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"""Search using Xapian index."""
import json
import urllib.parse
from flask import abort, Blueprint, current_app, jsonify, request
import xapian
from gn3.monads import MonadicDict
from gn3.db_utils import xapian_database
search = Blueprint("search", __name__)
def parse_query(query: str):
"""Parse search query using GeneNetwork specific field processors."""
queryparser = xapian.QueryParser()
queryparser.set_stemmer(xapian.Stem("en"))
queryparser.set_stemming_strategy(queryparser.STEM_SOME)
queryparser.add_boolean_prefix("author", "A")
queryparser.add_boolean_prefix("species", "XS")
queryparser.add_boolean_prefix("group", "XG")
queryparser.add_boolean_prefix("tissue", "XI")
queryparser.add_boolean_prefix("dataset", "XDS")
queryparser.add_boolean_prefix("symbol", "XY")
queryparser.add_boolean_prefix("chr", "XC")
queryparser.add_boolean_prefix("peakchr", "XPC")
queryparser.add_prefix("description", "XD")
range_prefixes = ["mean", "peak", "mb", "peakmb", "additive", "year"]
for i, prefix in enumerate(range_prefixes):
queryparser.add_rangeprocessor(xapian.NumberRangeProcessor(i, prefix + ":"))
return queryparser.parse_query(query)
@search.route("/")
def search_results():
"""Search Xapian index and return a list of results."""
args = request.args
search_type = args.get("type", default="gene")
querystring = args.get("query", default="")
page = args.get("page", default=1, type=int)
if page < 1:
abort(404, description="Requested page does not exist")
results_per_page = args.get("per_page", default=100, type=int)
maximum_results_per_page = 10000
if results_per_page > maximum_results_per_page:
abort(400, description="Requested too many search results")
query = parse_query(querystring)
traits = []
# pylint: disable=invalid-name
with xapian_database(current_app.config["XAPIAN_DB_PATH"]) as db:
enquire = xapian.Enquire(db)
# Filter documents by type.
enquire.set_query(xapian.Query(xapian.Query.OP_FILTER,
query,
xapian.Query(f"XT{search_type}")))
for xapian_match in enquire.get_mset((page-1)*results_per_page, results_per_page):
trait = MonadicDict(json.loads(xapian_match.document.get_data()))
# Add PubMed link to phenotype search results.
if search_type == "phenotype":
trait["pubmed_link"] = trait["pubmed_id"].map(
lambda pubmed_id: "http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?"
+ urllib.parse.urlencode({"cmd": "Retrieve",
"db": "PubMed",
"list_uids": pubmed_id,
"dopt": "Abstract"}))
traits.append(trait.data)
return jsonify(traits)
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