445 lines
14 KiB
Python
445 lines
14 KiB
Python
import cassandra
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import cassandra.cluster
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import random
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import os
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import pkg_resources
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import datetime
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from websucker.parser import normalize_link,urlunparse
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VERSION = "sucker6"
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def get_schema():
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with pkg_resources.resource_stream(__name__,"schema.sql") as f:
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schema = f.read()
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return str(schema,encoding="utf8")
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class Data:
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"""
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Database of text documents
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"""
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def __init__(self,keyspace="websucker",cassandra_host="127.0.0.1",cassandra_port=9042):
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# execution profile
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ep = cassandra.cluster.ExecutionProfile(request_timeout=240.0)
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profiles = {cassandra.cluster.EXEC_PROFILE_DEFAULT:ep}
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self.cluster = cassandra.cluster.Cluster([cassandra_host],port=cassandra_port,execution_profiles=profiles)
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self.session = self.cluster.connect(keyspace)
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self.check_document_select_query = self.session.prepare("SELECT count(url_hash) FROM paragraph_checksums WHERE checksum=?" )
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self.index_response_link_update = self.session.prepare("""
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UPDATE links SET
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link_status ='redirect',
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redirect_target = ?,
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update_time = toTimestamp(now())
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WHERE
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domain_name=? AND
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url_path=? AND
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url_query=?
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""")
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self.domain_quality_update = self.session.prepare("""
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UPDATE domain_quality SET
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seen_count=?,
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good_size=?,
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good_count=?,
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good_probability=?,
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good_originality=?,
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average_good_characters=?,
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content_size=?,
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content_count=?,
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content_probability=?,
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content_originality=?,
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average_content_characters=?,
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fetched_count=?,
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average_fetched_good_characters=?,
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gain_ratio=?,
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update_time = toTimestamp(now())
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WHERE
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domain_name=? AND
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day=toDate(now())
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""")
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self.index_response_insert_html = self.session.prepare("""
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INSERT INTO html(
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day,
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domain_name,
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source_link,
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target_link,
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redirect_links,
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status,
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headers,
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content,
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agent_version,
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update_time
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) VALUES (toDate(now()),?,?,?,?,?,?,?,?,toTimestamp(now()));
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""")
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self.index_content_link_insert = self.session.prepare("""
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INSERT INTO links (
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url_schema,
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domain_name,
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url_path,
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url_query,
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link_status,
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update_time
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) VALUES (?,?,?,?,'seen',?) IF NOT EXISTS
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""")
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self.daily_links_insert = self.session.prepare("""
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INSERT INTO daily_links (
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day,
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domain_name,
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url_path,
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url_query,
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link_status,
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body_size,
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link_originality,
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update_time
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) VALUES (toDate(now()),?,?,?,?,?,?,toTimestamp(now()))
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""")
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self.daily_links_select = self.session.prepare("""
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SELECT
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domain_name,
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link_status,
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count(link_status)
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FROM daily_links WHERE day=toDate(now()) GROUP BY domain_name,link_status
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""")
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# PArsed Content
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self.index_content_content_insert = self.session.prepare("""
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INSERT INTO content(
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domain_name,
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target_link,
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links,
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title,
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description,
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section,
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authors,
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tags,
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article_published_time,
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text_date,
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body,
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body_size,
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agent_version,
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update_time
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) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?);
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""")
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self.paragraph_checksums_insert = self.session.prepare("INSERT INTO paragraph_checksums (checksum,url_hash) VALUES(?,?)")
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self.index_content_links_update = self.session.prepare("UPDATE links SET link_status=?, link_originality=?,body_size=?,url_schema=? WHERE domain_name=? AND url_path = ? AND url_query=? ")
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self.check_domain_count = self.session.prepare("select count(url_path) from links where domain_name=? and link_status = ?")
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self.check_domain_size = self.session.prepare("select sum(body_size),sum(link_originality) from links where domain_name=? and link_status =?")
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self.domains_select = self.session.prepare("SELECT domain_name,seen_count,fetched_count,gain_ratio,average_fetched_good_characters FROM domain_quality PER PARTITION LIMIT 1")
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def index_responses(self,source_link,responses):
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# Redirect links
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pl = normalize_link(source_link)
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for response in responses:
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tl = response.get_canonical()
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r = (
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tl,
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pl[1],
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pl[2],
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pl[3],
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)
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if pl != tl:
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res = self.session.execute(self.index_response_link_update,r)
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d = (
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pl[1],
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source_link,
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response.get_canonical(),
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response.redirects,
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response.status,
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response.headers,
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response.get_content(),
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VERSION,
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)
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self.session.execute(self.index_response_insert_html,d)
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def daily_report(self):
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rows = self.session.execute(self.daily_links_select)
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for row in rows:
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print(row[0],row[1],row[2])
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def index_follow_links(self,parser,links,connection):
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# Index seen links
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follow_links = set()
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for l in links:
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if parser.is_link_good(l):
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#if connection is not None and parser.listen_robot and not connection.is_robot_good(l):
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# continue
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link = normalize_link(l,strip_query=parser.strip_query)
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follow_links.add(urlunparse(link))
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newlinkdomains = set()
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for link in follow_links:
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value = []
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nl = normalize_link(link)
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value += nl
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value.append(datetime.date.today())
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rows = self.session.execute(self.index_content_link_insert,value)
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row = rows.one()
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if row.applied:
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newlinkdomains.add(nl[1])
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for domain in newlinkdomains:
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self.check_domain(domain)
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def index_content(self,target_link,parsed_document):
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nl = normalize_link(target_link)
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domain_name = nl[1]
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assert len(domain_name) > 1
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pd = parsed_document
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body_length = 0
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if pd.body is not None:
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body_length = len(pd.body)
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value = (
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domain_name,
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target_link,
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pd.get_links(),
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pd.title,
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pd.description,
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pd.section,
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pd.authors,
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pd.tags,
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pd.article_published_time,
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pd.text_date,
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pd.body,
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body_length,
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VERSION,
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pd.current_time
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)
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content_future = self.session.execute_async(self.index_content_content_insert,value)
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# result later
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link_status = "good"
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originality = 0
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tsz = 0
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if pd.body is None:
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link_status = "bad_parse"
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else:
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tsz = len(pd.body)
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if tsz < 300:
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link_status = "bad_small"
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if link_status == "good":
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futures = []
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for pc,psz in zip(pd.paragraph_checksums,pd.paragraph_sizes):
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fut = self.session.execute_async(self.paragraph_checksums_insert,(pc,hash(nl[1] + "/" + nl[2] + "?" + nl[3])))
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futures.append(fut)
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for fut in futures:
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fut.result()
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originality = self.check_document(pd.paragraph_checksums,pd.paragraph_sizes)
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if originality < 0.8:
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link_status = "bad_copy"
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print(nl)
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self.session.execute(self.index_content_links_update,(link_status,originality,tsz,nl[0],nl[1],nl[2],nl[3]))
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content_future.result()
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print("<<<< " + link_status + " " + str(originality))
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dl = (
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nl[1],
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nl[2],
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nl[3],
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link_status,
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tsz,
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originality
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)
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self.session.execute(self.daily_links_insert,dl)
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def check_document(self,paragraph_checksums,paragraph_sizes):
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tsz = sum(paragraph_sizes)
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if tsz == 0:
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return 0
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copies = 0
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futures = []
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for pc,psz in zip(paragraph_checksums,paragraph_sizes):
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futures.append(self.session.execute_async(self.check_document_select_query,(pc,)))
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for fut,psz in zip(futures,paragraph_sizes):
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rows = fut.result()
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res = rows.one()[0]
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if res > 1:
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copies += psz
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return (tsz-copies)/tsz
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def check_domain(self, domain):
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assert len(domain) > 0
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seen_count = None
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good_size = None
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good_count = None
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good_probability = None
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good_originality = None
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average_good_characters = None
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content_size = None
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content_count = None
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content_probability = None
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content_originality = None
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average_content_characters = None
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fetched_count = None
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average_fetched_good_characters = None
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gain_ratio = None
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counts = {
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"good":0,
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"bad_copy":0,
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"bad_small":0,
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"bad_httpcode":0,
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"bad_type":0,
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"bad_content":0,
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"bad_parse":0,
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"seen":0
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}
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for k in counts.keys():
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res = self.session.execute(self.check_domain_count,(domain,k))
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co = res.one()[0]
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counts[k]= co
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seen_count = counts["seen"]
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good_count = counts["good"]
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content_count = counts["good"] + counts["bad_copy"] + counts["bad_small"]
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fetched_count = sum(counts.values()) - counts["seen"]
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if fetched_count > 0:
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content_probability = content_count / fetched_count
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good_probability = good_count / fetched_count
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sizes = {
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"good":0,
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"bad_copy":0,
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"bad_small":0
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}
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originalities ={}
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for k in sizes.keys():
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res = self.session.execute(self.check_domain_size,(domain,k))
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row = res.one()
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co =row[0]
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originalities[k] = row[1]
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sizes[k]= co
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good_size = sizes["good"]
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content_size = sum(sizes.values())
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if good_count > 0:
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good_originality = originalities["good"] / good_count
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if content_count > 0:
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content_originality = sum(originalities.values()) / content_count
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if good_count > 0:
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average_good_characters = good_size / good_count * good_originality
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average_fetched_good_characters = good_size * good_originality / fetched_count
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gain_ratio = average_fetched_good_characters / fetched_count
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if content_count > 0:
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average_content_characters = content_size / content_count
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#print(sizes)
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#print(originalities)
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uv = (
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seen_count,
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good_size,
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good_count,
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good_probability,
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good_originality,
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average_good_characters,
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content_size,
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content_count,
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content_probability,
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content_originality,
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average_content_characters,
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fetched_count,
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average_fetched_good_characters,
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gain_ratio,
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domain)
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if fetched_count > 0 or seen_count > 0:
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self.session.execute(self.domain_quality_update,uv)
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return average_fetched_good_characters
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def all_domains(self,count):
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rows = self.session.execute(self.domains_select)
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domains = []
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for row in rows:
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domain = row[0]
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seen_count = row[1]
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fetched_count = row[2]
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gain_ratio = row[3]
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afg = row[4]
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if fetched_count and afg and seen_count:
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domains.append(tuple(row))
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l = len(domains)
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ss = min(l,count)
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res = []
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if ss > 0:
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# sort according to ratio
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res = list(sorted(domains,key=lambda x:x[4],reverse=True))[0:ss]
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# returns sorted list of tuples domain,gain_ratio
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return res
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def get_best_domains(self,count):
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# get all domains
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rows = self.session.execute(self.domains_select)
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domains = []
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for row in rows:
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domain = row[0]
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seen_count = row[1]
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fetched_count = row[2]
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gain_ratio = row[3]
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afg = row[4]
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if seen_count and fetched_count and gain_ratio:
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domains.append((domain,gain_ratio))
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l = len(domains)
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ss = min(l,count)
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res = []
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if ss > 0:
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# sort according to ratio
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res = list(sorted(domains,key=lambda x:x[1],reverse=True))[0:ss]
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# returns sorted list of tuples domain,gain_ratio
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return res
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def get_unvisited_domains(self,count):
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# get all domains
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rows = self.session.execute(self.domains_select)
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domains = []
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for row in rows:
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domain = row[0]
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seen_count = row[1]
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fetched_count = row[2]
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gain_ratio = row[3]
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afg = row[4]
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if seen_count and not fetched_count:
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domains.append(domain)
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ss = min(len(domains),count)
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return random.sample(domains,ss)
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def get_visit_links(self,domain,recent_count,old_count,random_count):
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dblinks = []
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rows = self.session.execute("SELECT url_schema,url_path,url_query,update_time FROM links Where domain_name=%s AND link_status='seen'",(domain,))
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for row in rows:
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link = urlunparse((row[0],domain,row[1],row[2]))
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dblinks.append((link,row[3]))
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visitlinks = []
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dblinks.sort(key=lambda x:x[1])
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random_links = []
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for i,(link,time) in enumerate(dblinks):
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#print(link,time)
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if i < recent_count:
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visitlinks.append(link)
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elif i >= len(dblinks) - old_count:
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visitlinks.append(link)
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else:
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random_links.append(link)
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sc = min(random_count,len(random_links))
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if sc > 0:
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visitlinks += random.sample(random_links,sc)
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return visitlinks
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