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R3600/modules/miscutil/lib/solrutils_bibrank_searcher.py
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solrutils_bibrank_searcher.py
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# -*- coding: utf-8 -*-
##
## This file is part of Invenio.
## Copyright (C) 2011 CERN.
##
## Invenio is free software; you can redistribute it and/or
## modify it under the terms of the GNU General Public License as
## published by the Free Software Foundation; either version 2 of the
## License, or (at your option) any later version.
##
## Invenio is distributed in the hope that it will be useful, but
## WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
## General Public License for more details.
##
## You should have received a copy of the GNU General Public License
## along with Invenio; if not, write to the Free Software Foundation, Inc.,
## 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA.
"""
Solr utilities.
"""
import itertools
from invenio.config import CFG_SOLR_URL
from invenio.intbitset import intbitset
from invenio.errorlib import register_exception
if CFG_SOLR_URL:
import solr
conn = solr.Solr(CFG_SOLR_URL)
SOLR_CONNECTION = solr.SolrConnection(CFG_SOLR_URL) # pylint: disable=E1101
SOLR_MLT_CONNECTION = solr.SearchHandler(conn, "/mlt")
BOOLEAN_EQUIVALENTS = {"+": "AND",
"|": "OR",
"-": "NOT"}
def get_collection_filter(hitset, cutoff_amount):
# The last n hitset records are considered to be newest and therfore most relevant
start_index = len(hitset) - cutoff_amount
if start_index < 0:
start_index = 0
it = itertools.islice(hitset, start_index, None)
ids = ' '.join([str(recid) for recid in it])
if ids:
return 'id:(%s)' % ids
else:
return ''
def solr_get_ranked(query, hitset, params, ranked_result_amount):
"""
Queries Solr.
Returns: a list of ranked record ids [(recid, score), ...) contained in hitset
and an intbitset of record ids contained in hitset.
"""
response = SOLR_CONNECTION.query(q=query, fields=['id', 'score'], rows=str(ranked_result_amount), fq=get_collection_filter(hitset, params['cutoff_amount']), timeAllowed=params['cutoff_time_ms'])
return get_normalized_ranking_scores(response)
def solr_get_similar_ranked(recid, hitset, params, ranked_result_amount):
"""
Queries Solr for similar records.
Returns: a list of ranked record ids [(recid, score), ...) contained in hitset
and an intbitset of record ids contained in hitset.
"""
# original one first
query = 'id:%s' % recid
response = SOLR_MLT_CONNECTION(q=query, fields=['id', 'score'], rows=str(ranked_result_amount * params['find_similar_to_recid']['more_results_factor']),
mlt='true', mlt_fl=params['find_similar_to_recid']['mlt_fl'], timeAllowed=params['cutoff_time_ms'],
mlt_mintf=params['find_similar_to_recid']['mlt_mintf'], mlt_mindf=params['find_similar_to_recid']['mlt_mindf'], mlt_minwl=params['find_similar_to_recid']['mlt_minwl'],
mlt_maxwl=params['find_similar_to_recid']['mlt_maxwl'], mlt_maxqt=params['find_similar_to_recid']['mlt_maxqt'], mlt_maxntp=params['find_similar_to_recid']['mlt_maxntp'],
mlt_boost=params['find_similar_to_recid']['mlt_boost'])
# Insert original id at the front with guaranteed highest score
response.results.insert(0, {u'id': u'%s' % recid, u'score': response.maxScore * 1.1})
return get_normalized_ranking_scores(response, hitset, [recid])
def get_normalized_ranking_scores(response, hitset_filter = None, recids = []):
"""
Returns the result having normalized ranking scores, interval [0, 100].
hitset_filter - optional filter for the results
recids - optional recids that shall remain in the result despite the filter
"""
if not len(response.results):
return ([], intbitset())
# response.maxScore does not work in case of something was added to the response
max_score = float(response.results[0]['score'])
ranked_result = []
matched_recs = intbitset()
for hit in response.results:
recid = int(hit['id'])
if (not hitset_filter and hitset_filter != []) or recid in hitset_filter or recid in recids:
normalised_score = 0
if max_score > 0:
normalised_score = int(100.0 / max_score * float(hit['score']))
ranked_result.append((recid, normalised_score))
matched_recs.add(recid)
ranked_result.reverse()
return (ranked_result, matched_recs)
def word_similarity_solr(pattern, hitset, params, verbose, explicit_field, ranked_result_amount):
"""
Ranking a records containing specified words and returns a sorted list.
input:
hitset - a list of hits for the query found by search_engine
verbose - verbose value
explicit_field - field to search (selected in GUI)
ranked_result_amount - amount of results to be ranked
output:
recset - a list of sorted records: [[23,34], [344,24], [1,01]]
prefix - what to show before the rank value
postfix - what to show after the rank value
voutput - contains extra information, content dependent on verbose value
"""
voutput = ""
search_units = []
if not len(hitset):
return ([], "", "", voutput)
if pattern:
pattern = " ".join(map(str, pattern))
from invenio.search_engine import create_basic_search_units
search_units = create_basic_search_units(None, pattern, explicit_field)
else:
return (None, "Records not ranked. The query is not detailed enough, or not enough records found, for ranking to be possible.", "", voutput)
if verbose > 0:
voutput += "Hitset: %s<br/>" % hitset
voutput += "Pattern: %s<br/>" % pattern
voutput += "Search units: %s<br/>" % search_units
query = ""
(ranked_result, matched_recs) = (None, None)
# Ranks similar records
if search_units[0][2] == 'recid':
recid = search_units[0][1]
if verbose > 0:
voutput += "Ranked amount: %s<br/>" % ranked_result_amount
try:
(ranked_result, matched_recs) = solr_get_similar_ranked(recid, hitset, params, ranked_result_amount)
except:
register_exception()
return (None, "Records not ranked. An error occurred. Please check the query.", "", voutput)
# Cutoffs potentially large hitset
it = itertools.islice(hitset, params['find_similar_to_recid']['hitset_cutoff'])
hitset = intbitset(list(it))
# Regular word similarity ranking
else:
for (operator, pattern, field, unit_type) in search_units:
# Any field
if field == '':
field = 'global'
# Field might not exist
elif field not in params["fields"].keys():
field = params["default_field"]
if unit_type == "a":
# Eliminates leading and trailing %
if pattern[0] == "%":
pattern = pattern[1:-1]
pattern = "\"" + pattern + "\""
weighting = "^" + str(params["fields"][field]["weight"])
if ':' in pattern:
pattern = pattern.rsplit(':', 1)[1]
query_part = field + ":" + pattern + weighting
# Considers boolean operator from the second part on, allows negation from the first part on
if query or operator == "-":
query += " " + BOOLEAN_EQUIVALENTS[operator] + " "
query += query_part + " "
if verbose > 0:
voutput += "Solr query: %s<br/>" % query
try:
(ranked_result, matched_recs) = solr_get_ranked(query, hitset, params, ranked_result_amount)
except:
register_exception()
return (None, "Records not ranked. An error occurred. Please check the query.", "", voutput)
if verbose > 0:
voutput += "All matched records: %s<br/>" % matched_recs
# Considers not ranked records
not_ranked = hitset.difference(matched_recs)
if not_ranked:
lrecIDs = list(not_ranked)
ranked_result = zip(lrecIDs, [0] * len(lrecIDs)) + ranked_result
if verbose > 0:
voutput += "Not ranked: %s<br/>" % not_ranked
return (ranked_result, params["prefix"], params["postfix"], voutput)
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