def _related_investment_project_field():
"""Field for a related investment project."""
return Object(
properties={
'id': Keyword(),
'name': fields.NormalizedKeyword(),
'project_code': fields.NormalizedKeyword(),
})
class CompaniesHouseCompany(BaseESModel):
"""Elasticsearch representation of CompaniesHouseCompany model."""
id = Keyword()
company_category = fields.NormalizedKeyword()
company_number = fields.NormalizedKeyword()
company_status = fields.NormalizedKeyword()
incorporation_date = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
registered_address = fields.address_field(index_country=False)
# TODO: delete once the migration to nested registered address is complete
registered_address_1 = Text()
registered_address_2 = Text()
registered_address_town = fields.NormalizedKeyword()
registered_address_county = Text()
registered_address_postcode = Text(
copy_to='registered_address_postcode_trigram')
registered_address_postcode_trigram = fields.TrigramText()
registered_address_country = fields.id_name_field()
sic_code_1 = Text()
sic_code_2 = Text()
sic_code_3 = Text()
sic_code_4 = Text()
uri = Text()
COMPUTED_MAPPINGS = {
'registered_address':
partial(dict_utils.address_dict, prefix='registered_address'),
}
MAPPINGS = {
'id': str,
# TODO: delete once the migration to nested registered address is complete
'registered_address_country': dict_utils.id_name_dict,
}
SEARCH_FIELDS = (
'name', # to find 2-letter words
'name.trigram',
'company_number',
'registered_address.postcode.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class SearchSimpleModel(BaseSearchModel):
"""OpenSearch representation of SimpleModel model."""
id = Keyword()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
country = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
address = Text(fields={
'trigram': fields.TrigramText(),
}, )
date = Date()
SEARCH_FIELDS = (
'name',
'name.trigram',
'country.trigram',
'address.trigram',
)
class ESSimpleModel(BaseESModel):
"""Elasticsearch representation of SimpleModel model."""
id = Keyword()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
date = Date()
SEARCH_FIELDS = (
'name',
'name.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class Interaction(BaseESModel):
"""Elasticsearch representation of Interaction model."""
id = Keyword()
company = fields.company_field()
company_sector = fields.sector_field()
company_one_list_group_tier = fields.id_unindexed_name_field()
communication_channel = fields.id_unindexed_name_field()
contacts = _contact_field()
created_on = Date()
date = Date()
dit_participants = Object(_DITParticipant)
event = fields.id_name_partial_field()
investment_project = fields.id_unindexed_name_field()
investment_project_sector = fields.sector_field()
is_event = Boolean(index=False)
grant_amount_offered = Double(index=False)
kind = Keyword()
modified_on = Date()
net_company_receipt = Double(index=False)
notes = fields.Text(index=False)
policy_areas = fields.id_unindexed_name_field()
policy_issue_types = fields.id_unindexed_name_field()
service = fields.id_unindexed_name_field()
service_delivery_status = fields.id_unindexed_name_field()
subject = fields.NormalizedKeyword(
fields={
'english': fields.EnglishText(),
},
)
was_policy_feedback_provided = Boolean()
were_countries_discussed = Boolean()
export_countries = _export_country_field()
MAPPINGS = {
'company': dict_utils.company_dict,
'communication_channel': dict_utils.id_name_dict,
'contacts': dict_utils.contact_or_adviser_list_of_dicts,
'dit_participants': _dit_participant_list,
'export_countries': _export_countries_list,
'event': dict_utils.id_name_dict,
'investment_project': dict_utils.id_name_dict,
'policy_areas': dict_utils.id_name_list_of_dicts,
'policy_issue_types': dict_utils.id_name_list_of_dicts,
'service': dict_utils.id_name_dict,
'service_delivery_status': dict_utils.id_name_dict,
}
COMPUTED_MAPPINGS = {
'company_sector': dict_utils.computed_nested_sector_dict('company.sector'),
'company_one_list_group_tier': lambda obj: dict_utils.id_name_dict(
obj.company.get_one_list_group_tier() if obj.company else None,
),
'investment_project_sector': dict_utils.computed_nested_sector_dict(
'investment_project.sector',
),
'is_event': attrgetter('is_event'),
}
SEARCH_FIELDS = (
'id',
'company.name',
'company.name.trigram',
'contacts.name', # to find 2-letter words
'contacts.name.trigram',
'event.name',
'event.name.trigram',
'subject.english',
'dit_participants.adviser.name',
'dit_participants.adviser.name.trigram',
'dit_participants.team.name',
'dit_participants.team.name.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class InvestmentProject(BaseESModel):
"""Elasticsearch representation of InvestmentProject."""
id = Keyword()
actual_land_date = Date()
actual_uk_regions = fields.id_name_field()
address_1 = Text()
address_2 = Text()
address_town = fields.NormalizedKeyword()
address_postcode = Text()
approved_commitment_to_invest = Boolean()
approved_fdi = Boolean()
approved_good_value = Boolean()
approved_high_value = Boolean()
approved_landed = Boolean()
approved_non_fdi = Boolean()
allow_blank_estimated_land_date = Boolean(index=False)
allow_blank_possible_uk_regions = Boolean(index=False)
anonymous_description = fields.EnglishText()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
associated_non_fdi_r_and_d_project = _related_investment_project_field()
average_salary = fields.id_name_field()
business_activities = fields.id_name_field()
client_cannot_provide_foreign_investment = Boolean()
client_cannot_provide_total_investment = Boolean()
client_contacts = fields.contact_or_adviser_field()
client_relationship_manager = fields.contact_or_adviser_field(
include_dit_team=True)
client_requirements = Text(index=False)
comments = fields.EnglishText()
country_investment_originates_from = fields.id_name_field()
country_lost_to = Object(properties={
'id': Keyword(index=False),
'name': Text(index=False),
}, )
created_on = Date()
created_by = fields.contact_or_adviser_field(include_dit_team=True)
date_abandoned = Date()
date_lost = Date()
delivery_partners = fields.id_name_field()
description = fields.EnglishText()
estimated_land_date = Date()
export_revenue = Boolean()
fdi_type = fields.id_name_field()
fdi_value = fields.id_name_field()
foreign_equity_investment = Double()
government_assistance = Boolean()
intermediate_company = fields.id_name_field()
investor_company = fields.id_name_partial_field()
investor_company_country = fields.id_name_field()
investment_type = fields.id_name_field()
investor_type = fields.id_name_field()
level_of_involvement = fields.id_name_field()
likelihood_to_land = fields.id_name_field()
project_assurance_adviser = fields.contact_or_adviser_field(
include_dit_team=True)
project_manager = fields.contact_or_adviser_field(include_dit_team=True)
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
new_tech_to_uk = Boolean()
non_fdi_r_and_d_budget = Boolean()
number_new_jobs = Integer()
number_safeguarded_jobs = Long()
modified_on = Date()
project_arrived_in_triage_on = Date()
project_code = fields.NormalizedKeyword(fields={
'trigram': fields.TrigramText(),
}, )
proposal_deadline = Date()
other_business_activity = Text(index=False)
quotable_as_public_case_study = Boolean()
r_and_d_budget = Boolean()
reason_abandoned = Text(index=False)
reason_delayed = Text(index=False)
reason_lost = Text(index=False)
referral_source_activity = fields.id_name_field()
referral_source_activity_event = fields.NormalizedKeyword()
referral_source_activity_marketing = fields.id_name_field()
referral_source_activity_website = fields.id_name_field()
referral_source_adviser = Object(properties={
'id': Keyword(index=False),
'first_name': Text(index=False),
'last_name': Text(index=False),
'name': Text(index=False),
}, )
sector = fields.sector_field()
site_decided = Boolean()
some_new_jobs = Boolean()
specific_programme = fields.id_name_field()
stage = fields.id_name_field()
status = fields.NormalizedKeyword()
team_members = fields.contact_or_adviser_field(include_dit_team=True)
total_investment = Double()
uk_company = fields.id_name_partial_field()
uk_company_decided = Boolean()
uk_region_locations = fields.id_name_field()
will_new_jobs_last_two_years = Boolean()
level_of_involvement_simplified = Keyword()
gross_value_added = Double()
MAPPINGS = {
'actual_uk_regions':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'archived_by':
dict_utils.contact_or_adviser_dict,
'associated_non_fdi_r_and_d_project':
dict_utils.investment_project_dict,
'average_salary':
dict_utils.id_name_dict,
'business_activities':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'client_contacts':
lambda col: [dict_utils.contact_or_adviser_dict(c) for c in col.all()],
'client_relationship_manager':
dict_utils.adviser_dict_with_team,
'country_lost_to':
dict_utils.id_name_dict,
'country_investment_originates_from':
dict_utils.id_name_dict,
'created_by':
dict_utils.adviser_dict_with_team,
'delivery_partners':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'fdi_type':
dict_utils.id_name_dict,
'fdi_value':
dict_utils.id_name_dict,
'intermediate_company':
dict_utils.id_name_dict,
'investment_type':
dict_utils.id_name_dict,
'investor_company':
dict_utils.id_name_dict,
'investor_company_country':
dict_utils.id_name_dict,
'investor_type':
dict_utils.id_name_dict,
'level_of_involvement':
dict_utils.id_name_dict,
'likelihood_to_land':
dict_utils.id_name_dict,
'project_assurance_adviser':
dict_utils.adviser_dict_with_team,
'project_code':
str,
'project_manager':
dict_utils.adviser_dict_with_team,
'referral_source_activity':
dict_utils.id_name_dict,
'referral_source_activity_marketing':
dict_utils.id_name_dict,
'referral_source_activity_website':
dict_utils.id_name_dict,
'referral_source_adviser':
dict_utils.contact_or_adviser_dict,
'sector':
dict_utils.sector_dict,
'specific_programme':
dict_utils.id_name_dict,
'stage':
dict_utils.id_name_dict,
'team_members':
lambda col: [
dict_utils.contact_or_adviser_dict(c.adviser,
include_dit_team=True)
for c in col.all()
],
'uk_company':
dict_utils.id_name_dict,
'uk_region_locations':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
}
SEARCH_FIELDS = (
'id',
'name',
'name.trigram',
'uk_company.name',
'uk_company.name.trigram',
'investor_company.name',
'investor_company.name.trigram',
'project_code.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class Company(BaseESModel):
"""Elasticsearch representation of Company model."""
id = Keyword()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
business_type = fields.id_name_field()
companies_house_data = fields.ch_company_field()
company_number = fields.NormalizedKeyword()
created_on = Date()
description = fields.EnglishText()
employee_range = fields.id_name_field()
export_experience_category = fields.id_name_field()
export_to_countries = fields.id_name_field()
future_interest_countries = fields.id_name_field()
global_headquarters = fields.id_name_field()
headquarter_type = fields.id_name_field()
modified_on = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
reference_code = fields.NormalizedKeyword()
sector = fields.sector_field()
address = fields.address_field()
registered_address = fields.address_field()
# TODO: delete once the migration to address and registered address is complete
registered_address_1 = Text()
registered_address_2 = Text()
registered_address_town = fields.NormalizedKeyword()
registered_address_county = Text()
registered_address_country = fields.id_name_partial_field()
registered_address_postcode = Text(copy_to=[
'registered_address_postcode_trigram',
], )
registered_address_postcode_trigram = fields.TrigramText()
trading_address_1 = Text()
trading_address_2 = Text()
trading_address_town = fields.NormalizedKeyword()
trading_address_county = Text()
trading_address_postcode = Text(
copy_to=['trading_address_postcode_trigram'], )
trading_address_postcode_trigram = fields.TrigramText()
trading_address_country = fields.id_name_partial_field()
trading_names = Text(copy_to=['trading_names_trigram'], )
trading_names_trigram = fields.TrigramText()
turnover_range = fields.id_name_field()
uk_region = fields.id_name_field()
uk_based = Boolean()
vat_number = Keyword(index=False)
duns_number = Keyword()
website = Text()
suggest = Completion()
COMPUTED_MAPPINGS = {
'suggest':
get_suggestions,
'address':
partial(dict_utils.address_dict, prefix='address'),
'registered_address':
partial(dict_utils.address_dict, prefix='registered_address'),
}
MAPPINGS = {
'archived_by':
dict_utils.contact_or_adviser_dict,
'business_type':
dict_utils.id_name_dict,
'companies_house_data':
dict_utils.ch_company_dict,
'employee_range':
dict_utils.id_name_dict,
'export_experience_category':
dict_utils.id_name_dict,
'export_to_countries':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'future_interest_countries':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'global_headquarters':
dict_utils.id_name_dict,
'headquarter_type':
dict_utils.id_name_dict,
'sector':
dict_utils.sector_dict,
# TODO: delete once the migration to address and registered address is complete
'registered_address_country':
dict_utils.id_name_dict,
'trading_address_country':
dict_utils.id_name_dict,
'turnover_range':
dict_utils.id_name_dict,
'uk_based':
bool,
'uk_region':
dict_utils.id_name_dict,
}
SEARCH_FIELDS = (
'id',
'name', # to find 2-letter words
'name.trigram',
'company_number',
'trading_names', # to find 2-letter words
'trading_names_trigram',
'reference_code',
'address.country.name.trigram',
'address.postcode.trigram',
'registered_address.country.name.trigram',
'registered_address.postcode.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class LargeCapitalOpportunity(BaseSearchModel):
"""OpenSearch representation of LargeCapitalOpportunity."""
id = Keyword()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
type = fields.id_unindexed_name_field()
description = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
uk_region_locations = fields.id_unindexed_name_field()
promoters = fields.company_field()
required_checks_conducted = fields.id_unindexed_name_field()
required_checks_conducted_by = fields.contact_or_adviser_field(
include_dit_team=True)
required_checks_conducted_on = Date()
lead_dit_relationship_manager = fields.contact_or_adviser_field(
include_dit_team=True)
other_dit_contacts = fields.contact_or_adviser_field(include_dit_team=True)
asset_classes = fields.id_unindexed_name_field()
opportunity_value_type = fields.id_unindexed_name_field()
opportunity_value = Long()
construction_risks = fields.id_unindexed_name_field()
total_investment_sought = Long()
current_investment_secured = Long()
investment_types = fields.id_unindexed_name_field()
estimated_return_rate = fields.id_unindexed_name_field()
time_horizons = fields.id_unindexed_name_field()
investment_projects = fields.id_unindexed_name_field()
status = fields.id_unindexed_name_field()
sources_of_funding = fields.id_unindexed_name_field()
dit_support_provided = Boolean()
reasons_for_abandonment = fields.id_unindexed_name_field()
created_by = fields.contact_or_adviser_field(include_dit_team=True)
created_on = Date()
modified_on = Date()
_MAIN_FIELD_MAPPINGS = {
'type': dict_utils.id_name_dict,
'status': dict_utils.id_name_dict,
'created_by': dict_utils.adviser_dict_with_team,
}
_DETAIL_FIELD_MAPPINGS = {
'uk_region_locations': _get_many_to_many_list,
'promoters': _get_company_list,
'required_checks_conducted': dict_utils.id_name_dict,
'required_checks_conducted_by': dict_utils.adviser_dict_with_team,
'lead_dit_relationship_manager': dict_utils.adviser_dict_with_team,
'other_dit_contacts': _get_adviser_list,
'asset_classes': _get_many_to_many_list,
'opportunity_value_type': dict_utils.id_name_dict,
'construction_risks': _get_many_to_many_list,
'investment_projects': _get_investment_project_list,
'sources_of_funding': _get_many_to_many_list,
'reasons_for_abandonment': _get_many_to_many_list,
}
_REQUIREMENT_FIELD_MAPPINGS = {
'investment_types': _get_many_to_many_list,
'estimated_return_rate': dict_utils.id_name_dict,
'time_horizons': _get_many_to_many_list,
}
MAPPINGS = {
**_MAIN_FIELD_MAPPINGS,
**_DETAIL_FIELD_MAPPINGS,
**_REQUIREMENT_FIELD_MAPPINGS,
}
class Contact(BaseSearchModel):
"""OpenSearch representation of Contact model."""
id = Keyword()
address_1 = Text()
address_2 = Text()
address_town = fields.NormalizedKeyword()
address_county = fields.NormalizedKeyword()
address_postcode = Text()
address_country = fields.id_name_field()
address_area = fields.id_name_field()
address_same_as_company = Boolean()
adviser = fields.contact_or_adviser_field()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
company = fields.company_field()
company_sector = fields.sector_field()
company_uk_region = fields.id_name_field()
created_by = fields.contact_or_adviser_field(include_dit_team=True)
created_on = Date()
email = fields.NormalizedKeyword()
first_name = Text(fields={
'keyword': fields.NormalizedKeyword(),
}, )
job_title = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
last_name = Text(fields={
'keyword': fields.NormalizedKeyword(),
}, )
modified_on = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
name_with_title = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
notes = fields.EnglishText()
primary = Boolean()
full_telephone_number = Keyword()
title = fields.id_name_field()
MAPPINGS = {
'adviser': dict_utils.contact_or_adviser_dict,
'archived_by': dict_utils.contact_or_adviser_dict,
'company': dict_utils.company_dict,
'created_by': dict_utils.adviser_dict_with_team,
'title': dict_utils.id_name_dict,
}
COMPUTED_MAPPINGS = {
'address_1':
contact_dict_utils.computed_address_field('address_1'),
'address_2':
contact_dict_utils.computed_address_field('address_2'),
'address_town':
contact_dict_utils.computed_address_field('address_town'),
'address_county':
contact_dict_utils.computed_address_field('address_county'),
'address_postcode':
contact_dict_utils.computed_address_field('address_postcode'),
'address_country':
contact_dict_utils.computed_address_field('address_country'),
'address_area':
contact_dict_utils.computed_address_field('address_area'),
'company_sector':
dict_utils.computed_nested_sector_dict('company.sector'),
'company_uk_region':
dict_utils.computed_nested_id_name_dict('company.uk_region'),
}
SEARCH_FIELDS = (
'id',
'name',
'name.trigram',
'name_with_title',
'name_with_title.trigram',
'email',
'company.name',
'company.name.trigram',
'job_title',
'job_title.trigram',
'full_telephone_number',
)
class Order(BaseESModel):
"""Elasticsearch representation of Order model."""
id = Keyword()
reference = fields.NormalizedKeyword(copy_to=['reference_trigram'])
reference_trigram = fields.TrigramText()
status = fields.NormalizedKeyword()
company = fields.company_field()
contact = fields.contact_or_adviser_field()
created_by = fields.contact_or_adviser_field(include_dit_team=True)
created_on = Date()
modified_on = Date()
primary_market = fields.id_name_field()
sector = fields.sector_field()
uk_region = fields.id_name_field()
description = fields.EnglishText()
contacts_not_to_approach = Text()
further_info = Text()
existing_agents = Text(index=False)
delivery_date = Date()
service_types = fields.id_name_field()
contact_email = fields.NormalizedKeyword()
contact_phone = Keyword()
subscribers = fields.contact_or_adviser_field(include_dit_team=True)
assignees = fields.contact_or_adviser_field(include_dit_team=True)
po_number = Keyword(index=False)
discount_value = Integer(index=False)
vat_status = Keyword(index=False)
vat_number = Keyword(index=False)
vat_verified = Boolean(index=False)
net_cost = Integer(index=False)
subtotal_cost_string = Keyword()
subtotal_cost = Integer(copy_to=['subtotal_cost_string'])
vat_cost = Integer(index=False)
total_cost_string = Keyword()
total_cost = Integer(copy_to=['total_cost_string'])
payment_due_date = Date()
paid_on = Date()
completed_by = fields.contact_or_adviser_field()
completed_on = Date()
cancelled_by = fields.contact_or_adviser_field()
cancelled_on = Date()
cancellation_reason = fields.id_name_field()
billing_company_name = Text()
billing_contact_name = Text()
billing_email = fields.NormalizedKeyword()
billing_phone = fields.NormalizedKeyword()
billing_address_1 = Text()
billing_address_2 = Text()
billing_address_town = fields.NormalizedKeyword()
billing_address_county = fields.NormalizedKeyword()
billing_address_postcode = Text()
billing_address_country = fields.id_name_field()
MAPPINGS = {
'company':
dict_utils.company_dict,
'contact':
dict_utils.contact_or_adviser_dict,
'created_by':
dict_utils.adviser_dict_with_team,
'primary_market':
dict_utils.id_name_dict,
'sector':
dict_utils.sector_dict,
'uk_region':
dict_utils.id_name_dict,
'service_types':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'subscribers':
lambda col: [
dict_utils.contact_or_adviser_dict(c.adviser,
include_dit_team=True)
for c in col.all()
],
'assignees':
lambda col: [
dict_utils.contact_or_adviser_dict(c.adviser,
include_dit_team=True)
for c in col.all()
],
'billing_address_country':
dict_utils.id_name_dict,
'completed_by':
dict_utils.contact_or_adviser_dict,
'cancelled_by':
dict_utils.contact_or_adviser_dict,
'cancellation_reason':
dict_utils.id_name_dict,
}
COMPUTED_MAPPINGS = {
'payment_due_date':
lambda x: x.invoice.payment_due_date if x.invoice else None,
}
SEARCH_FIELDS = (
'id',
'reference_trigram',
'company.name',
'company.name.trigram',
'contact.name',
'contact.name.trigram',
'total_cost_string',
'subtotal_cost_string',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class Event(BaseESModel):
"""Elasticsearch representation of Event model."""
id = Keyword()
address_1 = Text()
address_2 = Text()
address_town = fields.NormalizedKeyword()
address_county = fields.NormalizedKeyword()
address_postcode = fields.TextWithTrigram()
address_country = fields.id_name_partial_field()
created_on = Date()
disabled_on = Date()
end_date = Date()
event_type = fields.id_name_field()
lead_team = fields.id_name_field()
location_type = fields.id_name_field()
modified_on = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
notes = fields.EnglishText()
organiser = fields.contact_or_adviser_field()
related_programmes = fields.id_name_partial_field()
service = fields.id_name_field()
start_date = Date()
teams = fields.id_name_partial_field()
uk_region = fields.id_name_partial_field()
MAPPINGS = {
'address_country':
dict_utils.id_name_dict,
'event_type':
dict_utils.id_name_dict,
'lead_team':
dict_utils.id_name_dict,
'location_type':
dict_utils.id_name_dict,
'organiser':
dict_utils.contact_or_adviser_dict,
'related_programmes':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'service':
dict_utils.id_name_dict,
'teams':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'uk_region':
dict_utils.id_name_dict,
}
COMPUTED_MAPPINGS = {}
SEARCH_FIELDS = (
'id',
'name',
'name.trigram',
'address_country.name.trigram',
'address_postcode.trigram',
'uk_region.name.trigram',
'organiser.name.trigram',
'teams.name',
'teams.name.trigram',
'related_programmes.name',
'related_programmes.name.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DEFAULT_MAPPING_TYPE
class Index:
doc_type = DEFAULT_MAPPING_TYPE
class Company(BaseESModel):
"""Elasticsearch representation of Company model."""
id = Keyword()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
business_type = fields.id_name_field()
company_number = fields.NormalizedKeyword()
created_on = Date()
description = fields.EnglishText()
employee_range = fields.id_name_field()
export_experience_category = fields.id_name_field()
export_to_countries = fields.id_name_field()
future_interest_countries = fields.id_name_field()
global_headquarters = fields.id_name_field()
headquarter_type = fields.id_name_field()
modified_on = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
reference_code = fields.NormalizedKeyword()
sector = fields.sector_field()
address = fields.address_field()
registered_address = fields.address_field()
one_list_group_global_account_manager = _adviser_field_with_indexed_id()
trading_names = fields.TextWithTrigram()
turnover_range = fields.id_name_field()
uk_region = fields.id_name_field()
uk_based = Boolean()
uk_address_postcode = fields.PostcodeKeyword()
uk_registered_address_postcode = fields.PostcodeKeyword()
vat_number = Keyword(index=False)
duns_number = Keyword()
website = Text()
suggest = Completion(contexts=[
{
'name': 'country',
'type': 'category',
},
], )
latest_interaction_date = Date()
COMPUTED_MAPPINGS = {
'suggest':
get_suggestions,
'address':
partial(dict_utils.address_dict, prefix='address'),
'registered_address':
partial(dict_utils.address_dict, prefix='registered_address'),
'one_list_group_global_account_manager':
dict_utils.computed_field_function(
'get_one_list_group_global_account_manager',
dict_utils.contact_or_adviser_dict,
),
'latest_interaction_date':
lambda obj: obj.latest_interaction_date,
'uk_address_postcode':
lambda obj: obj.address_postcode if obj.uk_based else '',
'uk_registered_address_postcode':
lambda obj: obj.registered_address_postcode if obj.uk_based else '',
}
MAPPINGS = {
'archived_by':
dict_utils.contact_or_adviser_dict,
'business_type':
dict_utils.id_name_dict,
'employee_range':
dict_utils.id_name_dict,
'export_experience_category':
dict_utils.id_name_dict,
'export_to_countries':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'future_interest_countries':
lambda col: [dict_utils.id_name_dict(c) for c in col.all()],
'global_headquarters':
dict_utils.id_name_dict,
'headquarter_type':
dict_utils.id_name_dict,
'sector':
dict_utils.sector_dict,
'turnover_range':
dict_utils.id_name_dict,
'uk_based':
bool,
'uk_region':
dict_utils.id_name_dict,
}
SEARCH_FIELDS = (
'id',
'name', # to find 2-letter words
'name.trigram',
'company_number',
'trading_names', # to find 2-letter words
'trading_names.trigram',
'reference_code',
'address.country.name.trigram',
'address.postcode.trigram',
'registered_address.country.name.trigram',
'registered_address.postcode.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DOC_TYPE
class Index:
doc_type = DOC_TYPE
class Company(BaseSearchModel):
"""
OpenSearch representation of Company model.
"""
id = Keyword()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
business_type = fields.id_name_field()
company_number = fields.NormalizedKeyword()
created_on = Date()
description = fields.EnglishText()
employee_range = fields.id_name_field()
export_experience_category = fields.id_name_field()
export_to_countries = fields.id_name_field()
future_interest_countries = fields.id_name_field()
global_headquarters = fields.id_name_field()
headquarter_type = fields.id_name_field()
modified_on = Date()
name = Text(
fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
},
)
reference_code = fields.NormalizedKeyword()
sector = fields.sector_field()
address = fields.address_field()
registered_address = fields.address_field()
one_list_group_global_account_manager = _adviser_field_with_indexed_id()
trading_names = fields.TextWithTrigram()
turnover_range = fields.id_name_field()
uk_region = fields.id_name_field()
uk_based = Boolean()
uk_address_postcode = fields.PostcodeKeyword()
uk_registered_address_postcode = fields.PostcodeKeyword()
vat_number = Keyword(index=False)
duns_number = Keyword()
website = Text()
latest_interaction_date = Date()
export_segment = Text()
export_sub_segment = Text()
COMPUTED_MAPPINGS = {
'address': partial(dict_utils.address_dict, prefix='address'),
'registered_address': partial(dict_utils.address_dict, prefix='registered_address'),
'one_list_group_global_account_manager': dict_utils.computed_field_function(
'get_one_list_group_global_account_manager',
dict_utils.contact_or_adviser_dict,
),
'export_to_countries': lambda obj: [
dict_utils.id_name_dict(o.country) for o in obj.export_countries.all()
if o.status == CompanyExportCountry.Status.CURRENTLY_EXPORTING
],
'future_interest_countries': lambda obj: [
dict_utils.id_name_dict(o.country) for o in obj.export_countries.all()
if o.status == CompanyExportCountry.Status.FUTURE_INTEREST
],
'latest_interaction_date': lambda obj: obj.latest_interaction_date,
'uk_address_postcode': lambda obj: obj.address_postcode if obj.uk_based else '',
'uk_registered_address_postcode':
lambda obj: obj.registered_address_postcode if obj.uk_based else '',
}
MAPPINGS = {
'archived_by': dict_utils.contact_or_adviser_dict,
'business_type': dict_utils.id_name_dict,
'employee_range': dict_utils.id_name_dict,
'export_experience_category': dict_utils.id_name_dict,
'global_headquarters': dict_utils.id_name_dict,
'headquarter_type': dict_utils.id_name_dict,
'sector': dict_utils.sector_dict,
'turnover_range': dict_utils.id_name_dict,
'uk_based': bool,
'uk_region': dict_utils.id_name_dict,
}
SEARCH_FIELDS = (
'id',
'name', # to find 2-letter words
'name.trigram',
'company_number',
'trading_names', # to find 2-letter words
'trading_names.trigram',
'reference_code',
'sector.name',
'address.line_1.trigram',
'address.line_2.trigram',
'address.town.trigram',
'address.county.trigram',
'address.area.name.trigram',
'address.postcode',
'address.country.name.trigram',
'registered_address.line_1.trigram',
'registered_address.line_2.trigram',
'registered_address.town.trigram',
'registered_address.county.trigram',
'registered_address.area.name.trigram',
'registered_address.postcode',
'registered_address.country.name.trigram',
)
class Contact(BaseESModel):
"""Elasticsearch representation of Contact model."""
id = Keyword()
address_1 = Text()
address_2 = Text()
address_town = fields.NormalizedKeyword()
address_county = fields.NormalizedKeyword()
address_postcode = Text()
address_country = fields.id_name_field()
address_same_as_company = Boolean()
adviser = fields.contact_or_adviser_field()
archived = Boolean()
archived_by = fields.contact_or_adviser_field()
archived_on = Date()
archived_reason = Text()
company = fields.company_field()
company_sector = fields.sector_field()
company_uk_region = fields.id_name_field()
created_by = fields.contact_or_adviser_field(include_dit_team=True)
created_on = Date()
email = fields.NormalizedKeyword()
email_alternative = Text()
first_name = Text(fields={
'keyword': fields.NormalizedKeyword(),
}, )
job_title = fields.NormalizedKeyword()
last_name = Text(fields={
'keyword': fields.NormalizedKeyword(),
}, )
modified_on = Date()
name = Text(fields={
'keyword': fields.NormalizedKeyword(),
'trigram': fields.TrigramText(),
}, )
notes = fields.EnglishText()
primary = Boolean()
telephone_alternative = Text()
telephone_countrycode = Keyword()
telephone_number = Keyword()
title = fields.id_name_field()
MAPPINGS = {
'adviser': dict_utils.contact_or_adviser_dict,
'archived_by': dict_utils.contact_or_adviser_dict,
'company': dict_utils.company_dict,
'created_by': dict_utils.adviser_dict_with_team,
'title': dict_utils.id_name_dict,
}
COMPUTED_MAPPINGS = {
'address_1':
contact_dict_utils.computed_address_field('address_1'),
'address_2':
contact_dict_utils.computed_address_field('address_2'),
'address_town':
contact_dict_utils.computed_address_field('address_town'),
'address_county':
contact_dict_utils.computed_address_field('address_county'),
'address_postcode':
contact_dict_utils.computed_address_field('address_postcode'),
'address_country':
contact_dict_utils.computed_address_field('address_country'),
'company_sector':
dict_utils.computed_nested_sector_dict('company.sector'),
'company_uk_region':
dict_utils.computed_nested_id_name_dict('company.uk_region'),
}
SEARCH_FIELDS = (
'id',
'name',
'name.trigram',
'email',
'email_alternative',
'company.name',
'company.name.trigram',
)
class Meta:
"""Default document meta data."""
doc_type = DEFAULT_MAPPING_TYPE
class Index:
doc_type = DEFAULT_MAPPING_TYPE
