def get_expected_data_from_order(order):
"""Returns expected dictionary based on given order"""
return {
'cancellation_reason__name':
get_attr_or_none(order, 'cancellation_reason.name'),
'cancelled_on':
format_date_or_datetime(order.cancelled_on),
'company_id':
str(order.company_id),
'completed_on':
format_date_or_datetime(order.completed_on),
'contact_id':
str(order.contact_id),
'created_by__dit_team_id':
str(order.created_by.dit_team_id),
'created_on':
format_date_or_datetime(order.created_on),
'delivery_date':
format_date_or_datetime(order.delivery_date),
'id':
str(order.id),
'invoice__subtotal_cost':
get_attr_or_none(order, 'invoice.subtotal_cost'),
'paid_on':
format_date_or_datetime(order.paid_on),
'primary_market__name':
get_attr_or_none(order, 'primary_market.name'),
'quote__accepted_on':
format_date_or_datetime(get_attr_or_none(order,
'quote.accepted_on'), ),
'quote__created_on':
format_date_or_datetime(get_attr_or_none(order, 'quote.created_on')),
'reference':
order.reference,
'refund_created': (format_date_or_datetime(
order.refunds.latest('created_on').created_on)
if order.refunds.exists() else None),
'refund_total_amount':
(sum([x.total_amount for x in order.refunds.all()])
if order.refunds.exists() else None),
'sector_name':
get_attr_or_none(order, 'sector.name'),
'services':
join_attr_values(order.service_types.order_by('name')),
'status':
order.status,
'subtotal_cost':
order.subtotal_cost,
'total_cost':
order.total_cost,
'uk_region__name':
order.uk_region.name,
'vat_cost':
order.vat_cost,
}
def test_export(self, es_with_collector, request_sortby, orm_ordering):
"""Test export large capital investor profile search results."""
url = reverse('api-v4:search:large-investor-profile-export')
CompleteLargeCapitalInvestorProfileFactory(
investable_capital=10000,
global_assets_under_management=20000,
)
with freeze_time('2018-01-01 11:12:13'):
LargeCapitalInvestorProfileFactory(
investable_capital=300,
global_assets_under_management=200,
)
es_with_collector.flush_and_refresh()
data = {}
if request_sortby:
data['sortby'] = request_sortby
with freeze_time('2018-01-01 11:12:13'):
response = self.api_client.post(url, data=data)
assert response.status_code == status.HTTP_200_OK
assert parse_header(response.get('Content-Disposition')) == (
'attachment',
{
'filename':
'Data Hub - Large capital profiles - 2018-01-01-11-12-13.csv',
},
)
sorted_profiles = LargeCapitalInvestorProfile.objects.order_by(
orm_ordering, 'pk')
response_text = response.getvalue().decode('utf-8-sig')
reader = DictReader(StringIO(response_text))
assert reader.fieldnames == list(
SearchLargeInvestorProfileExportAPIView.field_titles.values(), )
expected_row_data = [{
'Date created':
profile.created_on,
'Global assets under management':
profile.global_assets_under_management,
'Investable capital':
profile.investable_capital,
'Investor company':
get_attr_or_none(
profile,
'investor_company.name',
),
'Investor description':
profile.investor_description,
'Notes on locations':
profile.notes_on_locations,
'Investor type':
get_attr_or_none(
profile,
'investor_type.name',
),
'Required checks conducted':
get_attr_or_none(
profile,
'required_checks_conducted.name',
),
'Minimum return rate':
get_attr_or_none(
profile,
'minimum_return_rate.name',
),
'Minimum equity percentage':
get_attr_or_none(
profile,
'minimum_equity_percentage.name',
),
'Date last modified':
profile.modified_on,
'UK regions of interest':
join_attr_values(profile.uk_region_locations.order_by('name'), ),
'Restrictions':
join_attr_values(profile.restrictions.order_by('name'), ),
'Time horizons':
join_attr_values(profile.time_horizons.order_by('name'), ),
'Investment types':
join_attr_values(profile.investment_types.order_by('name'), ),
'Deal ticket sizes':
join_attr_values(profile.deal_ticket_sizes.order_by('name'), ),
'Desired deal roles':
join_attr_values(profile.desired_deal_roles.order_by('name'), ),
'Required checks conducted by':
get_attr_or_none(
profile,
'required_checks_conducted_by.name',
),
'Required checks conducted on':
profile.required_checks_conducted_on,
'Other countries being considered':
join_attr_values(
profile.other_countries_being_considered.order_by('name'), ),
'Construction risks':
join_attr_values(profile.construction_risks.order_by('name'), ),
'Data Hub profile reference':
str(profile.pk),
'Asset classes of interest':
join_attr_values(
profile.asset_classes_of_interest.order_by('name'), ),
'Data Hub link':
(f'{settings.DATAHUB_FRONTEND_URL_PREFIXES["company"]}'
f'/{profile.investor_company.pk}/investments/large-capital-profile'
),
} for profile in sorted_profiles]
expected_rows = format_csv_data(expected_row_data)
# item is an ordered dict so is cast to a dict to make the comparison easier to
# interpret in the event of the assert actual_rows == expected_rows failing.
actual_rows = [dict(item) for item in reader]
assert actual_rows == expected_rows
def test_interaction_export(
self,
setup_es,
request_sortby,
orm_ordering,
):
"""
Test export of interaction search results with a policy feedback user.
Checks that all interaction kinds except for policy feedback are included in the export.
"""
# Faker generates job titles containing commas which complicates comparisons,
# so all contact job titles are explicitly set
company = CompanyFactory()
CompanyInteractionFactory(
company=company,
contacts=[
ContactFactory(company=company, job_title='Engineer'),
ContactFactory(company=company, job_title=None),
ContactFactory(company=company, job_title=''),
],
)
EventServiceDeliveryFactory(
company=company,
contacts=[
ContactFactory(company=company, job_title='Managing director'),
],
)
InvestmentProjectInteractionFactory(
company=company,
contacts=[
ContactFactory(company=company, job_title='Exports manager'),
],
)
ServiceDeliveryFactory(
company=company,
contacts=[
ContactFactory(company=company, job_title='Sales director'),
],
)
CompanyInteractionFactoryWithPolicyFeedback(
company=company,
contacts=[
ContactFactory(company=company,
job_title='Business development manager'),
],
policy_areas=PolicyArea.objects.order_by('?')[:2],
policy_issue_types=PolicyIssueType.objects.order_by('?')[:2],
)
setup_es.indices.refresh()
data = {}
if request_sortby:
data['sortby'] = request_sortby
url = reverse('api-v3:search:interaction-export')
with freeze_time('2018-01-01 11:12:13'):
response = self.api_client.post(url, data=data)
assert response.status_code == status.HTTP_200_OK
assert parse_header(response.get('Content-Type')) == ('text/csv', {
'charset':
'utf-8'
})
assert parse_header(response.get('Content-Disposition')) == (
'attachment',
{
'filename': 'Data Hub - Interactions - 2018-01-01-11-12-13.csv'
},
)
sorted_interactions = Interaction.objects.all().order_by(
orm_ordering,
'pk',
)
reader = DictReader(StringIO(response.getvalue().decode('utf-8-sig')))
assert reader.fieldnames == list(
SearchInteractionExportAPIView.field_titles.values())
expected_row_data = [{
'Date':
interaction.date,
'Type':
interaction.get_kind_display(),
'Service':
get_attr_or_none(interaction, 'service.name'),
'Subject':
interaction.subject,
'Link':
f'{settings.DATAHUB_FRONTEND_URL_PREFIXES["interaction"]}'
f'/{interaction.pk}',
'Company':
get_attr_or_none(interaction, 'company.name'),
'Company link':
f'{settings.DATAHUB_FRONTEND_URL_PREFIXES["company"]}'
f'/{interaction.company.pk}',
'Company country':
get_attr_or_none(
interaction,
'company.address_country.name',
),
'Company UK region':
get_attr_or_none(interaction, 'company.uk_region.name'),
'Company sector':
get_attr_or_none(interaction, 'company.sector.name'),
'Contacts':
_format_expected_contacts(interaction),
'Adviser':
get_attr_or_none(interaction, 'dit_adviser.name'),
'Service provider':
get_attr_or_none(interaction, 'dit_team.name'),
'Event':
get_attr_or_none(interaction, 'event.name'),
'Communication channel':
get_attr_or_none(interaction, 'communication_channel.name'),
'Service delivery status':
get_attr_or_none(
interaction,
'service_delivery_status.name',
),
'Net company receipt':
interaction.net_company_receipt,
'Policy issue types':
join_attr_values(interaction.policy_issue_types.all()),
'Policy areas':
join_attr_values(interaction.policy_areas.all(), separator='; '),
'Policy feedback notes':
interaction.policy_feedback_notes,
} for interaction in sorted_interactions]
actual_row_data = [_format_actual_csv_row(row) for row in reader]
assert actual_row_data == format_csv_data(expected_row_data)
def test_export(self, setup_es, request_sortby, orm_ordering):
"""Test export of investment project search results."""
url = reverse('api-v3:search:investment_project-export')
InvestmentProjectFactory()
InvestmentProjectFactory(cdms_project_code='cdms-code')
VerifyWinInvestmentProjectFactory()
won_project = WonInvestmentProjectFactory()
InvestmentProjectTeamMemberFactory.create_batch(3, investment_project=won_project)
InvestmentProjectFactory(
name='project for subsidiary',
investor_company=CompanyFactory(
global_headquarters=CompanyFactory(
one_list_tier_id=OneListTier.objects.first().id,
one_list_account_owner=AdviserFactory(),
),
),
)
setup_es.indices.refresh()
data = {}
if request_sortby:
data['sortby'] = request_sortby
with freeze_time('2018-01-01 11:12:13'):
response = self.api_client.post(url, data=data)
assert response.status_code == status.HTTP_200_OK
assert parse_header(response.get('Content-Disposition')) == (
'attachment', {'filename': 'Data Hub - Investment projects - 2018-01-01-11-12-13.csv'},
)
sorted_projects = InvestmentProject.objects.order_by(orm_ordering, 'pk')
response_text = response.getvalue().decode('utf-8-sig')
reader = DictReader(StringIO(response_text))
assert reader.fieldnames == list(SearchInvestmentExportAPIView.field_titles.values())
expected_row_data = [
{
'Date created': project.created_on,
'Project reference': project.project_code,
'Project name': project.name,
'Investor company': project.investor_company.name,
'Investor company town or city': project.investor_company.address_town,
'Country of origin':
get_attr_or_none(project, 'investor_company.address_country.name'),
'Investment type': get_attr_or_none(project, 'investment_type.name'),
'Status': project.get_status_display(),
'Stage': get_attr_or_none(project, 'stage.name'),
'Link':
f'{settings.DATAHUB_FRONTEND_URL_PREFIXES["investmentproject"]}'
f'/{project.pk}',
'Actual land date': project.actual_land_date,
'Estimated land date': project.estimated_land_date,
'FDI value': get_attr_or_none(project, 'fdi_value.name'),
'Sector': get_attr_or_none(project, 'sector.name'),
'Date of latest interaction': None,
'Project manager': get_attr_or_none(project, 'project_manager.name'),
'Client relationship manager':
get_attr_or_none(project, 'client_relationship_manager.name'),
'Global account manager': self._get_global_account_manager_name(project),
'Project assurance adviser':
get_attr_or_none(project, 'project_assurance_adviser.name'),
'Other team members': join_attr_values(project.team_members.all(), 'adviser.name'),
'Delivery partners': join_attr_values(project.delivery_partners.all()),
'Possible UK regions': join_attr_values(project.uk_region_locations.all()),
'Actual UK regions': join_attr_values(project.actual_uk_regions.all()),
'Specific investment programme':
get_attr_or_none(project, 'specific_programme.name'),
'Referral source activity':
get_attr_or_none(project, 'referral_source_activity.name'),
'Referral source activity website':
get_attr_or_none(project, 'referral_source_activity_website.name'),
'Total investment': project.total_investment,
'New jobs': project.number_new_jobs,
'Average salary of new jobs': get_attr_or_none(project, 'average_salary.name'),
'Safeguarded jobs': project.number_safeguarded_jobs,
'Level of involvement': get_attr_or_none(project, 'level_of_involvement.name'),
'Likelihood to land': get_attr_or_none(project, 'likelihood_to_land.name'),
'R&D budget': project.r_and_d_budget,
'Associated non-FDI R&D project': project.non_fdi_r_and_d_budget,
'New to world tech': project.new_tech_to_uk,
'FDI type': project.fdi_type,
'Foreign equity investment': project.foreign_equity_investment,
'GVA multiplier': get_attr_or_none(project, 'gva_multiplier.multiplier'),
'GVA': project.gross_value_added,
}
for project in sorted_projects
]
expected_rows = format_csv_data(expected_row_data)
# item is an ordered dict so is cast to a dict to make the comparison easier to
# interpret in the event of the assert actual_rows == expected_rows failing.
actual_rows = [dict(item) for item in reader]
# Support for ordering was added to StringAgg in Django 2.2. However, it is not
# currently used due to https://code.djangoproject.com/ticket/30315. While that
# remains the case, our StringAgg fields are unordered and we use this workaround to
# compare them.
unordered_fields = (
'Other team members',
'Delivery partners',
'Possible UK regions',
'Actual UK regions',
)
for row in chain(actual_rows, expected_rows):
for field in unordered_fields:
row[field] = frozenset(row[field].split(', '))
assert actual_rows == expected_rows
def _build_expected_export_response(opportunity):
return {
'Date created': opportunity.created_on,
'Created by': get_attr_or_none(opportunity, 'created_by.name'),
'Data Hub opportunity reference': str(opportunity.pk),
'Data Hub link': (
f'{settings.DATAHUB_FRONTEND_URL_PREFIXES["largecapitalopportunity"]}'
f'/{opportunity.pk}/investments/large-capital-opportunity'
),
'Name': opportunity.name,
'Description': opportunity.description,
'Type': get_attr_or_none(
opportunity, 'type.name',
),
'Status': get_attr_or_none(
opportunity, 'status.name',
),
'UK region locations': join_attr_values(
opportunity.uk_region_locations.order_by('name'),
),
'Promoters': join_attr_values(
opportunity.promoters.order_by('name'),
),
'Lead DIT relationship manager': opportunity.lead_dit_relationship_manager.name,
'Other DIT contacts': get_attr_or_none(
opportunity, 'other_dit_contacts.name',
),
'Required checks conducted': get_attr_or_none(
opportunity, 'required_checks_conducted.name',
),
'Required checks conducted by': get_attr_or_none(
opportunity, 'required_checks_conducted_by.name',
),
'Required checks conducted on': opportunity.required_checks_conducted_on,
'Asset classes': join_attr_values(
opportunity.asset_classes.order_by('name'),
),
'Opportunity value type': get_attr_or_none(
opportunity, 'opportunity_value_type.name',
),
'Opportunity value': opportunity.opportunity_value,
'Construction risks': join_attr_values(
opportunity.construction_risks.order_by('name'),
),
'Total investment sought': opportunity.total_investment_sought,
'Current investment secured': opportunity.current_investment_secured,
'Investment types': join_attr_values(
opportunity.investment_types.order_by('name'),
),
'Estimated return rate': get_attr_or_none(
opportunity, 'estimated_return_rate.name',
),
'Time horizons': join_attr_values(
opportunity.time_horizons.order_by('name'),
),
'Sources of funding': join_attr_values(
opportunity.sources_of_funding.order_by('name'),
),
'DIT support provided': opportunity.dit_support_provided,
'Funding supporting details': opportunity.funding_supporting_details,
'Reasons for abandonment': join_attr_values(
opportunity.reasons_for_abandonment.order_by('name'),
),
'Why abandoned': opportunity.why_abandoned,
'Why suspended': opportunity.why_suspended,
'Date last modified': opportunity.modified_on,
}