Automated Discovery of Blog Feeds and Twitter, Facebook, LinkedIn Accounts Connected to Business Website « Data Big Bang Blog

Automated Discovery of Blog Feeds and Twitter, Facebook, LinkedIn Accounts Connected to Business Website « Data Big Bang Blog

January 4, 2012

Automated Discovery of Blog Feeds and Twitter, Facebook, LinkedIn Accounts Connected to Business Website


Prerequisites

  1. Python 2.7 (or greater 2.x series)
  2. lxml.html
  3. parse_domain.py
  4. PyYAML

Script

This code is available at github.

fwc.py

#!/usr/bin/python2.7

import argparse
import sys
from focused_web_crawler import FocusedWebCrawler
import logging
import code
import yaml
from constraint import Constraint

def main():
   logger = logging.getLogger('data_big_bang.focused_web_crawler')
   ap = argparse.ArgumentParser(description='Discover web resources associated with a site.')
   ap.add_argument('input', metavar='input.yaml', type=str, nargs=1, help ='YAML file indicating the sites to crawl.')
   ap.add_argument('output', metavar='output.yaml', type=str, nargs=1, help ='YAML file with the web resources discovered.')

   args = ap.parse_args()

   input = yaml.load(open(args.input[0], "rt"))

   fwc = FocusedWebCrawler()

   for e in input:
      e.update({'constraint': Constraint()})
      fwc.queue.put(e)

   fwc.start()
   fwc.join()

   with open(args.output[0], "wt") as s:
      yaml.dump(fwc.collection, s, default_flow_style = False)

if __name__ == '__main__':
   main()

focused-web-crawler.py

from threading import Thread, Lock
from worker import Worker
from Queue import Queue
import logging

class FocusedWebCrawler(Thread):
   NWORKERS = 10
   def __init__(self, nworkers = NWORKERS):
      Thread.__init__(self)
      self.nworkers = nworkers
      #self.queue = DualQueue()
      self.queue = Queue()
      self.visited_urls = set()
      self.mutex = Lock()
      self.workers = []
      self.logger = logging.getLogger('data_big_bang.focused_web_crawler')
      sh = logging.StreamHandler()
      formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
      sh.setFormatter(formatter)
      self.logger.addHandler(sh)
      self.logger.setLevel(logging.INFO)
      self.collection = {}
      self.collection_mutex = Lock()

   def run(self):
      self.logger.info('Focused Web Crawler launched')
      self.logger.info('Starting workers')
      for i in xrange(self.nworkers):
         worker = Worker(self.queue, self.visited_urls, self.mutex, self.collection, self.collection_mutex)
         self.workers.append(worker)
         worker.start()

      self.queue.join() # Wait until all items are consumed

      for i in xrange(self.nworkers): # send a 'None signal' to finish workers
         self.queue.put(None)

      self.queue.join() # Wait until all workers are notified

#     for worker in self.workers:
#        worker.join()

      self.logger.info('Finished workers')
      self.logger.info('Focused Web Crawler finished')

worker.py

from threading import Thread
from fetcher import fetch
from evaluator import get_all_links, get_all_feeds
from collector import collect
from urllib2 import HTTPError
import logging

class Worker(Thread):
   def __init__(self, queue, visited_urls, mutex, collection, collection_mutex):
      Thread.__init__(self)
      self.queue = queue
      self.visited_urls = visited_urls
      self.mutex = mutex
      self.collection = collection
      self.collection_mutex = collection_mutex
      self.logger = logging.getLogger('data_big_bang.focused_web_crawler')

   def run(self):
      item = self.queue.get()

      while item != None:
         try:
            url = item['url']
            key = item['key']
            constraint = item['constraint']
            data = fetch(url)

            if data == None:
               self.logger.info('Not fetched: %s because type != text/html', url)
            else:
               links = get_all_links(data, base = url)
               feeds = get_all_feeds(data, base = url)
               interesting = collect(links)

               if interesting:
                  self.collection_mutex.acquire()
                  if key not in self.collection:
                     self.collection[key] = {'feeds':{}}

                  if feeds:
                     for feed in feeds:
                        self.collection[key]['feeds'][feed['href']] = feed['type']

                  for service, accounts in interesting.items():
                     if service not in self.collection[key]:
                        self.collection[key][service]  = {}

                     for a,u in accounts.items():
                        self.collection[key][service][a] = {'url': u, 'depth':constraint.depth}
                  self.collection_mutex.release()

               for l in links:
                  new_constraint = constraint.inherit(url, l)
                  if new_constraint == None:
                     continue

                  self.mutex.acquire()
                  if l not in self.visited_urls:
                     self.queue.put({'url':l, 'key':key, 'constraint': new_constraint})
                     self.visited_urls.add(l)
                  self.mutex.release()

         except HTTPError:
            self.logger.info('HTTPError exception on url: %s', url)

         self.queue.task_done()

         item = self.queue.get()

      self.queue.task_done() # task_done on None

fetcher.py

import urllib2
import logging

def fetch(uri):
   fetch.logger.info('Fetching: %s', uri)
   #logger = logging.getLogger('data_big_bang.focused_web_crawler')
   print uri

   h = urllib2.urlopen(uri)
   if h.headers.type == 'text/html':
      data = h.read()
   else:
      data = None

   return data

fetch.logger = logging.getLogger('data_big_bang.focused_web_crawler')

evaluator.py

import lxml.html
import urlparse

def get_all_links(page, base = ''):
   doc = lxml.html.fromstring(page)
   links = map(lambda x: urlparse.urljoin(base, x.attrib['href']), filter(lambda x: 'href' in x.attrib, doc.xpath('//a')))

   return links

def get_all_feeds(page, base = ''):
   doc = lxml.html.fromstring(page)

   feeds = map(lambda x: {'href':urlparse.urljoin(base, x.attrib['href']),'type':x.attrib['type']}, filter(lambda x: 'type' in x.attrib and x.attrib['type'] in ['application/atom+xml', 'application/rss+xml'], doc.xpath('//link')))

   return feeds

constraint.py

import urlparse
from parse_domain import parse_domain

class Constraint:
   DEPTH = 1
   def __init__(self):
      self.depth = 0

   def inherit(self, base_url, url):
      base_up = urlparse.urlparse(base_url)
      up = urlparse.urlparse(url)

      base_domain = parse_domain(base_url, 2)
      domain = parse_domain(url, 2)

      if base_domain != domain:
         return None

      if self.depth >= Constraint.DEPTH: # only crawl two levels
         return None
      else:
         new_constraint = Constraint()
         new_constraint.depth = self.depth + 1

         return new_constraint

collector.py

import urlparse
import re

twitter = re.compile('^http://twitter.com/(#!/)?(?P[a-zA-Z0-9_]{1,15})

) def collect(urls): collection = {'twitter':{}} for url in urls : up = urlparse.urlparse(url) hostname = up.hostname if hostname == None: continue if hostname == 'www.facebook.com': pass elif hostname == 'twitter.com': m = twitter.match(url) if m: gs = m.groupdict() if 'account' in gs: if gs['account'] != 'share': # this is not an account, although http://twitter.com/#!/share says that this account is suspended. collection['twitter'][gs['account']] = url elif hostname == 'www.linkedin.com': pass elif hostname == 'plus.google.com': pass elif hostname == 'www.slideshare.net': pass elif hostname == 'www.youtube.com': pass elif hostname == 'www.flickr.com': pass elif hostname[-9:] == '.xing.com': pass else: continue return collection

Further Work

This process can be integrated with a variety of CRM and business intelligence processes like Salesforce, Microsoft Dynamics, and SAP. These applications provide APIs to retrieve company URLs which you can crawl with our script.

The discovery process is just the first step in studying your prospective customers and generating leads. Once you have stored the sources of company information it is possible to apply machine learning tools to search for more opportunities.

See Also

  1. Integrating Google Analytics into your Company Loop with a Microsoft Excel Add-on

Resources

  1. Sales process
  2. Sales process engineering
  3. Microsoft Dynamics API
  4. Salesforce API
  5. SAP API
  6. SugarCRM Developer Zone
原文地址:https://www.cnblogs.com/lexus/p/2486117.html