websucker-pip/websucker/db.py

import cassandra
import cassandra.cluster
import cassandra.query
import random
import os
import pkg_resources
import datetime
from websucker.parser import normalize_link,urlunparse
import collections
import math
import json

VERSION = "sucker6"


def get_schema():
    with pkg_resources.resource_stream(__name__,"schema.sql") as f:
        schema = f.read()
        return str(schema,encoding="utf8")

class Data:
    """
    Database of text documents
    """
    def __init__(self,keyspace="websucker",cassandra_host="127.0.0.1",cassandra_port=9042):
        #print("Database {}@{}:{}".format(keyspace,cassandra_host, cassandra_port))
        # execution profile
        ep = cassandra.cluster.ExecutionProfile(request_timeout=240.0)
        profiles = {cassandra.cluster.EXEC_PROFILE_DEFAULT:ep}
        self.cluster = cassandra.cluster.Cluster([cassandra_host],port=cassandra_port,execution_profiles=profiles)
        self.session = self.cluster.connect(keyspace)

        self.check_document_select_query = self.session.prepare("SELECT count(url_hash) FROM paragraph_checksums WHERE checksum=?" )



        self.update_links = self.session.prepare("""
        UPDATE links SET 
        link_status = ?,
        redirect_target = ?,
        update_time = toTimestamp(now())
        WHERE
        domain_name=? AND
        url_path=? AND
        url_query=? 
        """)

        self.domain_quality_update = self.session.prepare("""
        UPDATE domain_quality SET 
            seen_count=?,
            good_size=?,
            good_count=?,
            good_probability=?,
            good_originality=?,
            average_good_characters=?,
            content_size=?,
            content_count=?,
            content_probability=?,
            content_originality=?,
            average_content_characters=?,
            fetched_count=?,
            average_fetched_good_characters=?,
            gain_ratio=?,
            update_time = toTimestamp(now())
        WHERE
            domain_name=? AND
            day=toDate(now())
        """)

        self.index_response_insert_html = self.session.prepare("""
INSERT INTO html(
  day,
  domain_name,
  source_link,
  target_link,
  redirect_links,
  status,
  headers,
  content,
  agent_version,
  update_time
  ) VALUES (toDate(now()),?,?,?,?,?,?,?,?,toTimestamp(now()));
""")

        self.index_content_link_insert = self.session.prepare("""
INSERT INTO links (
url_schema,
domain_name,
url_path,
url_query,
link_status,
update_time
) VALUES (?,?,?,?,'seen',?) IF NOT EXISTS
""")

        self.daily_links_insert = self.session.prepare("""
INSERT INTO daily_links (
day,
domain_name,
url_path,
url_query,
link_status,
body_size,
link_originality,
update_time
) VALUES (toDate(now()),?,?,?,?,?,?,toTimestamp(now()))
""")
        self.daily_links_select = self.session.prepare("""
SELECT 
domain_name,
link_status,
count(link_status) 
FROM daily_links WHERE day=toDate(now()) GROUP BY domain_name,link_status
""")
        # PArsed Content
        self.index_content_content_insert = self.session.prepare("""
INSERT INTO content(
  domain_name,
  target_link,
  links,
  title,
  description,
  section,
  authors,
  tags,
  article_published_time,
  text_date,
  body,
  body_size,
  agent_version,
  update_time
  ) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?);
""")

        self.paragraph_checksums_insert = self.session.prepare("INSERT INTO paragraph_checksums (checksum,url_hash) VALUES(?,?)")
        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=? ")
        self.check_domain_count = self.session.prepare("select count(url_path) from links where domain_name=? and link_status = ?")

        self.check_domain_size = self.session.prepare("select sum(body_size),sum(link_originality) from links where domain_name=? and link_status =?")

        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")


    def index_responses(self,source_link,responses):
        # Redirect links
        pl = normalize_link(source_link)
        domain = pl[1]
        npl = urlunparse(pl)
        for response in responses:
            tl = response.get_canonical()
            if npl != tl:
                self.update_link_status(npl,"redirect",tl)
            d = (
                domain,
                npl,
                tl,
                response.redirects,
                response.status,
                response.headers,
                response.get_content(),
                VERSION,
            )
            self.session.execute(self.index_response_insert_html,d)

    def summary(self,parser):
        gs = 0
        cs = 0
        fetched_documents = 0
        vd = 0
        unvisited_domains = 0
        unvisited_junk_domains = 0
        sl = 0
        fd = 0
        junk_domains = 0
        rows = self.session.execute("SELECT domain_name,good_size,content_size, fetched_count,seen_count FROM domain_quality PER PARTITION LIMIT 1")
        # TODO submdomain analysis
        #dd = collections.defaultdict(set)
        second_level = set()
        for row in rows:
            domain = row[0]
            subdomains = domain.split(".")
            #d2 = subdomains[-2] + "." + subdomains[-1]
            if len(subdomains) > 2:
                d3 = ".".join(subdomains[0:-2])
                second_level.add(d3)
            if not parser.is_domain_good(domain):
                junk_domains += 1
            if row[1] is not None:
                gs += row[1]
            if row[2] is not None:
                cs += row[2]
            if row[3] is not None:
                fetched_documents += row[3]
            if row[4] is not None:
                sl += row[4]
            if row[3] is None or row[3] == 0:
                unvisited_domains += 1
                if not parser.is_domain_good(domain):
                    unvisited_junk_domains += 1
            else:
                vd += 1
                if row[4] is None or row[4] == 0:
                    fd += 1
        print("Good characters: {}".format(gs))
        print("Fetched characters: {}".format(cs))
        print("Fetched documents: {}".format(fetched_documents))
        print("Visited domains: {}".format(vd))
        print("Unvisited domains: {}".format(unvisited_domains))
        print("Junk domains: {}".format(junk_domains))
        print("Unvisited junk domains: {}".format(unvisited_junk_domains))
        print("New links : {}".format(sl))
        print("Second level domains: {}".format(len(second_level)))
        print("Finished domains : {}".format(fd))
        #for d,sd in dd.items():
        #    if len(sd) > 1:
        #        print(d + " " +  ",".join(sd))

    def daily_report(self):
        #rows = self.session.execute(self.daily_links_select)
        rows = self.session.execute("SELECT domain_name,count(link_status) FROM daily_links WHERE day=toDate(now()) GROUP BY day,domain_name")
        domains = []
        for row in rows:
            domains.append(list(row))
        total_count = 0
        total_size = 0
        out = []
        for domain,count in domains:
            if count < 2:
                continue
            total_count += count
            rows = self.session.execute("SELECT link_status,count(link_status),sum(body_size) FROM daily_links WHERE day=toDate(now()) AND domain_name=%s GROUP BY day,domain_name,link_status",(domain,))
            gc = 0
            bs = 0
            for row in rows:
                if row[0] == "good":
                    gc = row[1]
                    bs = row[2]
                    total_size += bs
            out.append((domain,bs,gc/count,count))
        print("Domain, characters,good ratio,documents")
        for i,value in enumerate(reversed(sorted(out,key=lambda x: x[3]))):
            if i < 20:
                print(value)
                #print("{},{},{},{}".format(value))
                
        print("{} domains, {} documents, {} characters ".format(len(domains),total_count,total_size))

    def update_link_status(self,link,status,redirect_target=None):
        pl = normalize_link(link)
        r = (
            status,
            redirect_target,
            pl[1],
            pl[2],
            pl[3],
        )
        res = self.session.execute(self.update_links ,r)

    def index_follow_links(self,parser,links,connection):
        # Index seen links
        follow_links = set()
        for l in links:
            if parser.is_link_good(l):
                #if connection is not None and parser.listen_robot and not connection.is_robot_good(l):
                #    continue
                link = normalize_link(l,strip_query=parser.strip_query)
                follow_links.add(urlunparse(link))

        newlinkdomains = set()
        newlinkcount = 0
        for link in follow_links:
            value = []
            nl = normalize_link(link)
            value +=  nl
            value.append(datetime.date.today())
            rows = self.session.execute(self.index_content_link_insert,value)
            row = rows.one()
            if row.applied:
                newlinkdomains.add(nl[1])
                newlinkcount += 1
        for domain in newlinkdomains:
            self.check_domain(domain)
        print("{} new links, {} new domains".format(newlinkcount,len(newlinkdomains)))


    def index_content(self,target_link,parsed_document):
        nl = normalize_link(target_link)
        domain_name = nl[1]
        assert len(domain_name) > 1

        pd = parsed_document
        body_length = 0
        if pd.body is not None:
            body_length = len(pd.body)
        value = ( 
          domain_name,
          target_link,
          pd.get_links(),
          pd.title,
          pd.description,
          pd.section,
          pd.authors,
          pd.tags,
          pd.article_published_time,
          pd.text_date,
          pd.body,
          body_length,
            VERSION,
          pd.current_time
        )
        content_future = self.session.execute_async(self.index_content_content_insert,value)
        # result later

        link_status = "good"
        originality = 0
        tsz = 0
        if pd.body is None:
            link_status = "bad_parse"
        else:
            tsz = len(pd.body)
            if tsz < 300:
                link_status = "bad_small"

        if link_status == "good":

            futures = []
            for pc,psz in zip(pd.paragraph_checksums,pd.paragraph_sizes):
                fut = self.session.execute_async(self.paragraph_checksums_insert,(pc,hash(nl[1] + "/" + nl[2] + "?" + nl[3])))
                futures.append(fut)
            for fut in futures:
                fut.result()
            originality = self.check_document(pd.paragraph_checksums,pd.paragraph_sizes)
            if originality < 0.8:
                link_status = "bad_copy"
        self.session.execute(self.index_content_links_update,(link_status,originality,tsz,nl[0],nl[1],nl[2],nl[3]))
        content_future.result()
        print("<<<< " + link_status + " " + str(originality))
        dl = (
            nl[1],
            nl[2],
            nl[3],
            link_status,
            tsz,
            originality
        )
        self.session.execute(self.daily_links_insert,dl)

    def check_document(self,paragraph_checksums,paragraph_sizes):
       tsz = sum(paragraph_sizes)
       if tsz == 0:
           return 0
       copies = 0
       futures = []
       for pc,psz in zip(paragraph_checksums,paragraph_sizes):
           futures.append(self.session.execute_async(self.check_document_select_query,(pc,)))

       for fut,psz in zip(futures,paragraph_sizes):
           rows = fut.result()
           res = rows.one()[0]
           if res > 1:
               copies += psz
       return (tsz-copies)/tsz


    def check_domain(self, domain):
        assert len(domain) > 0
        seen_count = None
        good_size = None
        good_count = None
        good_probability = None
        good_originality = None
        average_good_characters = None
        content_size = None
        content_count = None
        content_probability = None
        content_originality = None
        average_content_characters = None
        fetched_count = None
        average_fetched_good_characters = None
        gain_ratio = None

        counts = {
            "good":0,
            "bad_copy":0,
            "bad_small":0,
            "bad_httpcode":0,
            "bad_type":0,
            "bad_content":0,
            "bad_parse":0,
            "seen":0
        }
        for k in counts.keys():
            res = self.session.execute(self.check_domain_count,(domain,k))
            co = res.one()[0]
            counts[k]= co

        seen_count = counts["seen"]
        good_count = counts["good"]
        content_count = counts["good"] + counts["bad_copy"] + counts["bad_small"]

        fetched_count = sum(counts.values()) - counts["seen"]

        if fetched_count > 0:
            content_probability = content_count / fetched_count
            good_probability = good_count / fetched_count
            sizes = {
                "good":0,
                "bad_copy":0,
                "bad_small":0
            }

            originalities ={}

            for k in sizes.keys():
                res = self.session.execute(self.check_domain_size,(domain,k))
                row = res.one()
                co =row[0]
                originalities[k] = row[1]
                sizes[k]= co
            good_size = sizes["good"]
            content_size = sum(sizes.values())
            if good_count > 0:
                good_originality = originalities["good"] / good_count
            if content_count > 0:
                content_originality =  sum(originalities.values()) / content_count
        
        if good_count > 0:
            average_good_characters = good_size / good_count  * good_originality
            average_fetched_good_characters = good_size * good_originality / fetched_count

            gain_ratio = average_fetched_good_characters / fetched_count

        if content_count > 0:
            average_content_characters = content_size / content_count

        #print(sizes)
        #print(originalities)
        uv = (
        seen_count,
        good_size,
        good_count,
        good_probability,
        good_originality,
        average_good_characters,
        content_size,
        content_count,
        content_probability,
        content_originality,
        average_content_characters,
        fetched_count,
        average_fetched_good_characters,
        gain_ratio,
        domain)
        if fetched_count > 0 or seen_count > 0:
            self.session.execute(self.domain_quality_update,uv)
        return average_fetched_good_characters

    def all_domains(self,count):
        rows = self.session.execute(self.domains_select)
        domains = []
        for row in rows:
            domain = row[0]
            seen_count = row[1]
            fetched_count = row[2]
            gain_ratio = row[3]
            afg = row[4]
            if fetched_count and afg and seen_count:
                domains.append(tuple(row))
        l = len(domains)
        ss = min(l,count)
        res = []
        if ss > 0:
            # sort according to ratio
            res = list(sorted(domains,key=lambda x:x[4],reverse=True))[0:ss]
        # returns sorted list of tuples domain,gain_ratio
        return res

    def get_best_domains(self,count,parser):
        # get all domains
        rows = self.session.execute(self.domains_select)
        domains = []
        for row in rows:
            domain = row[0]
            seen_count = row[1]
            fetched_count = row[2]
            gain_ratio = row[3]
            afg = row[4]
            if seen_count and fetched_count and gain_ratio and parser.is_domain_good(domain):
                domains.append(list(row))
        l = len(domains)
        ss = min(l,count)
        res = []
        if ss > 0:
            # sort according to ratio
            res = list(sorted(domains,key=lambda x:x[3],reverse=True))[0:ss]
        # returns sorted list of tuples domain,gain_ratio
        return res

    def get_random_domains(self,count,parser):
        # get all domains
        rows = self.session.execute(self.domains_select)
        domains = []
        for row in rows:
            domain = row[0]
            if parser.is_domain_good(domain):
                domains.append(list(row))
        l = len(domains)
        ss = min(l,count)
        return random.sample(domains,ss)

    def get_unvisited_domains(self,count,parser):
        # get all domains
        rows = self.session.execute(self.domains_select)
        domains = []
        # Analyze third level domains
        dd = collections.defaultdict(set)
        third_count = 0
        for row in rows:
            domain = row[0]
            seen_count = row[1]
            fetched_count = row[2]
            gain_ratio = row[3]
            afg = row[4]
            if seen_count and not fetched_count:
                subdomains = domain.split(".")
                d2 = subdomains[-2] + "." + subdomains[-1]
                dd[d2].add(domain)
        # Select second level first
        result = []
        # then select third level
        ll = list(dd.items()) 
        random.shuffle(ll)
        domain_weight = count / len(ll) 
        for domain,subdomains in ll:
            dl = list(subdomains)
            link_weight = domain_weight / len(dl)
            random.shuffle(dl)
            for d in dl:
                r = random.random()
                if r < link_weight:
                    result.append((d,0))
        return result

    def export_domain(self,domain):
        rows = self.session.execute("SELECT JSON * from content WHERE domain_name=%s",(domain,))
        for row in rows:
            print(row[0])
    
    def get_visit_links(self,domain,recent_count,old_count,random_count):
        dblinks = []
        rows = self.session.execute("SELECT url_schema,url_path,url_query,update_time FROM links Where domain_name=%s AND link_status='seen'",(domain,))
        for row in rows:
            link = urlunparse((row[0],domain,row[1],row[2]))
            dblinks.append((link,row[3]))

        visitlinks = []
        dblinks.sort(key=lambda x:x[1])
        random_links = []
        for i,(link,time) in enumerate(dblinks):
            #print(link,time)
            if i < recent_count:
                visitlinks.append(link)
            elif i >= len(dblinks) - old_count:
                visitlinks.append(link)
            else:
                random_links.append(link)
        sc = min(random_count,len(random_links))
        if sc > 0:
            visitlinks += random.sample(random_links,sc)
        return visitlinks