def generate_fake_data(workspace_quantity=10, generate_all_disagg=False):
if not settings.IS_TEST and workspace_quantity < 1:
workspace_quantity = 1
print('Workspace quantity reset to {}'.format(workspace_quantity))
if workspace_quantity >= 5:
workspace_quantity = 5
print('Workspace quantity reset to {}'.format(workspace_quantity))
today = datetime.date.today()
admin_password = '******'
# Cluster admin creation
sys_admin, _ = User.objects.get_or_create(username='******',
defaults={
'email':
'*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Cluster',
'last_name': 'Admin',
})
sys_admin.set_password(admin_password)
sys_admin.save()
# Give Cluster admin role to cluster_admin User
ClusterPRPRoleFactory(
user=sys_admin,
role=PRP_ROLE_TYPES.cluster_system_admin,
workspace=None,
cluster=None,
)
SectionFactory.create_batch(workspace_quantity)
print("{} Section objects created".format(workspace_quantity))
unicef_re = ReportingEntity.objects.get(title="UNICEF")
# cluster_re = ReportingEntity.objects.get(title="Cluster")
ws_list = list()
for i in random.sample(range(0,
len(COUNTRIES_ALPHA2_CODE) - 1),
workspace_quantity):
ws = WorkspaceFactory(title=COUNTRIES_ALPHA2_CODE[i][1],
workspace_code=COUNTRIES_ALPHA2_CODE[i][0])
ws_list.append(ws)
print("{} Workspace created".format(ws))
beginning_of_this_year = datetime.date(today.year, 1, 1)
end_of_this_year = datetime.date(today.year, 12, 31)
for workspace in ws_list:
country = CountryFactory(
country_short_code=workspace.workspace_code,
name=workspace.title,
)
workspace.countries.add(country)
for idx in range(0, 2):
year = today.year - idx
# Using direct ORM due to M2M factory to clusters
ResponsePlan.objects.create(workspace=workspace,
title="{} {} HR".format(
workspace.title, year),
start=beginning_of_this_year,
end=end_of_this_year)
gateways = list()
for idx in range(5):
gateways.append(
GatewayTypeFactory(country=country, admin_level=idx + 1))
carto_db_table = CartoDBTableFactory(location_type=gateways[0],
country=country)
locations = list()
for idx in range(12):
locations.append(
LocationFactory.create(
gateway=gateways[idx] if idx < 5 else gateways[4],
parent=None if idx == 0 else
(locations[idx - 1] if idx < 6 else locations[4]),
carto_db_table=carto_db_table,
p_code=generate_random_character_sequence() + "-" +
str(idx)))
print("{} ResponsePlan objects created for {}".format(3, workspace))
# Cluster IMO creation
imo, _ = User.objects.get_or_create(username='******',
defaults={
'email': '*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Cluster',
'last_name': 'IMO',
})
imo.set_password(admin_password)
imo.save()
for response_plan in ResponsePlan.objects.all():
country = response_plan.workspace.countries.first()
locations = list(
Location.objects.filter(
gateway__country=country,
gateway__admin_level=5,
))
cluster = ClusterFactory(response_plan=response_plan, type="wash")
# Give Cluster IMO role in this cluster to cluster_admin User
ClusterPRPRoleFactory(
user=imo,
role=PRP_ROLE_TYPES.cluster_imo,
workspace=response_plan.workspace,
cluster=cluster,
)
co = ClusterObjectiveFactory(
title="{} - {} - {} CO".format(idx, cluster.response_plan.title,
cluster.type.upper()),
cluster=cluster,
)
if random.randint(0, 1) == 0:
reportable = RatioReportableToClusterObjectiveFactory(
content_object=co,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
else:
reportable = QuantityReportableToClusterObjectiveFactory(
content_object=co,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
for loc in locations[:2]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
for loc in locations[-2:-1:-1]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
partner = PartnerFactory(
title="{} - {} Cluster Partner".format(cluster.response_plan.title,
cluster.type.upper())[:50],
# partner_activity=None,
# partner_project=None,
)
partner.clusters.add(cluster)
print("{} Cluster objects created for {}".format(
1, response_plan.title))
print("{} Partner objects objects created for {}".format(1, cluster))
print("{} Cluster Objective objects created for {}".format(1, cluster))
table = CartoDBTable.objects.first()
locations = list(
Location.objects.filter(carto_db_table=table,
gateway__country=carto_db_table.country,
gateway__admin_level=5))
# Associate partner, role, workspace with the partner users
first_partner = Partner.objects.first()
partner_users = list()
# Partner AO creation
ao, _ = User.objects.get_or_create(username='******',
defaults={
'email': '*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Partner',
'last_name': 'AO',
})
ao.set_password(admin_password)
ao.save()
partner_users.append(ao)
# Partner Editor creation
editor, _ = User.objects.get_or_create(username='******',
defaults={
'email':
'*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Partner',
'last_name': 'Editor',
})
editor.set_password(admin_password)
editor.save()
partner_users.append(editor)
# Partner Viewer creation
viewer, _ = User.objects.get_or_create(username='******',
defaults={
'email':
'*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Partner',
'last_name': 'Viewer',
})
viewer.set_password(admin_password)
viewer.save()
partner_users.append(viewer)
# Partner Admin creation
admin, _ = User.objects.get_or_create(username='******',
defaults={
'email':
'*****@*****.**',
'is_superuser': True,
'is_staff': True,
'first_name': 'Partner',
'last_name': 'Admin',
})
admin.set_password(admin_password)
admin.save()
partner_users.append(admin)
# Give Cluster IMO role in this cluster to cluster_admin User
ClusterPRPRoleFactory(
user=imo,
role=PRP_ROLE_TYPES.cluster_imo,
workspace=None,
cluster=None,
)
for u in partner_users:
partner_cluster = first_partner.clusters.first()
workspace = partner_cluster.response_plan.workspace
u.partner = first_partner
u.save()
if 'ao' in u.username:
role = PRP_ROLE_TYPES.ip_authorized_officer
elif 'editor' in u.username:
role = PRP_ROLE_TYPES.ip_editor
elif 'viewer' in u.username:
role = PRP_ROLE_TYPES.ip_viewer
elif 'admin' in u.username:
role = PRP_ROLE_TYPES.ip_admin
ClusterPRPRoleFactory(
user=u,
role=role,
workspace=workspace,
cluster=None,
)
for cluster_objective in ClusterObjective.objects.all():
for idx in range(2, 0, -1):
ca = ClusterActivityFactory(
title="{} CA".format(cluster_objective.title),
cluster_objective=cluster_objective,
)
reportable = QuantityReportableToClusterActivityFactory(
content_object=ca,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
for loc in locations[:2]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
for loc in locations[-2:-1:-1]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
print("{} Cluster Activity objects created for {}".format(
2, cluster_objective.title))
for partner in Partner.objects.all():
first_cluster = partner.clusters.first()
pp = PartnerProjectFactory(partner=partner,
title="{} PP".format(partner.title))
pp.clusters.add(first_cluster)
reportable = QuantityReportableToPartnerProjectFactory(
content_object=pp,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
for loc in locations[:2]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
for loc in locations[-2:-1:-1]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
print(
"{} PartnerProject objects created for {} under {} Cluster".format(
1, partner, first_cluster.type.upper()))
# ClusterActivity <-> PartnerActivity link
for cluster_activity in ClusterActivity.objects.all():
partner = cluster_activity.cluster_objective.cluster.partners.first()
for project in partner.partner_projects.all():
pa = ClusterActivityPartnerActivityFactory(
partner=project.partner,
# project=project,
cluster_activity=cluster_activity,
title="{} Partner Activity from CA".format(project.title))
papc = PartnerActivityProjectContextFactory(
activity=pa,
project=project,
start_date=project.start_date,
end_date=project.end_date)
reportable_to_pa = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=papc,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
reportable_to_pa.parent_indicator = cluster_activity.reportables.first(
)
reportable_to_pa.save()
for loc in locations[:2]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable_to_pa)
for loc in locations[-2:-1:-1]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable_to_pa)
pa = ClusterActivityPartnerActivityFactory(
partner=project.partner,
# project=project,
cluster_activity=None,
cluster_objective=cluster_activity.cluster_objective,
title="{} Partner Activity".format(project.title))
papc = PartnerActivityProjectContextFactory(
activity=pa,
project=project,
start_date=project.start_date,
end_date=project.end_date)
reportable_to_pa = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=papc,
# indicator_report__progress_report=None,
# indicator_report__reporting_entity=cluster_re,
)
for loc in locations[:2]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable_to_pa)
for loc in locations[-2:-1:-1]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable_to_pa)
print(
"{} PartnerActivity objects created for {} under {} Cluster Activity and Custom Activity"
.format(2, partner, cluster_activity.title))
print("ClusterActivity <-> PartnerActivity objects linked")
PersonFactory.create_batch(workspace_quantity)
# only create PD's for the partner being used above
programme_documents = []
for workspace in Workspace.objects.all():
for i in range(workspace_quantity * 2):
pd = ProgrammeDocumentFactory.create(partner=first_partner,
workspace=workspace)
programme_documents.append(pd)
now = datetime.datetime.now()
# HRs
for month in range(1, 13):
monthrange = calendar.monthrange(now.year, month)
HRReportingPeriodDatesFactory(
programme_document=pd,
start_date=datetime.datetime(now.year, month, 1),
end_date=datetime.datetime(now.year, month, monthrange[1]),
due_date=datetime.datetime(now.year, month, monthrange[1]),
)
# Q1
QPRReportingPeriodDatesFactory(
programme_document=pd,
start_date=datetime.datetime(now.year, 1, 1),
end_date=datetime.datetime(now.year, 3, 31),
due_date=datetime.datetime(now.year, 3, 31),
)
# Q2
QPRReportingPeriodDatesFactory(
programme_document=pd,
start_date=datetime.datetime(now.year, 4, 1),
end_date=datetime.datetime(now.year, 6, 30),
due_date=datetime.datetime(now.year, 6, 30),
)
# Q3
QPRReportingPeriodDatesFactory(
programme_document=pd,
start_date=datetime.datetime(now.year, 7, 1),
end_date=datetime.datetime(now.year, 9, 30),
due_date=datetime.datetime(now.year, 9, 30),
)
# Q4
QPRReportingPeriodDatesFactory(
programme_document=pd,
start_date=datetime.datetime(now.year, 10, 1),
end_date=datetime.datetime(now.year, 12, 31),
due_date=datetime.datetime(now.year, 12, 31),
)
print("{} ProgrammeDocument objects created".format(
min(2, workspace_quantity * 2)))
# Linking the followings:
# ProgressReport - ProgrammeDocument
# created LowerLevelOutput - QuantityReportableToLowerLevelOutput
# Section - ProgrammeDocument via QuantityReportableToLowerLevelOutput
# ProgressReport - IndicatorReport from
# QuantityReportableToLowerLevelOutput
for idx, pd in enumerate(programme_documents):
locations = pd.workspace.locations
# Only mark first 2 ProgrammeDocuments to be HF indicator
is_unicef_hf_indicator = idx == 0 or idx == 1
if is_unicef_hf_indicator:
pd.status = PD_STATUS.active
pd.save()
pd.sections.add(Section.objects.order_by('?').first())
pd.unicef_focal_point.add(Person.objects.order_by('?').first())
pd.partner_focal_point.add(Person.objects.order_by('?').first())
pd.unicef_officers.add(Person.objects.order_by('?').first())
# generate reportables for this PD
for cp_idx, cp_output in enumerate(pd.cp_outputs.all()):
for llo_idx, llo in enumerate(cp_output.ll_outputs.all()):
first_llo_indicator_flag = idx == 0 and cp_idx == 0 and llo_idx == 0
# Make the first LLO from first ProgrammeDocument
# to be dual reporting enabled
if first_llo_indicator_flag:
cluster_activity_reportable = Reportable.objects.filter(
cluster_activities__partner_activity_project_contexts__activity__partner
=pd.partner).first()
else:
cluster_activity_reportable = None
# generate 2 reportable (indicators) per llo
num_reportables_range = range(2)
for i in num_reportables_range:
if i % 2 != 0:
reportable = QuantityReportableToLowerLevelOutputFactory(
content_object=llo,
indicator_report__progress_report=None,
indicator_report__reporting_entity=unicef_re,
is_unicef_hf_indicator=is_unicef_hf_indicator,
ca_indicator_used_by_reporting_entity=
cluster_activity_reportable,
)
elif i % 2 == 0 and not first_llo_indicator_flag:
reportable = RatioReportableToLowerLevelOutputFactory(
content_object=llo,
indicator_report__progress_report=None,
indicator_report__reporting_entity=unicef_re,
is_unicef_hf_indicator=is_unicef_hf_indicator,
ca_indicator_used_by_reporting_entity=
cluster_activity_reportable,
)
# delete the junk indicator report the factory creates
# we create IR's in the next for loop down below
reportable.indicator_reports.all().delete()
for loc in locations[:7]:
LocationWithReportableLocationGoalFactory.create(
location=loc, reportable=reportable)
print("{} Reportables generated for {}".format(
num_reportables_range[-1] + 1, llo))
# Generate progress reports per pd based on its reporting period dates. Requires creating indicator
# reports for each llo and then associating them with a progress report
def generate_initial_progress_reports(report_type):
rpd_queryset = pd.reporting_periods.filter(report_type=report_type)
for rpd_idx, rpd in enumerate(rpd_queryset):
print("Generating ProgressReport: ", rpd.report_type,
rpd.start_date, rpd.end_date, rpd.due_date)
progress_report = ProgressReportFactory(
programme_document=pd,
report_type=report_type,
report_number=rpd_idx + 1,
start_date=rpd.start_date,
end_date=rpd.end_date,
due_date=rpd.due_date,
)
if rpd_idx == rpd_queryset.count() - 1:
progress_report.is_final = True
progress_report.save()
for cp_output in pd.cp_outputs.all():
for llo in cp_output.ll_outputs.all():
# All Indicator Reports inside LLO should have same status
# We should skip "No status"
status = "NoS"
queryset = llo.reportables.all()
if report_type == "HR":
queryset = queryset.filter(
is_unicef_hf_indicator=True)
for reportable in queryset:
if reportable.blueprint.unit == IndicatorBlueprint.NUMBER:
ProgressReportIndicatorReportFactory(
reportable=reportable,
progress_report=progress_report,
overall_status=status,
time_period_start=rpd.start_date,
time_period_end=rpd.end_date,
due_date=rpd.due_date,
reporting_entity=unicef_re,
)
elif reportable.blueprint.unit == IndicatorBlueprint.PERCENTAGE:
ProgressReportIndicatorReportFactory(
reportable=reportable,
progress_report=progress_report,
overall_status=status,
time_period_start=rpd.start_date,
time_period_end=rpd.end_date,
due_date=rpd.due_date,
reporting_entity=unicef_re,
)
# QPR generation
generate_initial_progress_reports("QPR")
if is_unicef_hf_indicator:
# HR generation
generate_initial_progress_reports("HR")
print("{} Progress Reports generated for {}".format(
ProgressReport.objects.filter(programme_document=pd).count(), pd))
cai_llo_queryset = Reportable.objects.filter(
content_type__model="lowerleveloutput",
ca_indicator_used_by_reporting_entity__isnull=False,
)
for indicator in cai_llo_queryset:
indicator.blueprint = indicator.ca_indicator_used_by_reporting_entity.blueprint
indicator.save()
partner_activity = PartnerActivity.objects.filter(
cluster_activity=indicator.ca_indicator_used_by_reporting_entity.
content_object,
partner=indicator.content_object.cp_output.programme_document.
partner,
).first()
# Copy-paste from unicef/tasks.py
# Force update on PA Reportable instance for location update
for pa_reportable in Reportable.objects.filter(
partner_activity_project_contexts__activity=partner_activity):
pa_reportable.frequency = REPORTABLE_FREQUENCY_LEVEL.monthly
pa_reportable.save()
llo_locations = indicator.locations.values_list('id', flat=True)
pai_locations = pa_reportable.locations.values_list('id',
flat=True)
loc_diff = pai_locations.exclude(id__in=llo_locations)
# Add new locations from LLO Reportable to PA Reportable
if loc_diff.exists():
# Creating M2M Through model instances
reportable_location_goals = [
ReportableLocationGoal(
reportable=indicator,
location=l,
) for l in loc_diff
]
ReportableLocationGoal.objects.bulk_create(
reportable_location_goals)
print(
"ProgrammeDocument <-> QuantityReportableToLowerLevelOutput <-> IndicatorReport objects linked"
)
# print("Generating IndicatorLocationData for Quantity type")
# generate_indicator_report_location_disaggregation_quantity_data(generate_all=generate_all_disagg)
# print("Generating IndicatorLocationData for Ratio type")
# generate_indicator_report_location_disaggregation_ratio_data(generate_all=generate_all_disagg)
# Disaggregation association fix for CAI LLO indicators
for indicator in cai_llo_queryset:
ca_reportable = indicator.ca_indicator_used_by_reporting_entity
indicator.disaggregations.clear()
indicator.disaggregations.add(*ca_reportable.disaggregations.all())
# Fulfill submission date for closed IR
IndicatorReport.objects.filter(
report_status__in=(INDICATOR_REPORT_STATUS.submitted,
INDICATOR_REPORT_STATUS.accepted)).update(
submission_date=today)
# Null submission date for open IR
IndicatorReport.objects.exclude(
report_status__in=(INDICATOR_REPORT_STATUS.submitted,
INDICATOR_REPORT_STATUS.accepted)).update(
submission_date=None)
def setUp(self):
self.country = CountryFactory()
self.workspace = WorkspaceFactory(countries=[
self.country,
])
self.response_plan = ResponsePlanFactory(workspace=self.workspace)
self.cluster = ClusterFactory(type='cccm',
response_plan=self.response_plan)
self.loc_type = GatewayTypeFactory(country=self.country)
self.carto_table = CartoDBTableFactory(location_type=self.loc_type,
country=self.country)
self.loc1 = LocationFactory(gateway=self.loc_type,
carto_db_table=self.carto_table)
self.loc2 = LocationFactory(gateway=self.loc_type,
carto_db_table=self.carto_table)
self.unicef_officer = PersonFactory()
self.unicef_focal_point = PersonFactory()
self.partner_focal_point = PersonFactory()
self.objective = ClusterObjectiveFactory(cluster=self.cluster,
locations=[
self.loc1,
self.loc2,
])
self.activity = ClusterActivityFactory(
cluster_objective=self.objective, locations=[self.loc1, self.loc2])
self.partner = PartnerFactory(
country_code=self.country.country_short_code)
self.user = NonPartnerUserFactory()
self.partner_user = PartnerUserFactory(partner=self.partner)
ClusterPRPRoleFactory(user=self.user,
workspace=self.workspace,
cluster=self.cluster,
role=PRP_ROLE_TYPES.cluster_imo)
IPPRPRoleFactory(user=self.partner_user,
workspace=self.workspace,
role=PRP_ROLE_TYPES.ip_authorized_officer)
IPPRPRoleFactory(user=self.partner_user,
workspace=self.workspace,
cluster=None,
role=PRP_ROLE_TYPES.cluster_member)
self.project = PartnerProjectFactory(
partner=self.partner,
clusters=[self.cluster],
locations=[self.loc1, self.loc2],
)
self.p_activity = ClusterActivityPartnerActivityFactory(
partner=self.partner,
cluster_activity=self.activity,
)
self.project_context = PartnerActivityProjectContextFactory(
project=self.project,
activity=self.p_activity,
)
self.sample_disaggregation_value_map = {
"height": ["tall", "medium", "short", "extrashort"],
"age": ["1-2m", "3-4m", "5-6m", '7-10m', '11-13m', '14-16m'],
"gender": ["male", "female", "other"],
}
blueprint = QuantityTypeIndicatorBlueprintFactory(
unit=IndicatorBlueprint.NUMBER,
calculation_formula_across_locations=IndicatorBlueprint.SUM,
calculation_formula_across_periods=IndicatorBlueprint.SUM,
)
self.partneractivity_reportable = QuantityReportableToPartnerActivityProjectContextFactory(
content_object=self.project_context, blueprint=blueprint)
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=self.partneractivity_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=self.partneractivity_reportable,
)
self.pd = ProgrammeDocumentFactory(workspace=self.workspace,
partner=self.partner,
sections=[
SectionFactory(),
],
unicef_officers=[
self.unicef_officer,
],
unicef_focal_point=[
self.unicef_focal_point,
],
partner_focal_point=[
self.partner_focal_point,
])
for idx in range(2):
qpr_period = QPRReportingPeriodDatesFactory(
programme_document=self.pd)
ProgressReportFactory(
start_date=qpr_period.start_date,
end_date=qpr_period.end_date,
due_date=qpr_period.due_date,
report_number=idx + 1,
report_type=qpr_period.report_type,
is_final=False,
programme_document=self.pd,
submitted_by=self.user,
submitting_user=self.user,
)
for idx in range(6):
hr_period = HRReportingPeriodDatesFactory(
programme_document=self.pd)
ProgressReportFactory(
start_date=hr_period.start_date,
end_date=hr_period.end_date,
due_date=hr_period.due_date,
report_number=idx + 1,
report_type=hr_period.report_type,
is_final=False,
programme_document=self.pd,
submitted_by=self.user,
submitting_user=self.user,
)
self.cp_output = PDResultLinkFactory(programme_document=self.pd, )
self.llo = LowerLevelOutputFactory(cp_output=self.cp_output, )
self.llo_reportable = QuantityReportableToLowerLevelOutputFactory(
content_object=self.llo,
blueprint=QuantityTypeIndicatorBlueprintFactory(
unit=IndicatorBlueprint.NUMBER,
calculation_formula_across_locations=IndicatorBlueprint.SUM,
))
self.llo_reportable.disaggregations.clear()
self.partneractivity_reportable.disaggregations.clear()
# Create the disaggregations and values in the db for all response plans
# including one for no response plan as well
for disagg_name, values in self.sample_disaggregation_value_map.items(
):
disagg = IPDisaggregationFactory(name=disagg_name)
cluster_disagg = DisaggregationFactory(
name=disagg_name, response_plan=self.response_plan)
self.llo_reportable.disaggregations.add(disagg)
self.partneractivity_reportable.disaggregations.add(cluster_disagg)
for value in values:
DisaggregationValueFactory(disaggregation=cluster_disagg,
value=value)
DisaggregationValueFactory(disaggregation=disagg, value=value)
LocationWithReportableLocationGoalFactory(
location=self.loc1,
reportable=self.llo_reportable,
)
LocationWithReportableLocationGoalFactory(
location=self.loc2,
reportable=self.llo_reportable,
)
for _ in range(2):
with patch("django.db.models.signals.ModelSignal.send", Mock()):
ClusterIndicatorReportFactory(
reportable=self.partneractivity_reportable,
report_status=INDICATOR_REPORT_STATUS.submitted,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(self.partneractivity_reportable,
indicator_type="quantity")
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=self.partneractivity_reportable):
QuantityIndicatorDisaggregator.post_process(loc_data)
for pr in self.pd.progress_reports.all():
ProgressReportIndicatorReportFactory(
progress_report=pr,
reportable=self.llo_reportable,
report_status=INDICATOR_REPORT_STATUS.submitted,
overall_status=OVERALL_STATUS.met,
)
# Creating Level-3 disaggregation location data for all locations
generate_3_num_disagg_data(self.llo_reportable,
indicator_type="quantity")
for loc_data in IndicatorLocationData.objects.filter(
indicator_report__reportable=self.llo_reportable):
QuantityIndicatorDisaggregator.post_process(loc_data)
super().setUp()
def generate_fake_data(workspace_quantity=10):
if not settings.IS_TEST and workspace_quantity < 1:
workspace_quantity = 5
if workspace_quantity >= 30:
workspace_quantity = 30
today = datetime.date.today()
users_to_create = [
('admin_imo', '*****@*****.**', IMORole),
('admin_ao', '*****@*****.**', PartnerAuthorizedOfficerRole),
('admin_pe', '*****@*****.**', PartnerEditorRole),
('admin_pv', '*****@*****.**', PartnerViewerRole),
]
users_created = []
for u in users_to_create:
admin, created = User.objects.get_or_create(username=u[0],
defaults={
'email': u[1],
'is_superuser': True,
'is_staff': True,
})
admin.set_password('Passw0rd!')
admin.save()
admin.groups.add(u[2].as_group())
users_created.append(admin)
print("Users created: {}/{}\n".format(users_created, 'Passw0rd!'))
SectionFactory.create_batch(workspace_quantity)
print("{} Section objects created".format(workspace_quantity))
CountryFactory.create_batch(workspace_quantity)
print("{} Country objects created".format(workspace_quantity))
WorkspaceFactory.create_batch(workspace_quantity)
print("{} Workspace objects created".format(workspace_quantity))
beginning_of_this_year = datetime.date(today.year, 1, 1)
for workspace in Workspace.objects.all():
country = Country.objects.order_by('?').first()
workspace.countries.add(country)
for idx in xrange(0, 3):
year = today.year - idx
# TODO: use ResponsePlanFactory
ResponsePlan.objects.create(
workspace=workspace,
title="{} {} Humanitarian Response Plan".format(
workspace.title, year),
start=beginning_of_this_year,
end=beginning_of_this_year + datetime.timedelta(days=30))
gateways = list()
for idx in range(5):
gateways.append(
GatewayTypeFactory(country=country, admin_level=idx + 1))
carto_db_table = CartoDBTableFactory(location_type=gateways[0],
country=country)
locations = list()
for idx in range(8):
locations.append(
LocationFactory.create(
gateway=gateways[idx] if idx < 5 else gateways[4],
parent=None if idx == 0 else
(locations[idx - 1] if idx < 6 else locations[4]),
carto_db_table=carto_db_table,
))
print("{} ResponsePlan objects created for {}".format(3, workspace))
for response_plan in ResponsePlan.objects.all():
country = response_plan.workspace.countries.first()
locations = list(Location.objects.filter(gateway__country=country))
table = response_plan.workspace.countries.first(
).carto_db_tables.first()
user = UserFactory(first_name="WASH", last_name="IMO")
cluster = ClusterFactory(response_plan=response_plan, type="wash")
for idx in xrange(2, 0, -1):
co = ClusterObjectiveFactory(
title="{} - {} - {} CO".format(idx,
cluster.response_plan.title,
cluster.type.upper()),
cluster=cluster,
)
reportable_to_co = QuantityReportableToClusterObjectiveFactory(
content_object=co,
indicator_report__progress_report=None,
locations=locations,
)
co.locations.add(*locations)
user = UserFactory(first_name="{} Cluster".format(
cluster.type.upper()[:20]),
last_name="Partner")
partner = PartnerFactory(
title="{} - {} Cluster Partner".format(cluster.response_plan.title,
cluster.type.upper()),
partner_activity=None,
partner_project=None,
user=user,
)
partner.clusters.add(cluster)
user = UserFactory(first_name="Nutrition", last_name="IMO")
cluster = ClusterFactory(
response_plan=response_plan,
type="nutrition",
)
for idx in xrange(2, 0, -1):
co = ClusterObjectiveFactory(
title="{} - {} Cluster Objective".format(
cluster.response_plan.title, cluster.type.upper()),
cluster=cluster,
)
reportable_to_co = QuantityReportableToClusterObjectiveFactory(
content_object=co,
indicator_report__progress_report=None,
locations=locations,
)
co.locations.add(*locations)
user = UserFactory(first_name="{} Cluster".format(
cluster.type.upper()),
last_name="Partner")
partner = PartnerFactory(
title="{} - {} Cluster Partner".format(cluster.response_plan.title,
cluster.type.upper()),
partner_activity=None,
partner_project=None,
user=user,
)
partner.clusters.add(cluster)
user = UserFactory(first_name="Education", last_name="IMO")
cluster = ClusterFactory(
response_plan=response_plan,
type="education",
)
for idx in xrange(2, 0, -1):
co = ClusterObjectiveFactory(
title="{} - {} Cluster Objective".format(
cluster.response_plan.title, cluster.type.upper()),
cluster=cluster,
)
reportable_to_co = QuantityReportableToClusterObjectiveFactory(
content_object=co,
indicator_report__progress_report=None,
locations=locations,
)
co.locations.add(*locations)
user = UserFactory(first_name="{} Cluster".format(
cluster.type.upper()),
last_name="Partner")
partner = PartnerFactory(
title="{} - {} Cluster Partner".format(cluster.response_plan.title,
cluster.type.upper()),
partner_activity=None,
partner_project=None,
user=user,
)
partner.clusters.add(cluster)
print("{} Cluster & Cluster user objects created for {}".format(
3, response_plan.title))
print(
"{} Partner objects & Partner user objects created for {}".format(
3, cluster))
print("{} Cluster Objective objects created for {}".format(
2 * 3, cluster))
table = CartoDBTable.objects.first()
locations = list(
Location.objects.filter(
carto_db_table=table,
carto_db_table__country=carto_db_table.country))
# associate partner, workspace, imo_clustes etc. with the users
first_partner = Partner.objects.first()
for u in users_created:
for w in Workspace.objects.all():
u.workspaces.add(w)
if not u.groups.filter(name=IMORole.as_group().name):
u.partner = first_partner
else:
u.organization = 'UNICEF Cluster Team'
u.imo_clusters = Cluster.objects.all().order_by('?')[:2]
u.save()
for cluster_objective in ClusterObjective.objects.all():
for idx in xrange(2, 0, -1):
ca = ClusterActivityFactory(
title="{} Cluster Activity".format(cluster_objective.title),
cluster_objective=cluster_objective,
)
reportable_to_ca = QuantityReportableToClusterActivityFactory(
content_object=ca,
indicator_report__progress_report=None,
locations=locations,
)
ca.locations.add(*locations)
print("{} Cluster Activity objects created for {}".format(
2, cluster_objective.title))
for partner in Partner.objects.all():
for idx in xrange(2, 0, -1):
first_cluster = partner.clusters.first()
pp = PartnerProjectFactory(partner=partner,
title="{} Partner Project".format(
partner.title))
pp.clusters.add(first_cluster)
reportable_to_pp = QuantityReportableToPartnerProjectFactory(
content_object=pp,
indicator_report__progress_report=None,
locations=locations,
)
pp.locations.add(*locations)
print(
"{} PartnerProject objects created for {} under {} Cluster".format(
2, partner, first_cluster.type.upper()))
# ClusterActivity <-> PartnerActivity link
for cluster_activity in ClusterActivity.objects.all():
partner = cluster_activity.cluster_objective.cluster.partners.first()
for project in partner.partner_projects.all():
for idx in xrange(2, 0, -1):
pa = PartnerActivityFactory(
partner=project.partner,
project=project,
cluster_activity=cluster_activity,
title="{} Partner Activity from CA".format(project.title))
reportable_to_pa = QuantityReportableToPartnerActivityFactory(
content_object=pa,
indicator_report__progress_report=None,
locations=locations,
)
reportable_to_pa.parent_indicator = cluster_activity.reportables.first(
)
reportable_to_pa.save()
pa.locations.add(*locations)
pa = PartnerActivityFactory(
partner=project.partner,
project=project,
cluster_activity=None,
cluster_objective=cluster_activity.cluster_objective,
title="{} Partner Activity".format(project.title))
reportable_to_pa = QuantityReportableToPartnerActivityFactory(
content_object=pa,
indicator_report__progress_report=None,
locations=locations,
)
pa.locations.add(*locations)
print(
"{} PartnerActivity objects created for {} under {} Cluster Activity and Custom Activity"
.format(4, partner, cluster_activity.title))
print("ClusterActivity <-> PartnerActivity objects linked")
PersonFactory.create_batch(workspace_quantity)
# only create PD's for the partner being used above
# for partner in Partner.objects.all():
for workspace in Workspace.objects.all():
for i in range(workspace_quantity * 5):
pd = ProgrammeDocumentFactory.create(partner=first_partner,
workspace=workspace)
for ir in range(3):
d = datetime.datetime.now() + datetime.timedelta(days=ir * 30)
ReportingPeriodDatesFactory.create(
programme_document=pd,
start_date=d,
end_date=d + datetime.timedelta(days=30),
due_date=d + datetime.timedelta(days=45),
)
print("{} ProgrammeDocument objects created".format(
min(4, workspace_quantity * 2)))
# Linking the followings:
# ProgressReport - ProgrammeDocument
# created LowerLevelOutput - QuantityReportableToLowerLevelOutput
# Section - ProgrammeDocument via QuantityReportableToLowerLevelOutput
# ProgressReport - IndicatorReport from
# QuantityReportableToLowerLevelOutput
for idx, pd in enumerate(ProgrammeDocument.objects.all()):
locations = pd.workspace.locations
pd.sections.add(Section.objects.order_by('?').first())
pd.unicef_focal_point.add(Person.objects.order_by('?').first())
pd.partner_focal_point.add(Person.objects.order_by('?').first())
pd.unicef_officers.add(Person.objects.order_by('?').first())
# generate reportables for this PD
for cp_output in pd.cp_outputs.all():
for llo in cp_output.ll_outputs.all():
# generate 2 to 10 reportable (indicators) per llo
num_reportables_range = range(random.randint(2, 10))
for i in num_reportables_range:
if i % 3 != 0:
reportable = QuantityReportableToLowerLevelOutputFactory(
content_object=llo,
indicator_report__progress_report=None,
locations=locations,
)
else:
reportable = RatioReportableToLowerLevelOutputFactory(
content_object=llo,
indicator_report__progress_report=None,
locations=locations,
)
# delete the junk indicator report the factory creates
# we create IR's in the next for loop down below
reportable.indicator_reports.all().delete()
print("{} Reportables generated for {}".format(
num_reportables_range[-1] + 1, llo))
# Generate 2-8 progress reports per pd. Requires creating indicator
# reports for each llo and then associating them with a progress
# report
for idx in xrange(0, random.randint(2, 8)):
progress_report = ProgressReportFactory(programme_document=pd)
for cp_output in pd.cp_outputs.all():
for llo in cp_output.ll_outputs.all():
# All Indicator Reports inside LLO should have same status
# We should skip "No status"
status = OVERALL_STATUS_LIST[random.randint(0, 4)]
for reportable in llo.reportables.all():
if reportable.blueprint.unit == IndicatorBlueprint.NUMBER:
QuantityIndicatorReportFactory(
reportable=reportable,
progress_report=progress_report,
overall_status=status,
)
elif reportable.blueprint.unit == IndicatorBlueprint.PERCENTAGE:
RatioIndicatorReportFactory(
reportable=reportable,
progress_report=progress_report,
overall_status=status,
)
print("{} Progress Reports generated for {}".format(
ProgressReport.objects.filter(programme_document=pd).count(), pd))
print(
"ProgrammeDocument <-> QuantityReportableToLowerLevelOutput <-> IndicatorReport objects linked"
.format(workspace_quantity))
print("Generating IndicatorLocationData for Quantity type")
generate_indicator_report_location_disaggregation_quantity_data()
print("Generating IndicatorLocationData for Ratio type")
generate_indicator_report_location_disaggregation_ratio_data()
# Fulfill submission date for closed IR
IndicatorReport.objects.filter(
report_status__in=(INDICATOR_REPORT_STATUS.submitted,
INDICATOR_REPORT_STATUS.accepted)).update(
submission_date=today)
# Null submission date for open IR
IndicatorReport.objects.exclude(
report_status__in=(INDICATOR_REPORT_STATUS.submitted,
INDICATOR_REPORT_STATUS.accepted)).update(
submission_date=None)