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"""
Helpers to make elasticsearch queries.
"""
import sys
import json
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
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": "Release Date",
"slug": "filter_time",
"default": "all_time",
"list": [
{"label": "All Time", "slug": "all_time"},
{"label": "Past Week", "slug": "past_week"},
{"label": "Past Year", "slug": "past_year"},
{"label": "Since 2000", "slug": "since_2000"},
{"label": "Before 1925", "slug": "before_1925"},
],
}
type_options: Any = {
"label": "Resource Type",
"slug": "filter_type",
"default": "papers",
"list": [
{"label": "Papers", "slug": "papers"},
{"label": "Reports", "slug": "reports"},
{"label": "Datasets", "slug": "datasets"},
{"label": "Everything", "slug": "everything"},
],
}
availability_options: Any = {
"label": "Availability",
"slug": "filter_availability",
"default": "everything",
"list": [
{"label": "Everything", "slug": "everything"},
{"label": "Fulltext", "slug": "fulltext"},
{"label": "Open Access", "slug": "oa"},
],
}
sort_options: Any = {
"label": "Sort Order",
"slug": "sort_order",
"default": "relevancy",
"list": [
{"label": "All Time", "slug": "relevancy"},
{"label": "Recent First", "slug": "time_desc"},
{"label": "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}'")
search = search.query(
'query_string',
query=query.q,
default_operator="AND",
analyze_wildcard=True,
lenient=True,
fields=[
"everything",
"abstracts_all",
"fulltext.body",
"fulltext.annex",
],
)
search = search.highlight(
"abstracts_all",
"fulltext.body",
"fulltext.annex",
number_of_fragments=2,
fragment_size=250,
)
# 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)
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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