def get_mkr_eth_prices(self, takes):
takes_1 = filter(lambda log_take: log_take.buy_token == self.mkr_address and log_take.pay_token == self.weth_address, takes)
takes_2 = filter(lambda log_take: log_take.buy_token == self.weth_address and log_take.pay_token == self.mkr_address, takes)
prices_mkr_eth = list(map(lambda log_take: Price(timestamp=log_take.timestamp,
price=float(log_take.take_amount / log_take.give_amount),
buy_price=None,
sell_price=None,
volume=float(log_take.give_amount)), takes_1)) \
+ list(map(lambda log_take: Price(timestamp=log_take.timestamp,
price=float(log_take.give_amount / log_take.take_amount),
buy_price=None,
sell_price=None,
volume=float(log_take.take_amount)), takes_2))
return prices_mkr_eth
def prepare_prices_for_charting(prices: List[Price],
price_gap_size: int) -> List[Price]:
if len(prices) == 0:
return prices
result = [prices[0]]
for i in range(1, len(prices)):
if prices[i].timestamp - prices[i - 1].timestamp > price_gap_size:
result.append(
Price(prices[i - 1].timestamp + 1, None, None, None, None))
result.append(prices[i])
return result
def convert_prices(self, source: List[Price], target: List[Price], operator):
result = []
for price in source:
matching_target = next(filter(lambda target_price: target_price.timestamp >= price.timestamp, target), None)
if matching_target is not None:
result.append(Price(timestamp=price.timestamp,
price=operator(price.price, matching_target.price),
buy_price=None,
sell_price=None,
volume=price.volume))
else:
logging.warning(f"No matching price found at {price.timestamp}")
return result
def test_granularize_prices_fills_gaps():
# given
# 1518440700 = 2018-02-12 13:05:00 UTC
prices = [Price(1518440700, 1.5, None, None, 10),
Price(1518440760, 1.7, None, None, 14),
Price(1518440880, 1.2, None, None, 18)]
# when
granularized_prices = granularize_prices(prices)
# then
assert granularized_prices == [Price(1518440700, 1.5, None, None, 10),
Price(1518440760, 1.7, None, None, 14),
Price(1518440820, 0, 0, 0, 0),
Price(1518440880, 1.2, None, None, 18)]
def test_granularize_prices_fills_gaps_even_if_seconds_are_uneven():
# given
# 1518440700 = 2018-02-12 13:05:00 UTC
prices = [Price(1518440759, 1.5, None, None, 10),
Price(1518440760, 1.7, None, None, 14),
Price(1518440851, 1.2, None, None, 18)]
# when
granularized_prices = granularize_prices(prices)
# then
assert granularized_prices == [Price(1518440759, 1.5, None, None, 10),
Price(1518440760, 1.7, None, None, 14),
Price(1518440851, 1.2, None, None, 18)]
def granularize_prices(prices: list) -> list:
def get_minute(ts):
return int(ts / 60)
granular_prices = []
last_timestamp = -1
for price in prices:
if last_timestamp != -1:
minute_increment = get_minute(
price.timestamp) - get_minute(last_timestamp)
for i in range(0, minute_increment - 1):
granular_prices.append(
Price(last_timestamp + 60 * (i + 1), 0.0, 0.0, 0.0, 0.0))
if minute_increment > 0:
granular_prices.append(price)
else:
granular_prices.append(price)
last_timestamp = price.timestamp
return granular_prices
def test_granularize_prices_removes_duplicates():
# given
# 1518440700 = 2018-02-12 13:05:00 UTC
prices = [Price(1518440700, 1.5, None, None, 10),
Price(1518440730, 1.51, None, None, 11),
Price(1518440740, 1.52, None, None, 12),
Price(1518440759, 1.53, None, None, 13),
Price(1518440760, 1.7, None, None, 14),
Price(1518440885, 1.2, None, None, 18),
Price(1518440910, 1.1, None, None, 29),]
# when
granularized_prices = granularize_prices(prices)
# then
assert granularized_prices == [Price(1518440700, 1.5, None, None, 10),
Price(1518440760, 1.7, None, None, 14),
Price(1518440820, 0, 0, 0, 0),
Price(1518440885, 1.2, None, None, 18)]