class PageHit(DocType):
doc_id = Long()
fc_user_id = Long()
product_id = Long()
permissions = Long(multi=True)
access_time = Date()
origin_ip = Ip()
request_type = Text()
uri = Text()
page_number = Long()
is_full = Boolean()
is_known_article = Boolean()
is_known_product = Boolean()
class Meta:
index = 'hits'
def save(self, **kwargs):
return super(PageHit, self).save(**kwargs)
@classmethod
def properties(cls):
props = PageHit._doc_type.mapping.properties.to_dict(
)['doc']['properties'].keys()
return [prop for prop in props]
class Facebook(DataHead):
group_detail_list = ['id', 'cover', 'description', 'name']
post_extra_data = ['id', 'message', 'updated_time', 'permalink_url']
keywords = Keyword(multi=True)
group_name = Text()
post_date = Date()
extra_data = Nested()
group_extra_data = Nested(
properties=dict(map(lambda x: (x, Text()), group_detail_list)))
class Pipeline_Document(Base_Document):
"""Represents the stored pipelines."""
# id already defined by Elasticsearch
# updated_at = Date() #FIXME long format not compatible with date
# created_at = Date(required=True) #FIXME long format not compatible with date
name = Text()
status = Text(required=True)
user = Text()
class Index:
"""Elasticsearch configuration."""
name = 'pipeline'
class Movie(Document):
title = Text(fields={'raw': {'type': 'keyword'}})
film_rating = Text()
duration = Text()
genre = Keyword(multi=True)
release_date = Text()
release_date_unix_time = Float()
imdb_ratingValue = Float()
imdb_bestRating = Float()
imdb_ratingCount = Float()
description = Text()
storyline = Text()
poster = Text()
trailer_img = Text()
director = Keyword(multi=True)
creator = Keyword(multi=True)
writer = Keyword(multi=True)
stars = Keyword(multi=True)
taglines = Keyword(multi=True)
url = Keyword()
req_headers = Object(enabled=False)
res_headers = Object(enabled=False)
suggest = Completion(analyzer=ngram_analyzer,
search_analyzer=analyzer('standard'))
class Index:
name = 'imdb'
class Movie(DocType):
title = Text(fields={'raw': {'type': 'keyword'}})
summary = Text()
datePublished = Date()
creators = Keyword(multi=True)
genres = Keyword(multi=True)
casts = Keyword(multi=True)
time = Integer()
countries = Keyword(multi=True)
plot_keywords = Keyword(multi=True)
languages = Keyword(multi=True)
rating = Float()
poster = Keyword()
suggest = Completion(analyzer=ngram_analyzer,
search_analyzer=analyzer('standard'))
class Meta:
index = 'imdb'
def get_es_mapping(cls):
es_mapping = super(Topic, cls).get_es_mapping()
es_mapping.field('title', Text(boost=1.5))
es_mapping.field('tags', Text(boost=2.0))
es_mapping.field('subtitle', Text())
es_mapping.field('is_solved', Boolean())
es_mapping.field('is_locked', Boolean())
es_mapping.field('is_sticky', Boolean())
es_mapping.field('pubdate', Date())
es_mapping.field('forum_pk', Integer())
# not indexed:
es_mapping.field('get_absolute_url', Keyword(index=False))
es_mapping.field('forum_title', Text(index=False))
es_mapping.field('forum_get_absolute_url', Keyword(index=False))
return es_mapping
def get_es_mapping(cls):
es_mapping = super(Topic, cls).get_es_mapping()
es_mapping.field("title", Text(boost=1.5))
es_mapping.field("tags", Text(boost=2.0))
es_mapping.field("subtitle", Text())
es_mapping.field("is_solved", Boolean())
es_mapping.field("is_locked", Boolean())
es_mapping.field("is_sticky", Boolean())
es_mapping.field("pubdate", Date())
es_mapping.field("forum_pk", Integer())
# not indexed:
es_mapping.field("get_absolute_url", Keyword(index=False))
es_mapping.field("forum_title", Text(index=False))
es_mapping.field("forum_get_absolute_url", Keyword(index=False))
return es_mapping
def get_es_mapping(cls):
es_mapping = super(Post, cls).get_es_mapping()
es_mapping.field('text_html', Text())
es_mapping.field('is_useful', Boolean())
es_mapping.field('is_visible', Boolean())
es_mapping.field('position', Integer())
es_mapping.field('like_dislike_ratio', Float())
es_mapping.field('pubdate', Date())
es_mapping.field('forum_pk', Integer())
es_mapping.field('topic_pk', Integer())
# not indexed:
es_mapping.field('get_absolute_url', Keyword(index=False))
es_mapping.field('topic_title', Text(index=False))
es_mapping.field('forum_title', Text(index=False))
es_mapping.field('forum_get_absolute_url', Keyword(index=False))
return es_mapping
def get_es_mapping(cls):
es_mapping = super(Post, cls).get_es_mapping()
es_mapping.field("text_html", Text())
es_mapping.field("is_useful", Boolean())
es_mapping.field("is_visible", Boolean())
es_mapping.field("position", Integer())
es_mapping.field("like_dislike_ratio", Float())
es_mapping.field("pubdate", Date())
es_mapping.field("forum_pk", Integer())
es_mapping.field("topic_pk", Integer())
# not indexed:
es_mapping.field("get_absolute_url", Keyword(index=False))
es_mapping.field("topic_title", Text(index=False))
es_mapping.field("forum_title", Text(index=False))
es_mapping.field("forum_get_absolute_url", Keyword(index=False))
return es_mapping
class ApplicationDocumentType(Document):
# purposefully not DED field - this is just for collecting other field values for wilcard search
wildcard = Text(analyzer=ngram_analyzer, search_analyzer=whitespace_analyzer, store=True)
id = fields.KeywordField()
queues = fields.NestedField(doc_class=Queue)
name = fields.TextField(copy_to="wildcard", analyzer=descriptive_text_analyzer)
reference_code = fields.TextField(
copy_to="wildcard",
analyzer=reference_code_analyzer,
fields={"raw": fields.KeywordField(normalizer=lowercase_normalizer), "suggest": fields.CompletionField(),},
)
organisation = fields.TextField(
copy_to="wildcard",
attr="organisation.name",
analyzer=descriptive_text_analyzer,
fields={"raw": fields.KeywordField(normalizer=lowercase_normalizer), "suggest": fields.CompletionField(),},
)
status = fields.KeywordField(
attr="status.status",
fields={"raw": fields.KeywordField(normalizer=lowercase_normalizer), "suggest": fields.CompletionField(),},
)
submitted_by = fields.ObjectField(doc_class=User)
case_officer = fields.NestedField(doc_class=User)
goods = fields.NestedField(doc_class=Product)
parties = fields.NestedField(doc_class=Party)
created = fields.DateField(attr="created_at")
updated = fields.DateField(attr="updated_at")
case_type = fields.KeywordField(
attr="case_type.type",
fields={"raw": fields.KeywordField(normalizer=lowercase_normalizer), "suggest": fields.CompletionField(),},
)
case_subtype = fields.KeywordField(
attr="case_type.sub_type",
fields={"raw": fields.KeywordField(normalizer=lowercase_normalizer), "suggest": fields.CompletionField(),},
)
class Index:
name = settings.ELASTICSEARCH_APPLICATION_INDEX_ALIAS
settings = {"number_of_shards": 1, "number_of_replicas": 0, "max_ngram_diff": 18}
class Meta:
model = models.BaseApplication
class Django:
model = models.BaseApplication
def get_queryset(self):
return super().get_queryset().exclude(status__status="draft")
def get_indexing_queryset(self):
# hack to make `parties` use the prefetch cache. party manager .all() calls .exclude, which clears cache,
# so work around that here: read from the instance's prefetched_parties attr, which was set in prefetch
# looks small, but is a huge performance improvement. Helps take db reads down to 7 in total.
self._fields["parties"]._path = ["prefetched_parties"]
return (
self.get_queryset()
.select_related("organisation")
.select_related("submitted_by__baseuser_ptr")
.select_related("case_officer__baseuser_ptr")
.select_related("status")
.select_related("case_type")
.prefetch_related("queues")
.prefetch_related("queues__team")
.prefetch_related(
Prefetch(
"goods",
queryset=(
models.GoodOnApplication.objects.all()
.select_related("good")
.select_related("good__organisation")
.prefetch_related("good__control_list_entries")
.prefetch_related("good__control_list_entries__parent")
),
)
)
.prefetch_related(
Prefetch(
"parties",
to_attr="prefetched_parties",
queryset=(
models.PartyOnApplication.objects.all()
.select_related("party")
.select_related("party__country")
.select_related("party__organisation")
),
)
)
)
class ProductDocumentType(Document):
# purposefully not DED field - this is just for collecting other field values for wilcard search
wildcard = Text(
analyzer=ngram_analyzer,
search_analyzer=whitespace_analyzer,
store=True,
)
# purposefully not DED field - this is just for collecting other field values for grouping purposes in ES
context = fields.Keyword()
# used for grouping
canonical_name = fields.KeywordField(
attr="good.description") # is overwritten in prepare
# base details. iteration 1
id = fields.KeywordField()
description = fields.TextField(
attr="good.description",
copy_to="wildcard",
analyzer=descriptive_text_analyzer,
)
control_list_entries = fields.NestedField(attr="good.control_list_entries",
doc_class=Rating)
queues = fields.NestedField(doc_class=Queue, attr="application.queues")
organisation = fields.TextField(
copy_to="wildcard",
attr="good.organisation.name",
analyzer=descriptive_text_analyzer,
fields={
"raw": fields.KeywordField(normalizer=lowercase_normalizer),
"suggest": fields.CompletionField(),
},
)
# does not exist yet). needs to be here for data shape parity with SPIRE
name = fields.TextField(attr="good.description")
# not mapped yet
destination = fields.KeywordField(
attr="application.end_user.party.country.name",
fields={
"raw": fields.KeywordField(normalizer=lowercase_normalizer),
"suggest": fields.CompletionField(),
},
normalizer=lowercase_normalizer,
)
end_use = fields.TextField(attr="application.intended_end_use")
end_user_type = fields.KeywordField(
attr="application.end_user.party.sub_type",
normalizer=lowercase_normalizer,
)
organisation = fields.TextField(
copy_to="wildcard",
attr="good.organisation.name",
analyzer=descriptive_text_analyzer,
fields={
"raw": fields.KeywordField(normalizer=lowercase_normalizer),
"suggest": fields.CompletionField(),
},
)
date = fields.DateField(attr="application.submitted_at")
application = fields.NestedField(doc_class=ApplicationOnProduct)
rating_comment = fields.TextField(attr="good.comment",
copy_to="wildcard",
analyzer=descriptive_text_analyzer)
report_summary = fields.TextField(
attr="good.report_summary",
fields={
"raw": fields.KeywordField(normalizer=lowercase_normalizer),
"suggest": fields.CompletionField(),
},
analyzer=descriptive_text_analyzer,
copy_to="wildcard",
)
part_number = fields.TextField(
attr="good.part_number",
fields={
"raw": fields.KeywordField(normalizer=lowercase_normalizer),
"suggest": fields.CompletionField(),
},
analyzer=part_number_analyzer,
copy_to="wildcard",
)
regime = fields.Keyword()
class Index:
name = settings.ELASTICSEARCH_PRODUCT_INDEX_ALIAS
settings = {
"number_of_shards": 1,
"number_of_replicas": 0,
"max_ngram_diff": 18,
}
class Meta:
model = models.GoodOnApplication
class Django:
model = models.GoodOnApplication
def get_queryset(self):
return super().get_queryset().exclude(
application__status__status="draft")
def prepare(self, instance):
data = super().prepare(instance)
data[
"context"] = f"{data['destination']}🔥{data['end_use']}🔥{data['end_user_type']}"
data["canonical_name"] = data["description"]
return data
def get_indexing_queryset(self):
return (self.get_queryset().select_related("good").select_related(
"application").select_related("good__organisation").
prefetch_related("application__parties__party__flags"))
class MXXZjacDoc(DocType):
caseId = Keyword()
ctime = Keyword()
timeStamp = Keyword()
applicant = Keyword()
respondent = Nested(doc_class=InnerObjectWrapper,
properties={
"name": Keyword(),
"certAddress": Keyword(),
"phone": Keyword(),
"email": Keyword(),
"otherAddress": Keyword(),
"idcard": Keyword(),
"card_front": Text(),
"card_nfront": Text(),
})
text = """
借款年利率:Annual interest rate of borrowing
合同金额:Contract amount
放款金额:Loan amount
合同签订时间:
借款开始时间:Borrowing start time
借款结束时间:End of loan time
借款时常:Borrowing often
借款时长单位:Borrowing time unit
违约时间:Default time
尚欠本金:Still owed principal
尚欠利息:Interest owed
仲裁协议签订时间:Arbitration agreement time
是否分期（分批）:Whether to stage (batch)
居间方:Intermediary party
借款用途:Use of the loan
还款方式:Repayment
是否涉外:Whether it is foreign-related
"""
caseInfo = Object(doc_class=InnerObjectWrapper,
properties={
"annualInterestOfBorrowing": Float(),
"contractAmount": Float(),
"loanAmount": Float(),
"contractTime ": Keyword(),
"borrowingStartTime": Keyword(),
"borrowingEndTime": Keyword(),
"borrowingOften": Integer(),
"borrowingTimeUnit": Keyword(),
"defaultTime": Keyword(),
"stillOwedPrincipal": Float(),
"interestOwed": Float(),
"arbitrationAgreementTime": Keyword(),
"whetherStaging": Keyword(),
"intermediaryParty": Keyword(),
"usageLoan": Keyword(),
"repaymentWay": Keyword(),
"whetherForeign": Keyword(),
})
contentiousAmount = Float()
class Meta:
index = config.ES_INDEX
doc_type = config.ES_DOC_TYPE
@classmethod
def make_doc(cls, caseId, ctime, timeStamp, applicant, respondent,
caseInfo, contentiousAmount):
doc_obj = cls()
doc_obj.meta.id = caseId
doc_obj.caseId = caseId
doc_obj.ctime = ctime
doc_obj.timeStamp = timeStamp
doc_obj.applicant = applicant
doc_obj.respondent = respondent
doc_obj.respondent = caseInfo
doc_obj.respondent = contentiousAmount
doc_obj.save()
return doc_obj.to_dict(include_meta=False)
