def search_web(keywords,prev_results,start,end):
doc_freq = keywords[start:end]
print "\nkeywords:::"
print doc_freq
if start == 0 :
return_string ='{"final_results":['
else:
return_string = prev_results
i=0
cate_obj = cate_mongo_specific1.categorization()
#bing = bingapi.Bing(app_ID)
bing = getbingid()
print "\n\nKEYWORDS:"
for l in doc_freq:
film =" "
books=" "
people = " "
location =" "
str1 = ' '.join(l)
print "keyword:" + str1
#category = cate_obj.get_category(str1) #get category of keyword
#print category
#for n in l.neighbours:
# str1 = str1 + " " + n.word
category = "cat"
search_query = str1
#search_query = str1
#print "search_query::::::::" + str1
#for neighbour in df.neighbours:
# print neighbour.word
# search_query = search_query + neighbour.word + " "
if "film" in category:
#if c is "film":
print "\n\n in film:"
film = cate_obj.search_film(search_query)
print film
elif "books" in category:
books = cate_obj.search_books(search_query)
elif "people" in category:
people = cate_obj.search_people(search_query)
elif "location" in category:
location = cate_obj.search_location(search_query)
else:
pass
res = bing.do_web_search(search_query)
dump_res = json.dumps({"keyword":search_query,"category":category,"search_res":res["SearchResponse"]["Web"]["Results"],"film":film,"books":books,"people":people,"location":location})
return_string += dump_res+","
#return_string += "]}"
#return_string +='{"test":"dummy_res"}' #Add dummy result for comma after last result
#return_string += "]}"
#print return_string
return return_string
def search_web(keywords, prev_results, start, end, url):
doc_freq = keywords[start:end]
print "\n next keywords:::"
for i in doc_freq:
print i.keyword
if start == 0:
return_string = '{"final_results":['
else:
return_string = prev_results
i = 0
cate_obj = cate_mongo_specific1.categorization()
#bing = bingapi.Bing(app_ID)
bing = getbingid()
print "\n\nMY KEYWORDS:"
for l in doc_freq:
film = " "
books = " "
people = " "
location = " "
#str1 = l.keyword
str1 = ' '.join(l.keyword)
print "keyword:" + str1
keyword = str1
category = cate_obj.get_category(str1) #get category of keyword
#print category
for n in l.neighbours:
str1 = str1 + " " + n.word
#category = "cat"
search_query = str1
#search_query = str1
print "search_query::::::::" + str1
#for neighbour in df.neighbours:
# print neighbour.word
# search_query = search_query + neighbour.word + " "
if "film" in category:
#if c is "film":
print "\n\n in film:"
film = cate_obj.search_film(search_query)
print film
elif "books" in category:
books = cate_obj.search_books(search_query)
elif "people" in category:
people = cate_obj.search_people(search_query)
elif "location" in category:
location = cate_obj.search_location(search_query)
else:
pass
# search_query = "sachin"
print "do web search"
try:
res = bing.do_web_search(search_query)
for i in res["SearchResponse"]["Web"][
"Results"]: #Removing current URL
if i["Url"] == url:
res["SearchResponse"]["Web"]["Results"].remove(i)
dump_res = json.dumps({
"keyword":
keyword,
"category":
category,
"search_res":
res["SearchResponse"]["Web"]["Results"][0:5],
"film":
film,
"books":
books,
"people":
people,
"location":
location
})
return_string += dump_res + ","
print "web search done"
except Exception:
print "search not done"
pass
#print return_string
# import pdb;pdb.set_trace();
return return_string
def search_web(keywords,prev_results,start,end,url):
doc_freq = keywords[start:end]
print "\n next keywords:::"
for i in doc_freq:
print i.keyword
if start == 0 :
return_string ='{"final_results":['
else:
return_string = prev_results
i=0
cate_obj = cate_mongo_specific1.categorization()
#bing = bingapi.Bing(app_ID)
bing = getbingid()
print "\n\nMY KEYWORDS:"
for l in doc_freq:
film =" "
books=" "
people = " "
location =" "
#str1 = l.keyword
str1 = ' '.join(l.keyword)
print "keyword:" + str1
keyword = str1
category = cate_obj.get_category(str1) #get category of keyword
#print category
for n in l.neighbours:
str1 = str1 + " " + n.word
#category = "cat"
search_query = str1
#search_query = str1
print "search_query::::::::" + str1
#for neighbour in df.neighbours:
# print neighbour.word
# search_query = search_query + neighbour.word + " "
if "film" in category:
#if c is "film":
print "\n\n in film:"
film = cate_obj.search_film(search_query)
print film
elif "books" in category:
books = cate_obj.search_books(search_query)
elif "people" in category:
people = cate_obj.search_people(search_query)
elif "location" in category:
location = cate_obj.search_location(search_query)
else:
pass
# search_query = "sachin"
print "do web search"
try:
res = bing.do_web_search(search_query)
for i in res["SearchResponse"]["Web"]["Results"]: #Removing current URL
if i["Url"]==url:
res["SearchResponse"]["Web"]["Results"].remove(i)
dump_res = json.dumps({"keyword":keyword,"category":category,"search_res":res["SearchResponse"]["Web"]["Results"][0:5],"film":film,"books":books,"people":people,"location":location})
return_string += dump_res+","
print "web search done"
except Exception:
print "search not done"
pass
#print return_string
# import pdb;pdb.set_trace();
return return_string
def search_web(doc_freq):
txt= '{"result":'
#txt += json.dumps(doc_freq)
txt += "}"
print "\n\n\n"
print txt
return_string ='{"final_results":['
i=0
cate_obj = cate_mongo_specific1.categorization()
#bing = bingapi.Bing(app_ID)
bing = getbingid()
print "\n\nKEYWORDS:"
film =" "
books=" "
people = " "
location =" "
for l in doc_freq:
str1 = ' '.join(l.keyword)
print "keyword:" + str1
category = cate_obj.get_category(str1) #get category of keyword
print category
for n in l.neighbours:
str1 = str1 + " " + n.word
search_query = str1
print "search_query::::::::" + str1
#for neighbour in df.neighbours:
# print neighbour.word
# search_query = search_query + neighbour.word + " "
if "film" in category:
#if c is "film":
print "\n\n in film:"
film = cate_obj.search_film(search_query)
print film
if "books" in category:
books = cate_obj.search_books(search_query)
if "people" in category:
people = cate_obj.search_people(search_query)
if "location" in category:
location = cate_obj.search_location(search_query)
# else:
# film ="empty"
res = bing.do_web_search(search_query)
dump_res = json.dumps({"keyword":search_query,"category":category,"search_res":res["SearchResponse"]["Web"]["Results"],"film":film,"books":books,"people":people,"location":location})
return_string += dump_res + ","
return_string +='{"test":"dummy_res"}' #Add dummy result for comma after last result
return_string += "]}"
#return_string ='{"final_results":['
#i=0
#bing = bingapi.Bing(app_ID)
#bing = getbingid()
#Getting Search results for each keywords and this loop builds json object. structure final_results:[array whr each element is {keyword:value, search_res:[arr of search res]}]
# obj = CT()
# for kw in keywords:
# category = obj.get_category(kw)
# search_query = ' '.join(kw.neighbours)
# category= "cat"
# res = bing.do_web_search(search_query)
# dump_res = json.dumps({"keyword":kw,"category":category,"search_res":res["SearchResponse"]["Web"]["Results"]})
# return_string += dump_res + ","
# return_string +='{"test":"dummy_res"}' #Add dummy result for comma after last result
# return_string += "]}"
print return_string
return return_string
