83 lines
2.4 KiB
Python
83 lines
2.4 KiB
Python
from math import ceil
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from django.conf import settings
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from numpy import array_split
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from core.db.storage import db
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def construct_query(net, nicks):
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# Construct the query
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query_nicks = [{"match": {"nick": x}} for x in nicks]
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query_should = query_nicks
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# Get the initial query
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query = {
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"size": settings.META_QUERY_SIZE,
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"query": {
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"bool": {
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"must": [
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{"match": {"net": net}},
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{"match": {"type": "who"}},
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{
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"bool": {
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"should": query_should,
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}
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},
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]
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}
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},
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}
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return query
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def get_meta(request, net, nicks, iter=True):
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"""
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Get all related nicknames of the given nickname by tracking nickname changes.
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"""
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# Split query into chunks
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split_nicks = array_split(nicks, ceil(len(nicks) / settings.META_MAX_CHUNK_SIZE))
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meta = []
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for nicks_chunked in split_nicks:
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if len(nicks_chunked) == 0:
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break
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meta_tmp = []
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query = construct_query(net, nicks_chunked)
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results = db.query(
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request.user,
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query,
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index=settings.INDEX_META,
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)
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if "object_list" in results.keys():
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for element in results["object_list"]:
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meta_tmp.append(element)
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for x in meta_tmp:
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if x not in meta:
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meta.append(x)
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# Run the search again, passing in all the users we found
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# Nicknames we find from the repeated search
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# nicks_searched = []
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# if iter:
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# nicks_l2 = []
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# loop = 0
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# while loop < settings.META_MAX_ITERATIONS:
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# loop += 1
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# nicks_not_searched = [x for x in nicks if x not in nicks_searched]
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# nicks_l2 = get_nicks(request, net, nicks, False)
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# # Add all the nicks we just searched for to the list
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# for x in nicks_not_searched:
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# if x not in nicks_not_searched:
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# nicks_searched.append(x)
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# # If all of the nicks we received now, we already know about
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# if set(nicks_l2).issubset(set(nicks)):
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# break
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# for x in nicks_l2:
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# if x not in nicks:
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# nicks.append(x)
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return meta
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