def trades_info(
data=arg_not_supplied,
calendar_days_back=1,
end_date=arg_not_supplied,
start_date=arg_not_supplied,
):
"""
Report on system status
:param: data blob
:return: list of formatted output items
"""
if data is arg_not_supplied:
data = dataBlob()
if end_date is arg_not_supplied:
end_date = datetime.datetime.now()
if start_date is arg_not_supplied:
start_date = n_days_ago(calendar_days_back, date_ref=start_date)
results_object = get_trades_report_data(data,
start_date=start_date,
end_date=end_date)
formatted_output = format_trades_data(results_object)
return formatted_output
def get_report_dates():
end_date = arg_not_supplied
start_date = arg_not_supplied
start_period = arg_not_supplied
end_period = arg_not_supplied
input_end_date = get_datetime_input("End date for report?\n",
allow_default=True,
allow_period=True,
allow_calendar_days=True)
if type(input_end_date) is int:
## calendar days
end_date = n_days_ago(input_end_date, datetime.datetime.now())
elif type(input_end_date) is str:
## period
end_period = input_end_date
elif type(input_end_date) is datetime.datetime:
end_date = input_end_date
else:
raise Exception("Don't recognise %s" % str(input_end_date))
input_start_date = get_datetime_input("Start date for report? \n",
allow_default=False,
allow_period=True,
allow_calendar_days=True)
if type(input_start_date) is int:
## calendar days
start_date = n_days_ago(input_start_date, end_date)
elif type(input_start_date) is str:
## period
start_period = input_start_date
elif type(input_start_date) is datetime.datetime:
start_date = input_start_date
else:
raise Exception("Don't recognise %s" % str(input_start_date))
start_date, end_date = calculate_start_and_end_dates(
calendar_days_back=arg_not_supplied,
end_date=end_date,
start_date=start_date,
start_period=start_period,
end_period=end_period)
return start_date, end_date
def _calculate_start_date(self) -> datetime.datetime:
start_date = self._passed_start_date
if start_date is arg_not_supplied:
calendar_days_back = self._calendar_days_back
end_date = self.end_date
start_date = n_days_ago(calendar_days_back, date_ref=end_date)
return start_date
def recent_average_price(data: dataBlob, instrument_code: str) -> float:
diag_prices = diagPrices(data)
prices = diag_prices.get_adjusted_prices(instrument_code)
if len(prices) == 0:
return np.nan
one_year_ago = n_days_ago(365)
recent_prices = prices[one_year_ago:]
return recent_prices.mean(skipna=True)
def costs_report(data: dataBlob = arg_not_supplied,
calendar_days_back: int = 250,
end_date: datetime.datetime = arg_not_supplied,
start_date: datetime.datetime = arg_not_supplied):
if data is arg_not_supplied:
data = dataBlob()
if end_date is arg_not_supplied:
end_date = datetime.datetime.now()
if start_date is arg_not_supplied:
start_date = n_days_ago(calendar_days_back, date_ref=end_date)
costs_report_data = get_costs_report_data(data,
start_date=start_date,
end_date=end_date)
formatted_output = format_costs_data(costs_report_data)
return formatted_output
def average_spread_last_n_days(self, n_days: int = 14):
recent_data = self[n_days_ago(n_days)]
if len(recent_data) == 0:
return missing_data
return recent_data.mean(skipna=True)