Coursera课程笔记----P4E.Capstone----Week 2&3

Building a Search Engine(week 2&3)

Search Engine Architecture

• Web Crawling

• Index Building

• Searching

Web Crawler

A Web crawler is a computer program that browses the World Wide Web in a methodical, automated manner. Web crawlers are mainly used to create a copy of all the visited pages for later processing by a search engine that will index the downloaded pages to provide fast searches.

steps

1. Retrieve a page
2. Look through the page for links
3. Add the links to a list of "to be retrieved" sites
4. repeat...

policy

• selection policy that states which page to download
• re-visit policy that states when to.check for changes to the pages
• politeness policy that states how to avoid overloading Web sites
• parallelization policy that states how to coordinate distributed Web crawlers

robots.txt

• A way for a web site to communicate with web crawlers

• An informal and voluntary standard

• It tells the crawler where to look and where not to look

Search Indexing

Search engine indexing collects, parses, and stores data to facilitate fast and accurate information retrieval. The purpose of storing an index is to optimize speed and performance in finding relevant documents for a search query. Without an index, the search engine would scan every document in the corpus, which would require considerable time and computing power.

code segment

spider.py

import sqlite3
import urllib.error
import ssl
from urllib.parse import urljoin
from urllib.parse import urlparse
from urllib.request import urlopen
from bs4 import BeautifulSoup

# Ignore SSL certificate errors
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE

# Link to sqlite
conn = sqlite3.connect('spider.sqlite')
cur = conn.cursor()

# Create new tables
cur.execute('''CREATE TABLE IF NOT EXISTS Pages
    (id INTEGER PRIMARY KEY, url TEXT UNIQUE, html TEXT,
     error INTEGER, old_rank REAL, new_rank REAL)''')

cur.execute('''CREATE TABLE IF NOT EXISTS Links
    (from_id INTEGER, to_id INTEGER)''')

#This table store only one url which is processing
cur.execute('''CREATE TABLE IF NOT EXISTS Webs (url TEXT UNIQUE)''')

# Check to see if we are already in progress...
cur.execute('SELECT id,url FROM Pages WHERE html is NULL and error is NULL ORDER BY RANDOM() LIMIT 1')
row = cur.fetchone()
if row is not None:
    print("Restarting existing crawl.  Remove spider.sqlite to start a fresh crawl.")
else :
    starturl = input('Enter web url or enter: ')
    if ( len(starturl) < 1 ) : starturl = 'http://www.dr-chuck.com/'
    # delete the "/"
    if ( starturl.endswith('/') ) : starturl = starturl[:-1]
    web = starturl
    if ( starturl.endswith('.htm') or starturl.endswith('.html') ) :
        pos = starturl.rfind('/')
        web = starturl[:pos]

    if ( len(web) > 1 ) :
        cur.execute('INSERT OR IGNORE INTO Webs (url) VALUES ( ? )', ( web, ) )
        cur.execute('INSERT OR IGNORE INTO Pages (url, html, new_rank) VALUES ( ?, NULL, 1.0 )', ( starturl, ) )
        conn.commit()

# Get the current webs
cur.execute('''SELECT url FROM Webs''')
webs = list()
for row in cur:
    webs.append(str(row[0]))

print(webs)

many = 0
while True:
    if ( many < 1 ) :
        sval = input('How many pages:')
        if ( len(sval) < 1 ) : break
        many = int(sval)
    many = many - 1

    cur.execute('SELECT id,url FROM Pages WHERE html is NULL and error is NULL ORDER BY RANDOM() LIMIT 1')
    try:
        row = cur.fetchone()
        # print row
        fromid = row[0]
        url = row[1]
    except:
        print('No unretrieved HTML pages found')
        many = 0
        break

    print(fromid, url, end=' ')

    # If we are retrieving this page, there should be no links from it
    cur.execute('DELETE from Links WHERE from_id=?', (fromid, ) )
    try:
        document = urlopen(url, context=ctx)

        html = document.read()
        if document.getcode() != 200 :
            print("Error on page: ",document.getcode())
            cur.execute('UPDATE Pages SET error=? WHERE url=?', (document.getcode(), url) )

        if 'text/html' != document.info().get_content_type() :
            print("Ignore non text/html page")
            cur.execute('DELETE FROM Pages WHERE url=?', ( url, ) )
            conn.commit()
            continue

        print('('+str(len(html))+')', end=' ')

        soup = BeautifulSoup(html, "html.parser")
    except KeyboardInterrupt:
        print('')
        print('Program interrupted by user...')
        break
    except:
        print("Unable to retrieve or parse page")
        cur.execute('UPDATE Pages SET error=-1 WHERE url=?', (url, ) )
        conn.commit()
        continue

    cur.execute('INSERT OR IGNORE INTO Pages (url, html, new_rank) VALUES ( ?, NULL, 1.0 )', ( url, ) )
    cur.execute('UPDATE Pages SET html=? WHERE url=?', (memoryview(html), url ) )
    conn.commit()

    # Retrieve all of the anchor tags
    tags = soup('a')
    count = 0
    for tag in tags:
        href = tag.get('href', None)
        if ( href is None ) : continue
        # Resolve relative references like href="/contact"
        up = urlparse(href)
        if ( len(up.scheme) < 1 ) :
            href = urljoin(url, href)
        ipos = href.find('#')
        if ( ipos > 1 ) : href = href[:ipos]
        if ( href.endswith('.png') or href.endswith('.jpg') or href.endswith('.gif') ) : continue
        if ( href.endswith('/') ) : href = href[:-1]
        # print href
        if ( len(href) < 1 ) : continue

		# Check if the URL is in any of the webs
        found = False
        for web in webs:
            if ( href.startswith(web) ) :
                found = True
                break
        if not found : continue

        cur.execute('INSERT OR IGNORE INTO Pages (url, html, new_rank) VALUES ( ?, NULL, 1.0 )', ( href, ) )
        count = count + 1
        conn.commit()

        cur.execute('SELECT id FROM Pages WHERE url=? LIMIT 1', ( href, ))
        try:
            row = cur.fetchone()
            toid = row[0]
        except:
            print('Could not retrieve id')
            continue
        # print fromid, toid
        cur.execute('INSERT OR IGNORE INTO Links (from_id, to_id) VALUES ( ?, ? )', ( fromid, toid ) )


    print(count)

cur.close()

sprank.py

import sqlite3

conn = sqlite3.connect('spider.sqlite')
cur = conn.cursor()

# Find the ids that send out page rank - we only are interested
# in pages in the SCC that have in and out links
cur.execute('''SELECT DISTINCT from_id FROM Links''')
from_ids = list()
for row in cur: 
    from_ids.append(row[0])

# Find the ids that receive page rank 
to_ids = list()
links = list()
cur.execute('''SELECT DISTINCT from_id, to_id FROM Links''')
for row in cur:
    from_id = row[0]
    to_id = row[1]
    if from_id == to_id : continue
    if from_id not in from_ids : continue
    if to_id not in from_ids : continue
    links.append(row)
    if to_id not in to_ids : to_ids.append(to_id)

# Get latest page ranks for strongly connected component
prev_ranks = dict()
for node in from_ids:
    cur.execute('''SELECT new_rank FROM Pages WHERE id = ?''', (node, ))
    row = cur.fetchone()
    prev_ranks[node] = row[0]

sval = input('How many iterations:')
many = 1
if ( len(sval) > 0 ) : many = int(sval)

# Sanity check
if len(prev_ranks) < 1 : 
    print("Nothing to page rank.  Check data.")
    quit()

# Lets do Page Rank in memory so it is really fast
for i in range(many):
    # print prev_ranks.items()[:5]
    next_ranks = dict();
    total = 0.0
    for (node, old_rank) in list(prev_ranks.items()):
        total = total + old_rank
        next_ranks[node] = 0.0
    # print total

    # Find the number of outbound links and sent the page rank down each
    for (node, old_rank) in list(prev_ranks.items()):
        # print node, old_rank
        give_ids = list()
        for (from_id, to_id) in links:
            if from_id != node : continue
           #  print '   ',from_id,to_id

            if to_id not in to_ids: continue
            give_ids.append(to_id)
        if ( len(give_ids) < 1 ) : continue
        amount = old_rank / len(give_ids)
        # print node, old_rank,amount, give_ids
    
        for id in give_ids:
            next_ranks[id] = next_ranks[id] + amount
    
    newtot = 0
    for (node, next_rank) in list(next_ranks.items()):
        newtot = newtot + next_rank
    evap = (total - newtot) / len(next_ranks)

    # print newtot, evap
    for node in next_ranks:
        next_ranks[node] = next_ranks[node] + evap

    newtot = 0
    for (node, next_rank) in list(next_ranks.items()):
        newtot = newtot + next_rank

    # Compute the per-page average change from old rank to new rank
    # As indication of convergence of the algorithm
    totdiff = 0
    for (node, old_rank) in list(prev_ranks.items()):
        new_rank = next_ranks[node]
        diff = abs(old_rank-new_rank)
        totdiff = totdiff + diff

    avediff = totdiff / len(prev_ranks)
    print(i+1, avediff)

    # rotate
    prev_ranks = next_ranks

# Put the final ranks back into the database
print(list(next_ranks.items())[:5])
cur.execute('''UPDATE Pages SET old_rank=new_rank''')
for (id, new_rank) in list(next_ranks.items()) :
    cur.execute('''UPDATE Pages SET new_rank=? WHERE id=?''', (new_rank, id))
conn.commit()
cur.close()

spdump.py

import sqlite3

conn = sqlite3.connect('spider.sqlite')
cur = conn.cursor()

cur.execute('''SELECT COUNT(from_id) AS inbound, old_rank, new_rank, id, url 
     FROM Pages JOIN Links ON Pages.id = Links.to_id
     WHERE html IS NOT NULL
     GROUP BY id ORDER BY inbound DESC''')

count = 0
for row in cur :
    if count < 50 : print(row)
    count = count + 1
print(count, 'rows.')
cur.close()

spjson.py

import sqlite3

conn = sqlite3.connect('spider.sqlite')
cur = conn.cursor()

print("Creating JSON output on spider.js...")
howmany = int(input("How many nodes? "))

cur.execute('''SELECT COUNT(from_id) AS inbound, old_rank, new_rank, id, url 
    FROM Pages JOIN Links ON Pages.id = Links.to_id
    WHERE html IS NOT NULL AND ERROR IS NULL
    GROUP BY id ORDER BY id,inbound''')

fhand = open('spider.js','w')
nodes = list()
maxrank = None
minrank = None
for row in cur :
    nodes.append(row)
    rank = row[2]
    if maxrank is None or maxrank < rank: maxrank = rank
    if minrank is None or minrank > rank : minrank = rank
    if len(nodes) > howmany : break

if maxrank == minrank or maxrank is None or minrank is None:
    print("Error - please run sprank.py to compute page rank")
    quit()

fhand.write('spiderJson = {"nodes":[
')
count = 0
map = dict()
ranks = dict()
for row in nodes :
    if count > 0 : fhand.write(',
')
    # print row
    rank = row[2]
    rank = 19 * ( (rank - minrank) / (maxrank - minrank) ) 
    fhand.write('{'+'"weight":'+str(row[0])+',"rank":'+str(rank)+',')
    fhand.write(' "id":'+str(row[3])+', "url":"'+row[4]+'"}')
    map[row[3]] = count
    ranks[row[3]] = rank
    count = count + 1
fhand.write('],
')

cur.execute('''SELECT DISTINCT from_id, to_id FROM Links''')
fhand.write('"links":[
')

count = 0
for row in cur :
    # print row
    if row[0] not in map or row[1] not in map : continue
    if count > 0 : fhand.write(',
')
    rank = ranks[row[0]]
    srank = 19 * ( (rank - minrank) / (maxrank - minrank) ) 
    fhand.write('{"source":'+str(map[row[0]])+',"target":'+str(map[row[1]])+',"value":3}')
    count = count + 1
fhand.write(']};')
fhand.close()
cur.close()

print("Open force.html in a browser to view the visualization")