def __init__(self,dbname):
self.con = sqlite.connect(dbname)
self.net = nn.searchnet(dbname)
import urllib
from bs4 import BeautifulSoup
from urllib.parse import urljoin
import urllib.request
import sqlite3 as sqlite
#from pysqlite2 import dbapi2 as sqlite
#from pysqlite3 import dbapi3
import re
import neuralnetwork as nn
import ssl # 以https开头的网站若ssl证书不通过会报错
mynet = nn.searchnet('nn.db')
# Create a list of words to ignore
ignorewords = {'the':1,'of':1,'to':1,'and':1,'a':1,'in':1,'is':1,'it':1}
class crawler:
# Initialize the crawler with the name of database
def __init__(self, dbname):
self.con=sqlite.connect(dbname)
def __del__(self):
self.con.close()
def dbcommit(self):
self.con.commit()
# Auxilliary function for getting an entry id and adding
# it if it's not present
def getentryid(self, table, field, value, createnew=True):
cur = self.con.execute(
"select rowid from %s where %s='%s'" % (table,field,value))
res = cur.fetchone()
if res == None:
import neuralnetwork
mynet = neuralnetwork.searchnet('nn.db')
# mynet.maketables()
wWorld, wRiver, wBank = 101, 102, 103
uWorldBank, uRiver, uEwarth = 201, 202, 203
mynet.generatehiddennode([wWorld, wBank], [uWorldBank, uRiver, uEwarth])
for c in mynet.con.execute("SELECT * FROM wordhidden"): print c
print "------------------"
for c in mynet.con.execute("SELECT * FROM hiddenurl"): print c
crawler = searchengine.crawler(fn)
#crawler.createindextables() # 若 db 已建好，可注释此句
# crawl some pages:
#pagelist=['https://en.wikipedia.org/wiki/R_(programming_language)']
#crawler.crawl(pagelist)
pagelist = ['http://www.diveintopython.net']
#crawler.crawl(pagelist)
# 若 db 已建好，可注释下句
#[row for row in crawler.con.execute('select rowid from wordlocation where wordid=1')]
import neuralnetwork as nn
mynet = nn.searchnet('nn.db')
# mynet.maketables()
wordstosearch = 'python programming'
e = searchengine.searcher('searchindex.db')
e.getmatchrows(wordstosearch)
# create the needed tables for the page rank algorithm:
crawler.calculatepagerank()
# before adding in the page rank algorithm into the weights that form the scoring function
e.query(wordstosearch)
# cur = crawler.con.execute('select * from pagerank order by score desc')
#for i in range(3): print(cur.next())
#e.geturlname(17) # word "python" rowid==17
for (u, score) in linkscores.iteritems()])
return normalizedScores
def neuralNetwordScore(self, rows, wordids):
urlids = [urlid for urlid in set([row[0] for row in rows])]
nnres = mynet.getResult(wordids, urlids)
scores = dict([(urlids[i], nnres[i]) for i in range(len(urlids))])
return self.normalizeScores(scores)
if __name__ == '__main__':
pagelist = []
seedpage = raw_input('Enter the website page address: ')
if seedpage.find('http://') == -1:
seedpage = 'http://' + seedpage
pagelist.append(seedpage)
dbname = raw_input('Enter the database name: ')
if dbname.find('.db') == -1:
dbname += '.db'
crawler = crawler(dbname)
if not os.path.isfile(dbname):
crawler.createIndexTables()
crawler.crawl(pagelist)
crawler.calculatePageRank()
searcher = searcher(dbname)
mynet = neuralnetwork.searchnet('nn.db')
while True:
qStr = raw_input('Enter the query string (press Enter to quit): ')
if qStr == '' or qStr == '\n':
break
searcher.query(qStr)
