestamp + offset
windows = {
'DAY':
t.replace(microsecond=0, second=0, minute=0, hour=0) - offset,
'MTD':
t.replace(microsecond=0, second=0, minute=0, hour=0, day=1) -
offset,
'YTD':
t.replace(
microsecond=0, second=0, minute=0, hour=0, day=1, month=1)
- offset,
}
for key, val in windows.items():
values = self.__context.fetch_transactions(val, timestamp)
for dto in values if values is not None else []:
inst_qty = dto.tx_net_inst
fund_qty = dto.tx_net_fund
inst_rate = self.calculate_evaluation(dto.ev_inst, prices)
fund_rate = self.calculate_evaluation(dto.ev_fund, prices)
if dto.product is None \
or inst_qty is None or fund_qty is None \
or inst_rate is None or fund_rate is None:
continue
metric = Metric()
metric.mc_type = 'trade@' + key
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = (inst_qty * inst_rate) + (fund_qty *
fund_rate)
metrics.append(metric)
self.__context.save_metrics(metrics)
except BaseException as e:
self.__logger.warn('Transaction (trade) : %s : %s', type(e),
e.args)
def process_transaction_volume(self, timestamp, prices):
try:
metrics = []
windows = {
'12H': timestamp - timedelta(hours=12),
'01D': timestamp - timedelta(hours=24),
'30D': timestamp - timedelta(days=30),
}
for key, val in windows.items():
values = self.__context.fetch_transactions(val, timestamp)
for dto in values if values is not None else []:
amount = dto.tx_grs_fund
rate = self.calculate_evaluation(dto.ev_fund, prices)
if dto.product is None or amount is None or rate is None:
continue
metric = Metric()
metric.mc_type = 'volume@' + key
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = amount * rate
metrics.append(metric)
self.__context.save_metrics(metrics)
except BaseException as e:
self.__logger.warn('Transaction (volume) : %s : %s', type(e),
e.args)
def process_ticker(self, timestamp):
prices = None
try:
values = self.__context.fetch_tickers(timestamp,
include_expired=True)
prices = defaultdict(lambda: dict())
for dto in values if values is not None else []:
ticker = dto.ticker
ask = ticker.tk_ask if ticker.tk_ask != self._ZERO else None
bid = ticker.tk_bid if ticker.tk_bid != self._ZERO else None
ltp = ticker.tk_ltp if ticker.tk_ltp != self._ZERO else None
price = None
if ask is not None and bid is not None:
price = (ask + bid) * self._HALF
if price is None:
price = ask
if price is None:
price = bid
if price is None:
price = ltp
prices[ticker.tk_site][ticker.tk_code] = price
metrics = []
threshold_minutes = self.__context.get_property(
self._ID, 'ticker_threshold', 3)
threshold_cutoff = timestamp - timedelta(
minutes=int(threshold_minutes))
for dto in values if values is not None else []:
if dto.ticker.tk_time.replace(
tzinfo=threshold_cutoff.tzinfo) < threshold_cutoff:
continue
price = prices[dto.ticker.tk_site][dto.ticker.tk_code]
if price is None or price == self._ZERO or dto.product is None:
continue
expiry = dto.product.pr_expr
if expiry is not None and expiry.astimezone(
timestamp.tzinfo) < timestamp:
continue
rate = self.calculate_evaluation(dto.fund, prices)
if rate is None:
continue
metric = Metric()
metric.mc_type = 'ticker'
metric.mc_name = dto.product.pr_disp
metric.mc_time = timestamp
metric.mc_amnt = price * rate
metrics.append(metric)
self.__context.save_metrics(metrics)
except BaseException as e:
self.__logger.warn('Ticker : %s : %s', type(e), e.args)
return prices