def __get_log_entry_numbers_for_log_type__(self,
log_type: str,
actual_day=True):
today_str = MyDate.get_date_as_string_from_date_time()
if log_type not in self._log_data_frame_dict:
return 0
df = self._log_data_frame_dict[log_type]
if actual_day:
if DC.WAVE_END_TS in df.columns:
today_ts = MyDate.get_epoch_seconds_for_date(
) - MyDate.get_seconds_for_period(days=1) # minus one day
df = df[df[DC.WAVE_END_TS] >= today_ts]
# print('max ts = {}, midnight={}'.format(df[DC.WAVE_END_TS].max(), today_ts)
elif DC.TS_PATTERN_TICK_LAST in df.columns:
today_ts = MyDate.get_epoch_seconds_for_date(
) - MyDate.get_seconds_for_period(days=1) # minus one day
df = df[df[DC.TS_PATTERN_TICK_LAST] >= today_ts]
elif PRDC.START_DT in df.columns:
df = df[df[PRDC.START_DT] == today_str]
elif LOGDC.DATE in df.columns:
df = df[df[LOGDC.DATE] == today_str]
if log_type == LOGT.TRADES:
add_number = df[df[LOGDC.PROCESS_STEP] == 'Add'].shape[0]
buy_number = df[df[LOGDC.PROCESS_STEP] == 'Buy'].shape[0]
return '{}/{}'.format(add_number, buy_number)
return df.shape[0]
def __adjust_log_df_to_selected_items__(self):
if self._process_column != '' and self._selected_log_process != '':
self._log_df = self._log_df[self._log_df[self._process_column] ==
self._selected_log_process]
if self._process_step_column != '' and self._selected_log_process_step != '':
self._log_df = self._log_df[self._log_df[self._process_step_column]
== self._selected_log_process_step]
if self._selected_date_range == DTRG.TODAY:
if self._date_column == DC.WAVE_END_TS:
offset_ts = MyDate.get_epoch_seconds_for_date(
) - MyDate.get_seconds_for_period(days=2) # minus 2 day
self._log_df = self._log_df[
self._log_df[self._date_column] >= offset_ts]
elif self._date_column == DC.TS_PATTERN_TICK_LAST:
offset_ts = MyDate.get_epoch_seconds_for_date(
) - MyDate.get_seconds_for_period(days=2) # minus 2 day
self._log_df = self._log_df[
self._log_df[self._date_column] >= offset_ts]
else:
today_str = MyDate.get_date_as_string_from_date_time()
self._log_df = self._log_df[self._log_df[self._date_column] ==
today_str]
def __adjust_log_df_to_selected_items__(self):
if self._process_column != '' and self._selected_log_process != '':
self._log_df = self._log_df[self._log_df[self._process_column] ==
self._selected_log_process]
if self._process_step_column != '' and self._selected_log_process_step != '':
self._log_df = self._log_df[self._log_df[self._process_step_column]
== self._selected_log_process_step]
if self._selected_date_range == DTRG.TODAY:
if self._date_column == DC.WAVE_END_TS:
offset_ts = MyDate.get_epoch_seconds_for_date(
) - 60 * 60 * 24 * 2 # minus 2 day...
self._log_df = self._log_df[
self._log_df[self._date_column] >= offset_ts]
else:
today_str = MyDate.get_date_as_string_from_date_time()
self._log_df = self._log_df[self._log_df[self._date_column] ==
today_str]