def _build_adjacency_graph(self, entries, domains):
"""
Constructs adjacency graph for outgoing links, saves to self.adj_graph
todo: mv ES entries/documents parsing in separate function?
:param entries: An iterable that contains the ES entries.
Preferably a generator to reduce RAM usage.
:param domains: If non-empty then inspect only the links that point
to webpages under these domains
:return: adjacency matrix
:rtype: ``list`` of tuples
"""
entries = entries or self.entries
adj_graph = []
for e in entries:
if '_source' in e:
# if called by `calc_page_pop.py` then `e` is an ES document
e = e['_source']
if 'domain' in e:
# entry from crawled page
origin = e['domain']
elif 'source' in e:
# entry from anchor text
origin = e['source']
else:
logger.warning('rank_pages: Unable to process: %s' % e)
continue
origin = utils.extract_domain_from_url(origin)
if is_valid_onion(origin):
origin_idx = self._get_domain_idx(origin)
links = e.get('links', []) # crawled case
if 'target' in e: # anchor case
links.append({'link': e['target']})
for l in links:
# ignore SE-spam links
if is_legit_link(l, e):
url = l['link']
if is_valid_full_onion_url(url):
destiny = utils.extract_domain_from_url(url)
# if domains non-empty ignore any other origins
if not domains or destiny in domains:
if destiny != origin:
destiny_idx = self._get_domain_idx(destiny)
adj_graph.append((origin_idx, destiny_idx))
self.num_links = len(adj_graph) # total links
adj_graph = set(adj_graph) # count only 1 edge of source->destiny
self.num_edges = len(adj_graph) # unique links
return adj_graph
def _build_adjacency_graph(self, entries, domains):
"""
Constructs adjacency graph for outgoing links, saves to self.adj_graph
todo: mv ES entries/documents parsing in separate function?
:param entries: An iterable that contains the ES entries.
Preferably a generator to reduce RAM usage.
:param domains: If non-empty then inspect only the links that point
to webpages under these domains
:return: adjacency matrix
:rtype: ``list`` of tuples
"""
entries = entries or self.entries
adj_graph = []
for e in entries:
if '_source' in e:
# if called by `calc_page_pop.py` then `e` is an ES document
e = e['_source']
if 'domain' in e:
# entry from crawled page
origin = e['domain']
elif 'source' in e:
# entry from anchor text
origin = e['source']
else:
logger.warning('rank_pages: Unable to process: %s' % e)
continue
origin = utils.extract_domain_from_url(origin)
if is_valid_onion(origin):
origin_idx = self._get_domain_idx(origin)
links = e.get('links', []) # crawled case
if 'target' in e: # anchor case
links.append({'link': e['target']})
for l in links:
# ignore SE-spam links
if is_legit_link(l, e):
url = l['link']
if is_valid_full_onion_url(url):
destiny = utils.extract_domain_from_url(url)
# if domains non-empty ignore any other origins
if not domains or destiny in domains:
if destiny != origin:
destiny_idx = self._get_domain_idx(destiny)
adj_graph.append((origin_idx, destiny_idx))
self.num_links = len(adj_graph) # total links
adj_graph = set(adj_graph) # count only 1 edge of source->destiny
self.num_edges = len(adj_graph) # unique links
return adj_graph
def onion_redirect(request):
"""Add clicked information and redirect to .onion address."""
redirect_url = request.GET.get('redirect_url', '')
search_term = request.GET.get('search_term', '')
#Checks for "malicious" URI-schemes that could lead to XSS
#Malicious user is redirected on a 403 error page
#if the previous checks replace a malicious URI-scheme
if not xss_safe(redirect_url):
answer = "Bad request: undefined URI-scheme provided"
return HttpResponseBadRequest(answer)
if not redirect_url or not search_term:
answer = "Bad request: no GET parameter URL."
return HttpResponseBadRequest(answer)
try:
onion = utils.extract_domain_from_url(redirect_url)
if is_valid_full_onion_url(redirect_url):
# currently we can't log i2p clicks due to
# SearchResultsClick.onion_domain having an onion validator
# Also we don't have yet i2p results in order to test it
SearchResultsClick.objects.add_or_increment(
onion_domain=onion,
clicked=redirect_url,
search_term=search_term)
except Exception as error:
logger.error("Error with redirect URL: {0}\n{1}".format(
redirect_url, error))
message = "Redirecting to hidden service."
return redirect_page(message, 0, redirect_url)
def onion_redirect(request):
"""Add clicked information and redirect to .onion address."""
redirect_url = request.GET.get('redirect_url', '')
search_term = request.GET.get('search_term', '')
if not redirect_url or not search_term:
answer = "Bad request: no GET parameter URL."
return HttpResponseBadRequest(answer)
try:
onion = utils.extract_domain_from_url(redirect_url)
if is_valid_full_onion_url(redirect_url):
# currently we can't log i2p clicks due to
# SearchResultsClick.onion_domain having an onion validator
# Also we don't have yet i2p results in order to test it
SearchResultsClick.objects.add_or_increment(
onion_domain=onion,
clicked=redirect_url,
search_term=search_term)
except Exception as error:
logger.error("Error with redirect URL: {0}\n{1}".format(
redirect_url, error))
message = "Redirecting to hidden service."
return redirect_page(message, 0, redirect_url)
def onion_redirect(request):
"""Add clicked information and redirect to .onion address."""
redirect_url = request.GET.get('redirect_url', '')
search_term = request.GET.get('search_term', '')
if not redirect_url or not search_term:
answer = "Bad request: no GET parameter URL."
return HttpResponseBadRequest(answer)
try:
onion = utils.extract_domain_from_url(redirect_url)
if is_valid_full_onion_url(redirect_url):
# currently we can't log i2p clicks due to
# SearchResultsClick.onion_domain having an onion validator
# Also we don't have yet i2p results in order to test it
SearchResultsClick.objects.add_or_increment(
onion_domain=onion,
clicked=redirect_url,
search_term=search_term)
except Exception as error:
logger.error("Error with redirect URL: {0}\n{1}".format(
redirect_url, error))
message = "Redirecting to hidden service."
return redirect_page(message, 0, redirect_url)
def build_adjacency_graph(self, documents):
"""
Constructs adjacency graph for outgoing links, saves to self.adj_graph
:param documents: An iterable that contains the ES documents.
Preferably a generator to reduce RAM usage.
:return: adjacency matrix
:rtype: ``list`` of tuples
"""
documents = documents or self.documents
adj_graph = []
for doc in documents:
source = doc['_source']
if 'domain' in source:
origin = source['domain']
elif 'source' in source:
origin = source['source']
else:
logger.info('rank_pages: Unable to process: %s' % source)
continue
origin = utils.extract_domain_from_url(origin)
if is_valid_onion(origin):
origin_idx = self._get_domain_idx(origin)
links = source.get('links', []) # crawled case
if 'target' in source: # anchor case
links.append({'link': source['target']})
for l in links:
url = l['link']
if is_valid_full_onion_url(url):
destiny = utils.extract_domain_from_url(url)
if destiny != origin:
destiny_idx = self._get_domain_idx(destiny)
adj_graph.append((origin_idx, destiny_idx))
self.num_links = len(adj_graph) # total links
adj_graph = set(adj_graph) # count only 1 edge of source->destiny
self.num_edges = len(adj_graph) # unique links
return adj_graph
