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
def test_address_field(index_country, expected_mapping):
"""Test for address_field."""
field_mapping = address_field(index_country=index_country)
assert field_mapping.to_dict() == expected_mapping
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 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
def test_address_field():
"""Test for address_field."""
field_mapping = address_field()
assert field_mapping.to_dict() == {
'type': 'object',
'properties': {
'line_1': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
'line_2': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
'town': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
'county': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
'area': {
'type': 'object',
'properties': {
'id': {
'type': 'keyword'
},
'name': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
},
},
'postcode': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
'country': {
'type': 'object',
'properties': {
'id': {
'type': 'keyword'
},
'name': {
'type': 'text',
'fields': {
'trigram': {
'type': 'text',
'analyzer': 'trigram_analyzer',
},
},
},
},
},
},
}
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',
)