def test_overlapping_full_detailed_tca_calculation():
"""Tests a detailed TCA calculation works with caching and overlapping dates, checking that it has the right tables returned.
"""
logger = LoggerManager.getLogger(__name__)
tca_request = TCARequest(start_date=start_date, finish_date=finish_date, ticker=ticker,
tca_type='detailed',
trade_data_store=trade_data_store,
market_data_store=market_data_store,
trade_order_mapping=trade_order_mapping, use_multithreading=True)
tca_engine = TCAEngineImpl(version=tcapy_version)
dict_of_df = tca_engine.calculate_tca(tca_request=tca_request)
sparse_market_trade_df = dict_of_df['sparse_market_' + trade_df_name]
logger.info("Running second TCA calculation, extending dates...")
# Extend sample
tca_request.start_date = pd.Timestamp(start_date) - timedelta(days=10)
dict_of_df = tca_engine.calculate_tca(tca_request=tca_request)
sparse_market_trade_df = dict_of_df['sparse_market_' + trade_df_name]
assert len(sparse_market_trade_df.index[sparse_market_trade_df.index < '01 Feb 2018']) > 0
def test_overlapping_full_detailed_tca_calculation():
"""Tests a detailed TCA calculation works with caching and overlapping dates, checking that it has the right tables returned.
"""
tca_request = TCARequest(start_date=start_date, finish_date=finish_date, ticker=ticker,
tca_type='detailed',
trade_data_store=trade_data_store,
trade_data_database_name=trade_data_database_name,
market_data_store=market_data_store,
market_data_database_table=market_data_database_table,
trade_order_mapping=trade_order_mapping, use_multithreading=use_multithreading)
tca_engine = TCAEngineImpl(version=tcapy_version)
# Extend sample
tca_request.start_date = pd.Timestamp(start_date) - timedelta(days=10)
dict_of_df = tca_engine.calculate_tca(tca_request=tca_request)
sparse_market_trade_df = dict_of_df['sparse_market_trade_df']
assert len(sparse_market_trade_df.index[sparse_market_trade_df.index < '01 Jun 2017']) > 0
def _split_tca_request_by_date(self,
tca_request,
tick,
split_dates=True,
period='month'):
tca_request_list = []
dates = []
# Break up dates into day/week/month chunks - our cache works on day/week/month chunks (can specify in constants)
# Typically day chunks seem optimal
# Careful to floor dates for midnight for caching purposes
if split_dates:
if period == 'month':
split_dates_freq = 'MS'
elif period == 'week':
split_dates_freq = 'W-MON'
elif period == 'day':
split_dates_freq = 'D'
start_date_floored = self._util_func.floor_tick_of_date(
tca_request.start_date)
finish_date_floored = self._util_func.floor_tick_of_date(
tca_request.finish_date, add_day=True)
dates = pd.date_range(start=start_date_floored,
end=finish_date_floored,
freq=split_dates_freq).tolist()
# Add start date and finish date if necessary
# if len(dates) > 0:
# if start_date_floored < dates[0]:
# dates.insert(0, start_date_floored)
#
# if finish_date_floored > dates[-1]:
# dates.append(finish_date_floored)
# else:
# dates = [start_date_floored, finish_date_floored]
logger = LoggerManager().getLogger(__name__)
# If our start/finish date ends up being more than a month
# eg. Jan 8th - Mar 7th - split into
# Jan 8th - Jan 31st 23:59:59.999, Feb 1st 00:00:00.000 - Feb 28th 23:59:59.999 etc
if len(dates) > 0:
# For the very first chunk in our series
if tca_request.start_date < dates[0]:
tca_request_temp = TCARequest(tca_request=tca_request)
tca_request_temp.ticker = tick
tca_request_temp.start_date = tca_request.start_date
tca_request_temp.finish_date = dates[0] - timedelta(
microseconds=1)
tca_request_list.append(tca_request_temp)
# For full months in between during our request
for i in range(0, len(dates) - 1):
tca_request_temp = TCARequest(tca_request=tca_request)
tca_request_temp.ticker = tick
tca_request_temp.start_date = dates[i]
tca_request_temp.finish_date = dates[i + 1] - timedelta(
microseconds=1)
tca_request_list.append(tca_request_temp)
# For the very last chunk of our series
if dates[-1] < tca_request.finish_date:
tca_request_temp = TCARequest(tca_request=tca_request)
tca_request_temp.ticker = tick
tca_request_temp.start_date = dates[-1]
tca_request_temp.finish_date = tca_request.finish_date
tca_request_list.append(tca_request_temp)
else:
tca_request_temp = TCARequest(tca_request=tca_request)
tca_request_temp.ticker = tick
tca_request_list.append(tca_request_temp)
date_str = ''
for t in tca_request_list:
date_str = date_str + ' / ' + str(t.start_date) + ' to ' + str(
t.finish_date)
logger.debug("Split TCA request for " + str(tca_request.ticker) +
" dates " + date_str + " from original request " +
str(tca_request.start_date) + ' to ' +
str(tca_request.finish_date))
return tca_request_list
