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"""
Helpers to make elasticsearch queries.
"""
import sys
import json
from gettext import gettext
import datetime
import elasticsearch
from pydantic import BaseModel
from dynaconf import settings
from dataclasses import dataclass
from elasticsearch_dsl import Search, Q
from typing import List, Dict, Tuple, Optional, Any, Sequence
# i18n note: the use of gettext below doesn't actually do the translation here,
# it just ensures that the strings are caught by babel for translation later
class FulltextQuery(BaseModel):
q: Optional[str] = None
limit: Optional[int] = None
offset: Optional[int] = None
filter_time: Optional[str] = None
filter_type: Optional[str] = None
filter_availability: Optional[str] = None
sort_order: Optional[str] = None
time_options: Any = {
"label": gettext("Release Date"),
"slug": "filter_time",
"default": "all_time",
"list": [
{"label": gettext("All Time"), "slug": "all_time"},
{"label": gettext("Past Week"), "slug": "past_week"},
{"label": gettext("Past Year"), "slug": "past_year"},
{"label": gettext("Since 2000"), "slug": "since_2000"},
{"label": gettext("Before 1925"), "slug": "before_1925"},
],
}
type_options: Any = {
"label": gettext("Resource Type"),
"slug": "filter_type",
"default": "papers",
"list": [
{"label": gettext("Papers"), "slug": "papers"},
{"label": gettext("Reports"), "slug": "reports"},
{"label": gettext("Datasets"), "slug": "datasets"},
{"label": gettext("Everything"), "slug": "everything"},
],
}
availability_options: Any = {
"label": gettext("Availability"),
"slug": "filter_availability",
"default": "everything",
"list": [
{"label": gettext("Everything"), "slug": "everything"},
{"label": gettext("Fulltext"), "slug": "fulltext"},
{"label": gettext("Open Access"), "slug": "oa"},
],
}
sort_options: Any = {
"label": gettext("Sort Order"),
"slug": "sort_order",
"default": "relevancy",
"list": [
{"label": gettext("All Time"), "slug": "relevancy"},
{"label": gettext("Recent First"), "slug": "time_desc"},
{"label": gettext("Oldest First"), "slug": "time_asc"},
],
}
class FulltextHits(BaseModel):
count_returned: int
count_found: int
offset: int
limit: int
deep_page_limit: int
query_time_ms: int
results: List[Any]
def do_fulltext_search(query: FulltextQuery, deep_page_limit: int = 2000) -> FulltextHits:
es_client = elasticsearch.Elasticsearch(settings.ELASTICSEARCH_BACKEND)
search = Search(using=es_client, index=settings.ELASTICSEARCH_FULLTEXT_INDEX)
# Convert raw DOIs to DOI queries
if len(query.q.split()) == 1 and query.q.startswith("10.") and query.q.count("/") >= 1:
search = search.filter("terms", doi=query.q)
query.q = "*"
# type filters
if query.filter_type == "papers":
search = search.filter("terms", type=[ "article-journal", "paper-conference", "chapter", ])
elif query.filter_type == "reports":
search = search.filter("terms", type=[ "report", "standard", ])
elif query.filter_type == "datasets":
search = search.filter("terms", type=[ "dataset", "software", ])
elif query.filter_type == "everything" or query.filter_type == None:
pass
else:
raise ValueError(f"Unknown 'filter_type' parameter value: '{query.filter_type}'")
# time filters
if query.filter_time == "past_week":
week_ago_date = str(datetime.date.today() - datetime.timedelta(days=7))
search = search.filter("range", date=dict(gte=week_ago_date))
elif query.filter_time == "past_year":
# (date in the past year) or (year is this year)
# the later to catch papers which don't have release_date defined
year_ago_date = str(datetime.date.today() - datetime.timedelta(days=365))
this_year = datetime.date.today().year
search = search.filter(Q("range", date=dict(gte=year_ago_date)) | Q("term", year=this_year))
elif query.filter_time == "since_2000":
search = search.filter("range", year=dict(gte=2000))
elif query.filter_time == "before_1925":
search = search.filter("range", year=dict(lt=1925))
elif query.filter_time == "all_time" or query.filter_time == None:
pass
else:
raise ValueError(f"Unknown 'filter_time' parameter value: '{query.filter_time}'")
# availability filters
if query.filter_availability == "oa":
# TODO: real OA filter/flag
search = search.filter("exists", field="license_slug")
elif query.filter_availability == "fulltext":
search = search.filter("terms", access_type=["wayback", "ia_file", "ia_sim"])
elif query.filter_availability == "everything" or query.filter_availability == None:
pass
else:
raise ValueError(f"Unknown 'filter_availability' parameter value: '{query.filter_availability}'")
# we combined several queries to improve scoring.
# this query use the fancy built-in query string parser
basic_fulltext = Q(
'query_string',
query=query.q,
default_operator="AND",
analyze_wildcard=True,
allow_leading_wildcard=False,
lenient=True,
quote_field_suffix=".exact",
fields=[
"title^5",
"biblio_all^3",
"abstracts.body^2",
"fulltext.body",
"everything",
],
)
has_fulltext = Q(
'terms',
access_type=["ia_sim", "ia_file", "wayback"],
)
poor_metadata = Q(
'bool',
should=[
# if these fields aren't set, metadata is poor. The more that do
# not exist, the stronger the signal.
Q("bool", must_not=Q("exists", field="title")),
Q("bool", must_not=Q("exists", field="year")),
Q("bool", must_not=Q("exists", field="type")),
Q("bool", must_not=Q("exists", field="stage")),
],
)
search = search.query(
"boosting",
positive=Q(
"bool",
must=basic_fulltext,
should=[has_fulltext],
),
negative=poor_metadata,
negative_boost=0.5,
)
search = search.highlight(
"abstracts.body",
"fulltext.body",
"fulltext.annex",
number_of_fragments=2,
fragment_size=300,
)
# sort order
if query.sort_order == "time_asc":
search = search.sort("year", "date")
elif query.sort_order == "time_desc":
search = search.sort("-year", "-date")
elif query.sort_order == "relevancy" or query.sort_order == None:
pass
else:
raise ValueError(f"Unknown 'sort_order' parameter value: '{query.sort_order}'")
# Sanity checks
limit = min((int(query.limit or 25), 100))
offset = max((int(query.offset or 0), 0))
if offset > deep_page_limit:
# Avoid deep paging problem.
offset = deep_page_limit
search = search[offset:offset+limit]
try:
resp = search.execute()
except elasticsearch.exceptions.RequestError as e:
# this is a "user" error
print("elasticsearch 400: " + str(e.info), file=sys.stderr)
if e.info.get('error', {}).get('root_cause', {}):
raise ValueError(str(e.info['error']['root_cause'][0].get('reason')))
else:
raise ValueError(str(e.info))
except elasticsearch.exceptions.TransportError as e:
# all other errors
print("elasticsearch non-200 status code: {}".format(e.info), file=sys.stderr)
raise IOError(str(e.info))
# convert from objects to python dicts
results = []
for h in resp:
r = h._d_
#print(json.dumps(h.meta._d_, indent=2))
r['_highlights'] = []
if 'highlight' in dir(h.meta):
highlights = h.meta.highlight._d_
for k in highlights:
r['_highlights'] += highlights[k]
results.append(r)
for h in results:
# Handle surrogate strings that elasticsearch returns sometimes,
# probably due to mangled data processing in some pipeline.
# "Crimes against Unicode"; production workaround
for key in h:
if type(h[key]) is str:
h[key] = h[key].encode('utf8', 'ignore').decode('utf8')
return FulltextHits(
count_returned=len(results),
count_found=int(resp.hits.total),
offset=offset,
limit=limit,
deep_page_limit=deep_page_limit,
query_time_ms=int(resp.took),
results=results,
)
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