def import_archived_analysis2(csvfile, year):
msgerror = "Failure importing archived Analysis 2. Error:"
try:
validate_year_for_archiving(year)
except ArchiveYearError as ex:
raise ArchiveYearError(f"{msgerror} {str(ex)}")
success, msg = import_obj(csvfile, ANALYSIS2_HISTORICAL_KEY, year=year)
if not success:
raise WrongChartOFAccountCodeException(f"{msgerror} {msg}")
return success, msg
def import_archived_programme(csvfile, year):
msgerror = "Failure importing archived Programme. Error:"
try:
validate_year_for_archiving(year)
except ArchiveYearError as ex:
raise ArchiveYearError(f"{msgerror} {str(ex)}")
success, msg = import_obj(csvfile, PROGRAMME_HISTORICAL_KEY, year=year)
if not success:
raise WrongChartOFAccountCodeException(f"{msgerror} {msg}")
return success, msg
def import_archived_cost_centre(csvfile, year):
try:
validate_year_for_archiving(year)
except ArchiveYearError as ex:
raise ArchiveYearError(
f"Failure import Importing archived Cost Centre hierarchy error: {str(ex)}"
)
success, msg = import_obj(csvfile, COST_CENTRE_HISTORICAL_KEY, year=year)
if not success:
raise WrongChartOFAccountCodeException(
f"Importing archived Cost Centre hierarchy error: "
f"{msg}")
return success, msg
def import_archived_nac(csvfile, year):
msgerror = "Failure importing archived NAC. Error:"
try:
validate_year_for_archiving(year)
except ArchiveYearError as ex:
raise ArchiveYearError(f"{msgerror} {str(ex)}")
success, msg = import_obj(csvfile, NAC_HISTORICAL_KEY, year=year)
if not success:
raise WrongChartOFAccountCodeException(f"{msgerror} {msg}")
else:
# The archived NAC is not normalised, and each expenditure NAC row
# contains the corresponding budget NAC.
# This information is missing from the upload file, so we need to extract it
# from the expenditure category: each expenditure category row is linked to
# a budget NAC.
# The classification of budget and expenditure NAC is internal to DIT:
# budgets should be set only using budget NAC, to reduce the number of lines
nac_qs = ArchivedNaturalCode.objects.filter(financial_year=year)
for nac_obj in nac_qs:
if nac_obj.expenditure_category:
account_L6_budget_val = nac_obj.expenditure_category.linked_budget_code
nac_obj.account_L6_budget = account_L6_budget_val
nac_obj.save()
category_qs = ArchivedExpenditureCategory.objects.filter(financial_year=year)
for category_obj in category_qs:
account_L6_budget_val = category_obj.linked_budget_code
try:
nac_obj = ArchivedNaturalCode.objects.get(
financial_year=year, natural_account_code=account_L6_budget_val
)
nac_obj.used_for_budget = True
nac_obj.save()
except ObjectDoesNotExist:
msg = f"NAC {account_L6_budget_val} not defined for year {year}"
raise WrongChartOFAccountCodeException(f"{msgerror} {msg}")
return success, msg
def import_single_archived_period(csvfile, month_to_upload, archive_period,
fin_year):
if month_to_upload <= archive_period:
raise WrongArchivePeriodException(
"You are trying to amend Actuals. Only forecast can be amended.")
end_of_month_info = EndOfMonthStatus.objects.get(
archived_period__financial_period_code=archive_period)
if not end_of_month_info.archived:
raise WrongArchivePeriodException(
f"There is no archive for period {archive_period} ")
period_obj = FinancialPeriod.objects.get(pk=month_to_upload)
archive_period_id = end_of_month_info.id
ActualUploadMonthlyFigure.objects.filter(
financial_year=fin_year, financial_period=period_obj).delete()
reader = csv.reader(csvfile)
col_key = csv_header_to_dict(next(reader))
row_number = 1
fin_obj, msg = get_fk(FinancialYear, fin_year)
period_obj = FinancialPeriod.objects.get(pk=month_to_upload)
month_col = col_key[period_obj.period_short_name.lower()]
check_financial_code = CheckFinancialCode(None)
csv_reader = csv.reader(csvfile, delimiter=",", quotechar='"')
for row in csv_reader:
row_number += 1
# protection against empty rows
if len(row) == 0:
break
cost_centre = row[col_key["cost centre"]].strip()
programme_code = row[col_key["programme"]].strip()
nac = row[col_key["natural account"]].strip()
analysis1 = row[col_key["analysis"]].strip()
analysis2 = row[col_key["analysis2"]].strip()
project_code = row[col_key["project"]].strip()
check_financial_code.validate(
cost_centre,
nac,
programme_code,
analysis1,
analysis2,
project_code,
row_number,
)
if check_financial_code.error_found or check_financial_code.ignore_row:
raise WrongChartOFAccountCodeException(
f"Overwriting period, Row {row_number} error: "
f"{check_financial_code.display_error}")
financialcode_obj = check_financial_code.get_financial_code()
period_amount = Decimal(row[month_col])
if period_amount:
month_figure_obj, created = ActualUploadMonthlyFigure.objects.get_or_create(
financial_year=fin_obj,
financial_period=period_obj,
financial_code=financialcode_obj,
)
if created:
month_figure_obj.amount = period_amount * 100
else:
month_figure_obj.amount += period_amount * 100
month_figure_obj.current_amount = month_figure_obj.amount
month_figure_obj.save()
if (row_number % 100) == 0:
logger.info(row_number)
logger.info(f"Completed processing {row_number} rows.")
# Now copy the newly uploaded figures to the monthly figure table
ForecastMonthlyFigure.objects.filter(
financial_year=fin_year,
financial_period=period_obj,
archived_status_id=archive_period_id,
).delete()
sql_insert = sql_for_single_month_copy(month_to_upload, archive_period_id,
fin_year)
with connection.cursor() as cursor:
cursor.execute(sql_insert)
ForecastMonthlyFigure.objects.filter(
financial_year=fin_year,
financial_period=period_obj,
amount=0,
starting_amount=0,
archived_status_id=archive_period_id,
).delete()
ActualUploadMonthlyFigure.objects.filter(
financial_year=fin_year, financial_period=period_obj).delete()