/
middleware.py
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/
middleware.py
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import os
import logging
from collections import defaultdict
from betfairlightweight.resources.bettingresources import RunnerBook
from ..order.order import OrderStatus, OrderTypes
from ..utils import wap, call_strategy_error_handling
from ..streams.historicalstream import (
HistoricListener,
FlumineHistoricalGeneratorStream,
)
from .. import config
logger = logging.getLogger(__name__)
WIN_MINIMUM_ADJUSTMENT_FACTOR = 2.5
PLACE_MINIMUM_ADJUSTMENT_FACTOR = 0 # todo implement correctly (https://en-betfair.custhelp.com/app/answers/detail/a_id/406)
LIVE_STATUS = [
OrderStatus.EXECUTABLE,
OrderStatus.CANCELLING,
OrderStatus.UPDATING,
OrderStatus.REPLACING,
]
class Middleware:
def __call__(self, market) -> None:
pass
def add_market(self, market) -> None:
pass
def remove_market(self, market) -> None:
pass
class SimulatedMiddleware(Middleware):
"""
Calculates matched amounts per runner
to be used in simulated matching.
# todo currency fluctuations fucks everything
"""
def __init__(self):
# {marketId: {(selectionId, handicap): RunnerAnalytics}}
self.markets = defaultdict(dict)
self._runner_removals = []
def __call__(self, market) -> None:
market_analytics = self.markets[market.market_id]
runner_removals = [] # [(selectionId, handicap, adjustmentFactor)..]
for runner in market.market_book.runners:
if runner.status == "ACTIVE":
self._process_runner(market_analytics, runner)
elif runner.status == "REMOVED":
_removal = (
runner.selection_id,
runner.handicap,
runner.adjustment_factor,
)
if _removal not in self._runner_removals:
logger.warning(
"Runner %s (%s) removed from market %s",
runner.selection_id,
runner.adjustment_factor,
market.market_id,
)
self._runner_removals.append(_removal)
runner_removals.append(_removal)
for _removal in runner_removals:
self._process_runner_removal(market, *_removal)
market.context["simulated"] = market_analytics
# process simulated orders
if market.blotter.active:
self._process_simulated_orders(market, market_analytics)
def remove_market(self, market) -> None:
try:
del self.markets[market.market_id]
except KeyError:
pass
def _process_runner_removal(
self,
market,
removal_selection_id: int,
removal_handicap: int,
removal_adjustment_factor: float,
) -> None:
for order in market.blotter:
if order.simulated:
if order.lookup == (
market.market_id,
removal_selection_id,
removal_handicap,
):
# cancel and void order
order.simulated.size_matched = 0
order.simulated.average_price_matched = 0
order.simulated.matched = []
if order.order_type.ORDER_TYPE == OrderTypes.LIMIT:
order.simulated.size_voided = order.order_type.size
else:
order.simulated.size_voided = order.order_type.liability
logger.warning(
"Order voided on non runner %s",
order.selection_id,
extra=order.info,
)
else:
# TODO: "Where an SP lay bet in a win market has a maximum odds limit specified,..."
if (
order.order_type.ORDER_TYPE == OrderTypes.MARKET_ON_CLOSE
) and order.side == "LAY":
if market.market_type == "WIN":
runner = [
x
for x in market.market_book.runners
if x.selection_id == order.selection_id
and x.handicap == order.handicap
][0]
runner_adjustment_factor = runner.adjustment_factor
# See https://github.com/betcode-org/flumine/issues/454
multiplier = 1 - (
removal_adjustment_factor
/ (100 - runner_adjustment_factor)
)
order.order_type.liability *= multiplier
if order.average_price_matched:
# We will get here if the NR is declared inplay
order.current_order.size_matched = round(
order.order_type.liability
/ (order.average_price_matched - 1),
2,
)
logger.warning(
"WIN MARKET_ON_CLOSE Order adjusted due to non runner %s",
order.selection_id,
extra=order.info,
)
elif market.market_type in {"PLACE", "OTHER_PLACE"}:
multiplier = (100 - removal_adjustment_factor) * 0.01
order.order_type.liability *= multiplier
if order.average_price_matched:
# We will get here if the NR is declared inplay
order.current_order.size_matched = round(
order.order_type.liability
/ (order.average_price_matched - 1),
2,
)
logger.warning(
"PLACE MARKET_ON_CLOSE Order adjusted due to non runner %s",
order.selection_id,
extra=order.info,
)
elif (
removal_adjustment_factor
and removal_adjustment_factor >= WIN_MINIMUM_ADJUSTMENT_FACTOR
):
# todo place market
for match in order.simulated.matched:
match[1] = self._calculate_reduction_factor(
match[1], removal_adjustment_factor
)
_, order.simulated.average_price_matched = wap(
order.simulated.matched
)
logger.warning(
"Order adjusted due to non runner %s",
order.selection_id,
extra=order.info,
)
@staticmethod
def _calculate_reduction_factor(price: float, adjustment_factor: float) -> float:
price_adjusted = round(price * (1 - (adjustment_factor / 100)), 2)
return max(price_adjusted, 1.01) # min: 1.01
def _process_simulated_orders(self, market, market_analytics: dict) -> None:
"""
#538 smart matching
- isolation per order
Potential double counting of passive liquidity, old logic no longer implemented
- isolation per strategy (default)
Prevent double counting of passive liquidity per strategy
- isolation per instance
Prevent double counting of passive liquidity on all orders regardless of strategy (interaction across strategies)
"""
# isolation per strategy (default)
if config.simulated_strategy_isolation:
for strategy, orders in market.blotter._strategy_orders.items():
live_orders = [
o for o in orders if o.status in LIVE_STATUS and o.simulated
]
if live_orders:
_lookup = {
k: (v.runner, v.traded.copy())
for k, v in market_analytics.items()
}
live_orders_sorted = self._sort_orders(live_orders)
for order in live_orders_sorted:
runner_traded = _lookup[(order.selection_id, order.handicap)]
order.simulated(market.market_book, runner_traded)
else: # isolation per instance
live_orders = list(market.blotter.live_orders)
if live_orders:
_lookup = {
k: (v.runner, v.traded.copy()) for k, v in market_analytics.items()
}
live_orders_sorted = self._sort_orders(live_orders)
for order in live_orders_sorted:
if order.status in LIVE_STATUS and order.simulated:
runner_traded = _lookup[(order.selection_id, order.handicap)]
order.simulated(market.market_book, runner_traded)
@staticmethod
def _sort_orders(orders: list) -> list:
# order by betId (default), side (Lay,Back) and then price
lay_orders = sorted(
[
o
for o in orders
if o.side == "LAY"
and o.order_type.ORDER_TYPE != OrderTypes.MARKET_ON_CLOSE
],
key=lambda x: -x.order_type.price,
)
back_orders = sorted(
[
o
for o in orders
if o.side == "BACK"
and o.order_type.ORDER_TYPE != OrderTypes.MARKET_ON_CLOSE
],
key=lambda x: x.order_type.price,
)
moc = [
o for o in orders if o.order_type.ORDER_TYPE == OrderTypes.MARKET_ON_CLOSE
]
return lay_orders + back_orders + moc
@staticmethod
def _process_runner(market_analytics: dict, runner: RunnerBook) -> None:
try:
runner_analytics = market_analytics[(runner.selection_id, runner.handicap)]
except KeyError:
runner_analytics = market_analytics[
(runner.selection_id, runner.handicap)
] = RunnerAnalytics(runner)
runner_analytics(runner)
class RunnerAnalytics:
def __init__(self, runner: RunnerBook):
self.runner = runner
self.traded = {} # price: size traded since last update
self._traded_volume = runner.ex.traded_volume
self._p_v = {
i["price"]: i["size"] for i in runner.ex.traded_volume
} # cached current volume
def __call__(self, runner: RunnerBook):
_tv = runner.ex.traded_volume
if self._traded_volume == _tv:
self.traded = {}
else:
self.traded = self._calculate_traded(_tv)
self._traded_volume = _tv
self.runner = runner
def _calculate_traded(self, traded_volume: list) -> dict:
p_v, traded = self._p_v, {}
# create dictionary
c_v = {i["price"]: i["size"] for i in traded_volume}
# calculate difference
for key, value in c_v.items():
if key in p_v:
new_value = float(value) - float(p_v[key])
if new_value > 0:
traded[key] = round(new_value, 2)
else:
traded[key] = value
# cache for next update
self._p_v = c_v
return traded
class SimulatedSportsDataMiddleware(Middleware):
"""
Middleware to allow simulation of historic
sports data.
Creates generator of sports data that is cycled
chronologically with the MarketBooks calling
`strategy.process_sports_data`
"""
def __init__(self, operation: str, directory: str):
self.operation = operation # "cricketSubscription" or "raceSubscription"
self.directory = directory # sports data directory (marketId used for lookup)
self._gen = None
self._next = None
def __call__(self, market) -> None:
pt = market.market_book.publish_time_epoch
while True:
if self._next is None:
break
for update in self._next:
if update.market_id != market.market_id:
continue
if pt > update.publish_time_epoch:
for strategy in market.flumine.strategies:
if (
market.market_book.streaming_unique_id
in strategy.stream_ids
):
if call_strategy_error_handling(
strategy.check_sports_data, market, update
):
call_strategy_error_handling(
strategy.process_sports_data, market, update
)
else:
return
try:
self._next = next(self._gen)
except StopIteration:
break
def add_market(self, market) -> None:
# create sports data generator
file_path = os.path.join(self.directory, market.market_id)
self._gen = self._create_generator(file_path, self.operation, 123)()
try:
self._next = next(self._gen)
except StopIteration:
logger.error(
f"File {market.market_id} cannot be processed (data is not valid)"
)
self._next = None
def remove_market(self, market) -> None:
# clear gens
self._gen = None
self._next = None
@staticmethod
def _create_generator(file_path: str, operation: str, unique_id: int):
listener = HistoricListener(max_latency=None, update_clk=False)
stream = FlumineHistoricalGeneratorStream(
file_path=file_path,
listener=listener,
operation=operation,
unique_id=unique_id,
)
return stream.get_generator()