def import_done_trades_data(uid: long):
DoneTrade.objects(user_id=uid).delete()
dt = DoneTrade()
dt.drop_collection()
dt.user_id = uid
dt.calculation_start_date = datetime.now()
dt.timely_trades_count_of_last_3_months = 1
dt.timely_trades_count_between_last_3_to_12_months = 0
dt.past_due_trades_count_of_last_3_months = 0
dt.past_due_trades_count_between_last_3_to_12_months = 0
dt.arrear_trades_count_of_last_3_months = 0
dt.arrear_trades_count_between_last_3_to_12_months = 0
dt.trades_total_balance = 45000000
dt.total_delay_days = 0
dt.save()
def get_document_by_user_id(doc: object, user_id: bson.ObjectId):
if doc == DoneTrade.__name__:
return DoneTrade.objects(user_id=user_id).first()
def get_done_trades_for_user(user_id: bson.ObjectId) -> DoneTrade:
done_trade = DoneTrade.objects(user_id=user_id).first()
# done_trade = db.doneTrades.find_one({'user_id': 23})
return done_trade
def test_get_bulk_data(self):
done_trades: DoneTrade = DoneTrade.objects(user_id=1).all()
# print(user.to_json())
print("all doneTrades are loaded.")
for dt in done_trades:
print(dt.to_json())
def calculate_user_undone_trades_score_2(
self,
user_id: long,
reset_cache=False,
undone_trade_object: UndoneTrade = None,
done_trade_object: DoneTrade = None):
if undone_trade_object is not None:
undone_trade = undone_trade_object
else:
undone_trade: UndoneTrade = UndoneTrade.objects(
user_id=user_id).first()
if done_trade_object is not None:
done_trade = done_trade_object
else:
done_trade: DoneTrade = DoneTrade.objects(user_id=user_id).first()
rds: RedisCachingRulesUndoneTrades = self.rds.get_redis_caching_rules_undone_trades_service(
reset_cache)
undone_trades_score = 0
normalized_undone_trades_score = 0
score = rds.get_score_of_rules_undone_undue_trades_counts_h10(
undone_trade.undue_trades_count)
# normalized_score = calculate_normalized_score(H10_RULES_UNDONE_UNDUE_TRADES_COUNTS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[HISTORIES_SCORE] = self.scores_dict.get(
HISTORIES_SCORE) + score
print('score= {}, undoneTrades:[undue_trades_count-h10]= {}'.format(
score, undone_trade.undue_trades_count))
# calculate undue_total_balance_ratio
undue_total_balance_ratio = float(
undone_trade.undue_trades_total_balance_of_last_year /
done_trade.trades_total_balance)
score = rds.get_score_of_rules_undone_undue_trades_total_balance_of_last_year_ratios_v15(
undue_total_balance_ratio)
# normalized_score = calculate_normalized_score(V15_RULES_UNDONE_UNDUE_TRADES_TOTAL_BALANCE_OF_LAST_YEAR_RATIOS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[VOLUMES_SCORE] = self.scores_dict.get(
VOLUMES_SCORE) + score
print('score= {}, undoneTrades:[undue_total_balance_ratio-v15]= {}'.
format(score, undue_total_balance_ratio))
score = rds.get_score_of_rules_undone_past_due_trades_counts_t26(
undone_trade.past_due_trades_count)
# normalized_score = calculate_normalized_score(T26_RULES_UNDONE_PAST_DUE_TRADES_COUNTS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[TIMELINESS_SCORE] = self.scores_dict.get(
TIMELINESS_SCORE) + score
print('score= {}, undoneTrades:[past_due_trades_count-t26]= {}'.format(
score, undone_trade.past_due_trades_count))
timely_done_trades_of_last_year = (
done_trade.timely_trades_count_of_last_3_months +
done_trade.timely_trades_count_between_last_3_to_12_months)
# calculate past_due_total_balance_ratio
past_due_total_balance_ratio = float(
undone_trade.past_due_trades_total_balance_of_last_year /
done_trade.trades_total_balance)
score = rds.get_score_of_rules_undone_past_due_trades_total_balance_of_last_year_ratios_v13(
past_due_total_balance_ratio)
score_code = rds.get_code_of_rules_undone_past_due_trades_total_balance_of_last_year_ratios_v13(
past_due_total_balance_ratio)
if timely_done_trades_of_last_year == 1 and score_code == SCORE_CODE_RULES_UNDONE_PAST_DUE_TRADES_TOTAL_BALANCE_OF_LAST_YEAR_RATIOS:
score *= 2
# normalized_score = calculate_normalized_score(V13_RULES_UNDONE_PAST_DUE_TRADES_TOTAL_BALANCE_OF_LAST_YEAR_RATIOS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[VOLUMES_SCORE] = self.scores_dict.get(
VOLUMES_SCORE) + score
print('score= {}, undoneTrades:[past_due_total_balance_ratio-v13]= {}'.
format(score, past_due_total_balance_ratio))
score = rds.get_score_of_rules_undone_arrear_trades_counts_t27(
undone_trade.arrear_trades_count)
# normalized_score = calculate_normalized_score(T27_RULES_UNDONE_ARREAR_TRADES_COUNTS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[TIMELINESS_SCORE] = self.scores_dict.get(
TIMELINESS_SCORE) + score
print('score= {}, undoneTrades:[arrear_trades_count-t27]= {}'.format(
score, undone_trade.arrear_trades_count))
# calculate arrear_total_balance_ratio
arrear_total_balance_ratio = float(
undone_trade.arrear_trades_total_balance_of_last_year /
done_trade.trades_total_balance)
score = rds.get_score_of_rules_undone_arrear_trades_total_balance_of_last_year_ratios_v14(
arrear_total_balance_ratio)
score_code = rds.get_code_of_rules_undone_arrear_trades_total_balance_of_last_year_ratios_v14(
arrear_total_balance_ratio)
if timely_done_trades_of_last_year == 1 and score_code == SCORE_CODE_RULES_UNDONE_ARREAR_TRADES_TOTAL_BALANCE_OF_LAST_YEAR_RATIOS:
score *= 2
# normalized_score = calculate_normalized_score(V14_RULES_UNDONE_ARREAR_TRADES_TOTAL_BALANCE_OF_LAST_YEAR_RATIOS, score)
# normalized_undone_trades_score += normalized_score
undone_trades_score += score
self.scores_dict[VOLUMES_SCORE] = self.scores_dict.get(
VOLUMES_SCORE) + score
print('score= {}, undoneTrades:[arrear_total_balance_ratio-v14]= {}'.
format(score, arrear_total_balance_ratio))
# print('............. undoneTrades_score = {} , normalized_score = {} ................\n'.format(undone_trades_score,
# normalized_undone_trades_score))
print('............. undoneTrades_score = {} ................'.format(
undone_trades_score))
print(
'... IDENTITIES_SCORE= {} , HISTORIES_SCORE= {}, VOLUMES_SCORE= {}, TIMELINESS_SCORE= {} \n'
.format(self.scores_dict.get(IDENTITIES_SCORE),
self.scores_dict.get(HISTORIES_SCORE),
self.scores_dict.get(VOLUMES_SCORE),
self.scores_dict.get(TIMELINESS_SCORE)))
return undone_trades_score