def gather_topics(addresslist, site):
"""Downloads, parses and pickles all the topics from a list of addresses.
addresslist - a list of web addresses
site - site name (for bundling topics)
"""
for address in addresslist:
parsed = parse(address, True)
with open(os.path.join(train_path,site,re.findall('[^/]*$',address)[0]), 'w') as file:
pickle.dump(parsed, file)
def search(request):
requestDict = request.POST
template = loader.get_template('search.html')
if 'question' not in requestDict:
return HttpResponse(template.render(
RequestContext(request,
{'title': 'No question',
'question': 'Please write the question URL first'
})))
questionURL = requestDict['question']
parsed = tparser.parse(questionURL)
if 'drupal' in questionURL:
posts = choose_answers('ent-sam-dru', parsed)
bestpost = choose_answer('ent-sam-dru', parsed)
elif 'ubuntu' in questionURL:
posts = choose_answers('ent-sam-ubu', parsed)
bestpost = choose_answer('ent-sam-ubu', parsed)
else:
posts = choose_answers('ent-sam-mix', parsed)
bestpost = choose_answer('ent-sam-mix', parsed)
#pdb.set_trace()
#Do some NLP magic here...
#vimpdb.set_trace()
#posts = nlpsort.magic(posts)
#response = ['good response', 'not so good response']
#response = test.post(0)
context = RequestContext(request,
{'title': 'Natural language search engine',
'question': questionURL,
'response': bestpost,
'others': posts,
'link': bestpost.link})
return HttpResponse(template.render(context))
