def entities_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
if text is None or not len(text):
q = match_all()
else:
q = {
"query_string": {
"query":
text,
"fields": [
'name^15', 'name_latin^5', 'terms^12', 'terms_latin^3',
'summary^10', 'summary_latin^7', 'description^5',
'description_latin^3'
],
"default_operator":
"AND",
"use_dis_max":
True
}
}
q = authz_filter(q)
filters = parse_filters(args)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
aggs = aggregate(q, aggs, facets)
sort_mode = args.get('sort', '').strip().lower()
default_sort = 'score' if len(text) else 'doc_count'
sort_mode = sort_mode or default_sort
if sort_mode == 'doc_count':
sort = [{'doc_count': 'desc'}, '_score']
elif sort_mode == 'alphabet':
sort = [{'name': 'asc'}, '_score']
elif sort_mode == 'score':
sort = ['_score']
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
def documents_query(args, fields=None, facets=True, escape=True):
"""Parse a user query string, compose and execute a query.
Escape -- filter input so it can be safely used in an ES query string
"""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
if escape:
text = escape_query_string(text)
q = text_query(text)
q = authz_sources_filter(q)
# Sorting -- should this be passed into search directly, instead of
# these aliases?
sort_mode = args.get('sort', '').strip().lower()
if sort_mode == 'score':
sort = ['_score']
elif sort_mode == 'newest_filed':
sort = [{'filing_date': 'desc'}]
elif sort_mode == 'oldest_filed':
sort = [{'filing_date': 'asc'}]
elif sort_mode == 'newest_added':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
elif sort_mode == 'oldest_added':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = [{'updated_at': 'desc'}, {'created_at': 'desc'}, '_score']
filters = parse_filters(args)
for entity in args.getlist('entity'):
filters.append(('entities.uuid', entity))
aggs = {}
if facets:
aggs = aggregate(q, args)
aggs = facet_source(q, aggs, filters)
#aggs = facet_sector(q, aggs, filters)
q = entity_collections(q, aggs, args, filters)
# XXX this is where I should be hooking in openoil aggregations
signals.document_query_process.send(q=q, args=args)
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
#'fields': fields or DEFAULT_FIELDS
}
def entities_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
if text is None or not len(text):
q = match_all()
else:
q = {
"query_string": {
"query": text,
"fields": ['name^15', 'name_latin^5',
'terms^12', 'terms_latin^3',
'summary^10', 'summary_latin^7',
'description^5', 'description_latin^3'],
"default_operator": "AND",
"use_dis_max": True
}
}
q = authz_filter(q)
filters = parse_filters(args)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
aggs = aggregate(q, aggs, facets)
sort_mode = args.get('sort', '').strip().lower()
default_sort = 'score' if len(text) else 'doc_count'
sort_mode = sort_mode or default_sort
if sort_mode == 'doc_count':
sort = [{'doc_count': 'desc'}, '_score']
elif sort_mode == 'alphabet':
sort = [{'name': 'asc'}, '_score']
elif sort_mode == 'score':
sort = ['_score']
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
def links_query(origin, state):
"""Parse a user query string, compose and execute a query."""
if state.has_text:
q = {
"query_string": {
"query": state.text,
"fields": ['name^5', 'names^2', 'text'],
"default_operator": "AND",
"use_dis_max": True
}
}
else:
q = match_all()
ids = origin.get('ids') or [origin.get('id')]
q = add_filter(q, {'terms': {'origin.id': ids}})
q = authz_filter(q, state.authz, roles=True)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
aggs = aggregate(state, q, aggs, state.facet_names)
if state.sort == 'score':
sort = ['_score']
else:
sort = [{
'properties.start_date': 'desc'
}, {
'properties.end_date': 'desc'
}]
q = {
'sort': sort,
'query': filter_query(q, state.filters),
'aggregations': aggs,
'size': state.limit,
'from': state.offset,
'_source': DEFAULT_FIELDS
}
result, hits, output = execute_basic(TYPE_LINK, q)
output['facets'] = parse_facet_result(state, result)
for doc in hits.get('hits', []):
link = doc.get('_source')
link['id'] = doc.get('_id')
link['score'] = doc.get('_score')
output['results'].append(link)
return output
def leads_query(collection_id, state):
q = {'term': {'entity_collection_id': collection_id}}
q = authz_filter(q, state.authz, roles=True)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
facets = list(state.facet_names)
if 'collections' in facets:
aggs = facet_collections(state, q, aggs)
facets.remove('collections')
aggs = aggregate(state, q, aggs, facets)
q = {
'sort': [{
'judgement': 'asc'
}, {
'score': 'desc'
}, {
'match_id': 'asc'
}],
'query': filter_query(q, state.filters),
'aggregations': aggs,
'size': state.limit,
'from': state.offset
}
result, hits, output = execute_basic(TYPE_LEAD, q)
output['facets'] = parse_facet_result(state, result)
entities = set([])
for doc in hits.get('hits', []):
link = doc.get('_source')
link['id'] = doc.get('_id')
entities.add(link.get('entity_id'))
entities.add(link.get('match_id'))
output['results'].append(link)
q = {'terms': {'_id': list(entities)}}
q = {'query': q, 'size': len(entities) + 2}
_, hits, _ = execute_basic(TYPE_ENTITY, q)
for doc in hits.get('hits', []):
entity = doc.get('_source')
entity['id'] = doc.get('_id')
for result in output['results']:
if result.get('match_id') == entity['id']:
result['match'] = entity
if result.get('entity_id') == entity['id']:
result['entity'] = entity
return output
def documents_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
q = text_query(text)
q = authz_filter(q)
# Sorting -- should this be passed into search directly, instead of
# these aliases?
sort_mode = args.get('sort', '').strip().lower()
if text or sort_mode == 'score':
sort = ['_score']
elif sort_mode == 'newest':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
elif sort_mode == 'oldest':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = [{'updated_at': 'desc'}, {'created_at': 'desc'}, '_score']
filters = parse_filters(args)
for entity in args.getlist('entity'):
filters.append(('entities.id', entity))
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
if 'entities' in facets:
aggs = facet_entities(aggs, args)
facets.remove('entities')
aggs = aggregate(q, aggs, facets)
signals.document_query_process.send(q=q, args=args)
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
def documents_query(args, fields=None, facets=True):
"""Parse a user query string, compose and execute a query."""
if not isinstance(args, MultiDict):
args = MultiDict(args)
text = args.get('q', '').strip()
q = text_query(text)
q = authz_filter(q)
# Sorting -- should this be passed into search directly, instead of
# these aliases?
sort_mode = args.get('sort', '').strip().lower()
if text or sort_mode == 'score':
sort = ['_score']
elif sort_mode == 'newest':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
elif sort_mode == 'oldest':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = [{'updated_at': 'desc'}, {'created_at': 'desc'}, '_score']
filters = parse_filters(args)
for entity in args.getlist('entity'):
filters.append(('entities.id', entity))
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = args.getlist('facet')
if 'collections' in facets:
aggs = facet_collections(q, aggs, filters)
facets.remove('collections')
if 'entities' in facets:
aggs = facet_entities(aggs, args)
facets.remove('entities')
aggs = aggregate(q, aggs, facets)
signals.document_query_process.send(q=q, args=args)
return {
'sort': sort,
'query': filter_query(q, filters, OR_FIELDS),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
def entities_query(state, fields=None, facets=True, doc_counts=False):
"""Parse a user query string, compose and execute a query."""
if state.has_text:
q = {
"query_string": {
"query": state.text,
"fields": ['name^5', 'names^2', 'text'],
"default_operator": "AND",
"use_dis_max": True
}
}
else:
q = match_all()
if state.raw_query:
q = {"bool": {"must": [q, state.raw_query]}}
q = authz_filter(q, state.authz, roles=True)
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = list(state.facet_names)
if 'collections' in facets:
aggs = facet_collections(state, q, aggs)
facets.remove('collections')
aggs = aggregate(state, q, aggs, facets)
if state.sort == 'doc_count':
sort = [{'doc_count': 'desc'}, '_score']
elif state.sort == 'score':
sort = ['_score', {'name_sort': 'asc'}]
else:
sort = [{'name_sort': 'asc'}]
# pprint(q)
q = {
'sort': sort,
'query': filter_query(q, state.filters),
'aggregations': aggs,
'size': state.limit,
'from': state.offset,
'_source': fields or DEFAULT_FIELDS
}
result, hits, output = execute_basic(TYPE_ENTITY, q)
output['facets'] = parse_facet_result(state, result)
sub_queries = []
for doc in hits.get('hits', []):
entity = doc.get('_source')
entity['id'] = doc.get('_id')
entity['score'] = doc.get('_score')
entity['api_url'] = url_for('entities_api.view', id=doc.get('_id'))
output['results'].append(entity)
sq = {'term': {'entities.id': entity['id']}}
sq = add_filter(
sq, {'terms': {
'collection_id': state.authz.collections_read
}})
sq = {'size': 0, 'query': sq}
sub_queries.append(json.dumps({}))
sub_queries.append(json.dumps(sq))
if doc_counts and len(sub_queries):
# Get the number of matching documents for each entity.
body = '\n'.join(sub_queries)
res = es.msearch(index=es_index, doc_type=TYPE_DOCUMENT, body=body)
for (entity, res) in zip(output['results'], res.get('responses')):
entity['doc_count'] = res.get('hits', {}).get('total')
return output
def documents_query(state, fields=None, facets=True, since=None):
"""Parse a user query string, compose and execute a query."""
# This used to be several functions, but it's actually incredibly
# procedural and so it's been linearised into one function. To really
# clean this up, I think it should be based around an object model of
# some sort.
q = text_query(state.text)
if state.raw_query:
q = {"bool": {"must": [q, state.raw_query]}}
q = authz_filter(q, state.authz, roles=False)
# Used by alerting to find only updated results:
if since is not None:
q = add_filter(q, {"range": {"created_at": {"gt": since}}})
# Sorting
if state.sort == 'newest':
sort = [{'dates': 'desc'}, {'created_at': 'desc'}, '_score']
if state.sort == 'oldest':
sort = [{'dates': 'asc'}, {'created_at': 'asc'}, '_score']
else:
sort = ['_score']
# TODO: find a better way to handle "slightly special" aggregations like
# entities and collections.
aggs = {'scoped': {'global': {}, 'aggs': {}}}
if facets:
facets = list(state.facet_names)
if 'collections' in facets:
aggs = facet_collections(state, q, aggs)
facets.remove('collections')
if 'entities' in facets:
aggs = facet_entities(state, aggs)
facets.remove('entities')
aggs = aggregate(state, q, aggs, facets)
# allow plug-ins to post-process the query.
signals.document_query_process.send(q=q, state=state)
q = {
'sort': sort,
'size': state.limit,
'from': state.offset,
'query': filter_query(q, state.filters),
'aggregations': aggs,
'_source': fields or DEFAULT_FIELDS
}
result, hits, output = execute_basic(TYPE_DOCUMENT, q)
# This will add labels and other contextual information.
output['facets'] = parse_facet_result(state, result)
# After the main query has run, a sub-query will be run for each returned
# result in order to find relevant records for result highlighting.
sub_shoulds = records_query_shoulds(state)
sub_queries = []
for doc in hits.get('hits', []):
document = doc.get('_source')
document['id'] = int(doc.get('_id'))
document['score'] = doc.get('_score')
document['records'] = {'results': [], 'total': 0}
collection_id = document.get('collection_id')
try:
# FIXME: there's got to be a nicer way of doing this....
document['public'] = state.authz.collection_public(collection_id)
except:
document['public'] = None
sq = records_query_internal(document['id'], sub_shoulds)
if sq is not None:
sub_queries.append(json.dumps({}))
sub_queries.append(json.dumps(sq))
output['results'].append(document)
if not len(sub_queries):
return output
body = '\n'.join(sub_queries)
res = es.msearch(index=es_index, doc_type=TYPE_RECORD, body=body)
for doc in output['results']:
for sq in res.get('responses', []):
sqhits = sq.get('hits', {})
doc['records']['total'] = sqhits.get('total', 0)
for hit in sqhits.get('hits', {}):
record = hit.get('_source')
if doc['id'] != record['document_id']:
continue
hlt = hit.get('highlight', {})
texts = hlt.get('text', []) or hlt.get('text_latin', [])
texts = [clean_highlight(t) for t in texts]
texts = [t for t in texts if len(t)]
if len(texts):
record['text'] = texts[0]
doc['records']['results'].append(record)
return output
