def non_aggr_search(queries, show_bing, show_blekko, show_entweb, page):
"""
Generate results in non-aggregated mode.
Returns a list of three result lists
"""
if show_bing:
bing_list = bing_get_item_list(queries[0], page, 10)
else:
bing_list = []
if show_blekko:
blekko_list = blekko_get_item_list(queries[1], page, 10)
else:
blekko_list = []
if show_entweb:
entweb_list = entweb_get_item_list(queries[2], page, 10)
else:
entweb_list = []
return [bing_list, blekko_list, entweb_list]
def non_aggr_search(queries, show_bing, show_blekko, show_entweb, page):
"""
Generate results in non-aggregated mode.
Returns a list of three result lists
"""
if show_bing:
bing_list = bing_get_item_list(queries[0], page, 10)
else:
bing_list = []
if show_blekko:
blekko_list = blekko_get_item_list(queries[1], page, 10)
else:
blekko_list = []
if show_entweb:
entweb_list = entweb_get_item_list(queries[2], page, 10)
else:
entweb_list = []
return [bing_list, blekko_list, entweb_list]
def aggr_search(queries, show_bing, show_blekko, show_entweb, page):
"""
Generate results in aggregated mode.
Return a list of aggregated results.
"""
bingWeight = 1.737
blekkoWeight = 1.412
entwebWeight = 1.0
scored_list = []
aggr_page = 0
engine_page = 0
##########################################
while aggr_page < page:
if len(scored_list) < 100:
engine_page += 1
if show_bing:
bing_list = bing_get_item_list(queries[0], engine_page, 50)
else:
bing_list = []
if show_blekko:
blekko_list = blekko_get_item_list(queries[1], engine_page, 50)
else:
blekko_list = []
if show_entweb:
entweb_list = entweb_get_item_list(queries[2], engine_page, 50)
else:
entweb_list = []
##################################
if aggr_page == 0:
for i in bing_list:
i.base_score[0] = 100.0 - bing_list.index(i)
for j in blekko_list:
j.base_score[1] = 100.0 - blekko_list.index(j)
for k in entweb_list:
k.base_score[2] = 100.0 - entweb_list.index(k)
##################################
else:
bing_top_score = 0
blekko_top_score = 0
entweb_top_score = 0
for i in scored_list:
if 'BING' in i.source:
if i.base_score[0] > bing_top_score:
bing_top_score = i.base_score[0]
if 'Blekko' in i.source:
if i.base_score[1] > blekko_top_score:
blekko_top_score = i.base_score[1]
if 'EntireWeb' in i.source:
if i.base_score[2] > entweb_top_score:
entweb_top_score = i.base_score[2]
max_top_score = max(bing_top_score, blekko_top_score,
entweb_top_score)
offset = 100.0 - max_top_score
for i in bing_list:
i.base_score[0] = offset + 50.0 - bing_list.index(i)
for j in blekko_list:
j.base_score[1] = offset + 50.0 - blekko_list.index(j)
for k in entweb_list:
k.base_score[2] = offset + 50.0 - entweb_list.index(k)
for i in scored_list:
if 'BING' in i.source:
i.base_score[0] += offset
else:
for j in bing_list:
if i.url.lower() == j.url.lower():
i.base_score[0] = j.base_score[0]
i.source.append('BING')
bing_list.pop(bing_list.index(j))
break
if 'Blekko' in i.source:
i.base_score[1] += offset
else:
for k in blekko_list:
if i.url.lower() == k.url.lower():
i.base_score[1] = k.base_score[0]
i.source.append('Blekko')
blekko_list.pop(blekko_list.index(k))
break
if 'EntireWeb' in i.source:
i.base_score[2] += offset
else:
for l in entweb_list:
if i.url.lower() == l.url.lower():
i.base_score[2] = l.base_score[0]
i.source.append('EntireWeb')
entweb_list.pop(entweb_list.index(l))
break
i.weighted_score = (i.base_score[0] * bingWeight +
i.base_score[1] * blekkoWeight +
i.base_score[2] * entwebWeight) * (
3 - i.base_score.count(0.0))
##################################
while bing_list:
for i in blekko_list:
if i.url.lower() == bing_list[0].url.lower():
bing_list[0].base_score[1] = i.base_score[1]
bing_list[0].source += i.source
blekko_list.pop(blekko_list.index(i))
break
for j in entweb_list:
if j.url.lower() == bing_list[0].url.lower():
bing_list[0].base_score[2] += j.base_score[2]
bing_list[0].source += j.source
entweb_list.pop(entweb_list.index(j))
break
bing_list[0].weighted_score = (
bing_list[0].base_score[0] * bingWeight +
bing_list[0].base_score[1] * blekkoWeight +
bing_list[0].base_score[2] * entwebWeight) * (
3 - bing_list[0].base_score.count(0.0))
scored_list.append(bing_list.pop(0))
##################################
while blekko_list:
for i in entweb_list:
if i.url.lower() == blekko_list[0].url.lower():
blekko_list[0].base_score[2] += i.base_score[2]
blekko_list[0].source += i.source
entweb_list.pop(entweb_list.index(i))
break
blekko_list[0].weighted_score = (
blekko_list[0].base_score[1] * blekkoWeight +
blekko_list[0].base_score[2] * entwebWeight) * (
3 - blekko_list[0].base_score.count(0.0))
scored_list.append(blekko_list.pop(0))
##################################
while entweb_list:
entweb_list[0].weighted_score = entweb_list[0].base_score[
2] * entwebWeight
scored_list.append(entweb_list.pop(0))
##################################
sorted_list = sorted(scored_list,
key=attrgetter('weighted_score'),
reverse=True)
result_list = sorted_list[0:50]
scored_list = sorted_list[50:]
aggr_page += 1
##################################
else:
result_list = sorted_list[0:50]
scored_list = sorted_list[50:]
aggr_page += 1
##########################################
return result_list
def aggr_search(queries, show_bing, show_blekko, show_entweb, page):
"""
Generate results in aggregated mode.
Return a list of aggregated results.
"""
bingWeight = 1.737
blekkoWeight = 1.412
entwebWeight = 1.0
scored_list = []
aggr_page = 0
engine_page = 0
##########################################
while aggr_page < page:
if len(scored_list) < 100:
engine_page += 1
if show_bing:
bing_list = bing_get_item_list(queries[0], engine_page, 50)
else:
bing_list = []
if show_blekko:
blekko_list = blekko_get_item_list(queries[1], engine_page, 50)
else:
blekko_list = []
if show_entweb:
entweb_list = entweb_get_item_list(queries[2], engine_page, 50)
else:
entweb_list = []
##################################
if aggr_page == 0:
for i in bing_list:
i.base_score[0] = 100.0 - bing_list.index(i)
for j in blekko_list:
j.base_score[1] = 100.0 - blekko_list.index(j)
for k in entweb_list:
k.base_score[2] = 100.0 - entweb_list.index(k)
##################################
else:
bing_top_score = 0
blekko_top_score = 0
entweb_top_score = 0
for i in scored_list:
if 'BING' in i.source:
if i.base_score[0] > bing_top_score:
bing_top_score = i.base_score[0]
if 'Blekko' in i.source:
if i.base_score[1] > blekko_top_score:
blekko_top_score = i.base_score[1]
if 'EntireWeb' in i.source:
if i.base_score[2] > entweb_top_score:
entweb_top_score = i.base_score[2]
max_top_score = max(bing_top_score, blekko_top_score, entweb_top_score)
offset = 100.0 - max_top_score
for i in bing_list:
i.base_score[0] = offset + 50.0 - bing_list.index(i)
for j in blekko_list:
j.base_score[1] = offset + 50.0 - blekko_list.index(j)
for k in entweb_list:
k.base_score[2] = offset + 50.0 - entweb_list.index(k)
for i in scored_list:
if 'BING' in i.source:
i.base_score[0] += offset
else:
for j in bing_list:
if i.url.lower() == j.url.lower():
i.base_score[0] = j.base_score[0]
i.source.append('BING')
bing_list.pop(bing_list.index(j))
break
if 'Blekko' in i.source:
i.base_score[1] += offset
else:
for k in blekko_list:
if i.url.lower() == k.url.lower():
i.base_score[1] = k.base_score[0]
i.source.append('Blekko')
blekko_list.pop(blekko_list.index(k))
break
if 'EntireWeb' in i.source:
i.base_score[2] += offset
else:
for l in entweb_list:
if i.url.lower() == l.url.lower():
i.base_score[2] = l.base_score[0]
i.source.append('EntireWeb')
entweb_list.pop(entweb_list.index(l))
break
i.weighted_score = (i.base_score[0] * bingWeight + i.base_score[1] * blekkoWeight + i.base_score[2] * entwebWeight) * (3 - i.base_score.count(0.0))
##################################
while bing_list:
for i in blekko_list:
if i.url.lower() == bing_list[0].url.lower():
bing_list[0].base_score[1] = i.base_score[1]
bing_list[0].source += i.source
blekko_list.pop(blekko_list.index(i))
break
for j in entweb_list:
if j.url.lower() == bing_list[0].url.lower():
bing_list[0].base_score[2] += j.base_score[2]
bing_list[0].source += j.source
entweb_list.pop(entweb_list.index(j))
break
bing_list[0].weighted_score = (bing_list[0].base_score[0] * bingWeight + bing_list[0].base_score[1] * blekkoWeight + bing_list[0].base_score[2] * entwebWeight) * (3 - bing_list[0].base_score.count(0.0))
scored_list.append(bing_list.pop(0))
##################################
while blekko_list:
for i in entweb_list:
if i.url.lower() == blekko_list[0].url.lower():
blekko_list[0].base_score[2] += i.base_score[2]
blekko_list[0].source += i.source
entweb_list.pop(entweb_list.index(i))
break
blekko_list[0].weighted_score = (blekko_list[0].base_score[1] * blekkoWeight + blekko_list[0].base_score[2] * entwebWeight) * (3 - blekko_list[0].base_score.count(0.0))
scored_list.append(blekko_list.pop(0))
##################################
while entweb_list:
entweb_list[0].weighted_score = entweb_list[0].base_score[2] * entwebWeight
scored_list.append(entweb_list.pop(0))
##################################
sorted_list = sorted(scored_list, key = attrgetter('weighted_score'), reverse = True)
result_list = sorted_list[0:50]
scored_list = sorted_list[50:]
aggr_page += 1
##################################
else:
result_list = sorted_list[0:50]
scored_list = sorted_list[50:]
aggr_page += 1
##########################################
return result_list
