I’m half-tempted to write my own, but I don’t really have enough time right now. I’ve seen the Wikipedia list of open source crawlers but I’d prefer something written in Python. I realize that I could probably just use one of the tools on the Wikipedia page and wrap it in Python. I might end up doing that – if anyone has any advice about any of those tools, I’m open to hearing about them. I’ve used Heritrix via its web interface and I found it to be quite cumbersome. I definitely won’t be using a browser API for my upcoming project.
Thanks in advance. Also, this is my first SO question!
Answers:
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Method 1
- Mechanize is my favorite; great high-level browsing capabilities (super-simple form filling and submission).
- Twill is a simple scripting language built on top of Mechanize
- BeautifulSoup + urllib2 also works quite nicely.
- Scrapy looks like an extremely promising project; it’s new.
Method 2
Use Scrapy.
It is a twisted-based web crawler framework. Still under heavy development but it works already. Has many goodies:
- Built-in support for parsing HTML, XML, CSV, and Javascript
- A media pipeline for scraping items with images (or any other media) and download the image files as well
- Support for extending Scrapy by plugging your own functionality using middlewares, extensions, and pipelines
- Wide range of built-in middlewares and extensions for handling of compression, cache, cookies, authentication, user-agent spoofing, robots.txt handling, statistics, crawl depth restriction, etc
- Interactive scraping shell console, very useful for developing and debugging
- Web management console for monitoring and controlling your bot
- Telnet console for low-level access to the Scrapy process
Example code to extract information about all torrent files added today in the mininova torrent site, by using a XPath selector on the HTML returned:
class Torrent(ScrapedItem):
pass
class MininovaSpider(CrawlSpider):
domain_name = 'mininova.org'
start_urls = ['http://www.mininova.org/today']
rules = [Rule(RegexLinkExtractor(allow=['/tor/d+']), 'parse_torrent')]
def parse_torrent(self, response):
x = HtmlXPathSelector(response)
torrent = Torrent()
torrent.url = response.url
torrent.name = x.x("//h1/text()").extract()
torrent.description = x.x("//div[@id='description']").extract()
torrent.size = x.x("//div[@id='info-left']/p[2]/text()[2]").extract()
return [torrent]
Method 3
Check the HarvestMan, a multi-threaded web-crawler written in Python, also give a look to the spider.py module.
And here you can find code samples to build a simple web-crawler.
Method 4
I’ve used Ruya and found it pretty good.
Method 5
I hacked the above script to include a login page as I needed it to access a drupal site. Not pretty but may help someone out there.
#!/usr/bin/python
import httplib2
import urllib
import urllib2
from cookielib import CookieJar
import sys
import re
from HTMLParser import HTMLParser
class miniHTMLParser( HTMLParser ):
viewedQueue = []
instQueue = []
headers = {}
opener = ""
def get_next_link( self ):
if self.instQueue == []:
return ''
else:
return self.instQueue.pop(0)
def gethtmlfile( self, site, page ):
try:
url = 'http://'+site+''+page
response = self.opener.open(url)
return response.read()
except Exception, err:
print " Error retrieving: "+page
sys.stderr.write('ERROR: %sn' % str(err))
return ""
return resppage
def loginSite( self, site_url ):
try:
cj = CookieJar()
self.opener = urllib2.build_opener(urllib2.HTTPCookieProcessor(cj))
url = 'http://'+site_url
params = {'name': 'customer_admin', 'pass': 'customer_admin123', 'opt': 'Log in', 'form_build_id': 'form-3560fb42948a06b01d063de48aa216ab', 'form_id':'user_login_block'}
user_agent = 'Mozilla/4.0 (compatible; MSIE 5.5; Windows NT)'
self.headers = { 'User-Agent' : user_agent }
data = urllib.urlencode(params)
response = self.opener.open(url, data)
print "Logged in"
return response.read()
except Exception, err:
print " Error logging in"
sys.stderr.write('ERROR: %sn' % str(err))
return 1
def handle_starttag( self, tag, attrs ):
if tag == 'a':
newstr = str(attrs[0][1])
print newstr
if re.search('http', newstr) == None:
if re.search('mailto', newstr) == None:
if re.search('#', newstr) == None:
if (newstr in self.viewedQueue) == False:
print " adding", newstr
self.instQueue.append( newstr )
self.viewedQueue.append( newstr )
else:
print " ignoring", newstr
else:
print " ignoring", newstr
else:
print " ignoring", newstr
def main():
if len(sys.argv)!=3:
print "usage is ./minispider.py site link"
sys.exit(2)
mySpider = miniHTMLParser()
site = sys.argv[1]
link = sys.argv[2]
url_login_link = site+"/node?destination=node"
print "nLogging in", url_login_link
x = mySpider.loginSite( url_login_link )
while link != '':
print "nChecking link ", link
# Get the file from the site and link
retfile = mySpider.gethtmlfile( site, link )
# Feed the file into the HTML parser
mySpider.feed(retfile)
# Search the retfile here
# Get the next link in level traversal order
link = mySpider.get_next_link()
mySpider.close()
print "ndonen"
if __name__ == "__main__":
main()
Method 6
Trust me nothing is better than curl.. . the following code can crawl 10,000 urls in parallel in less than 300 secs on Amazon EC2
CAUTION: Don’t hit the same domain at such a high speed.. .
#! /usr/bin/env python
# -*- coding: iso-8859-1 -*-
# vi:ts=4:et
# $Id: retriever-multi.py,v 1.29 2005/07/28 11:04:13 mfx Exp $
#
# Usage: python retriever-multi.py <file with URLs to fetch> [<# of
# concurrent connections>]
#
import sys
import pycurl
# We should ignore SIGPIPE when using pycurl.NOSIGNAL - see
# the libcurl tutorial for more info.
try:
import signal
from signal import SIGPIPE, SIG_IGN
signal.signal(signal.SIGPIPE, signal.SIG_IGN)
except ImportError:
pass
# Get args
num_conn = 10
try:
if sys.argv[1] == "-":
urls = sys.stdin.readlines()
else:
urls = open(sys.argv[1]).readlines()
if len(sys.argv) >= 3:
num_conn = int(sys.argv[2])
except:
print "Usage: %s <file with URLs to fetch> [<# of concurrent connections>]" % sys.argv[0]
raise SystemExit
# Make a queue with (url, filename) tuples
queue = []
for url in urls:
url = url.strip()
if not url or url[0] == "#":
continue
filename = "doc_%03d.dat" % (len(queue) + 1)
queue.append((url, filename))
# Check args
assert queue, "no URLs given"
num_urls = len(queue)
num_conn = min(num_conn, num_urls)
assert 1 <= num_conn <= 10000, "invalid number of concurrent connections"
print "PycURL %s (compiled against 0x%x)" % (pycurl.version, pycurl.COMPILE_LIBCURL_VERSION_NUM)
print "----- Getting", num_urls, "URLs using", num_conn, "connections -----"
# Pre-allocate a list of curl objects
m = pycurl.CurlMulti()
m.handles = []
for i in range(num_conn):
c = pycurl.Curl()
c.fp = None
c.setopt(pycurl.FOLLOWLOCATION, 1)
c.setopt(pycurl.MAXREDIRS, 5)
c.setopt(pycurl.CONNECTTIMEOUT, 30)
c.setopt(pycurl.TIMEOUT, 300)
c.setopt(pycurl.NOSIGNAL, 1)
m.handles.append(c)
# Main loop
freelist = m.handles[:]
num_processed = 0
while num_processed < num_urls:
# If there is an url to process and a free curl object, add to multi stack
while queue and freelist:
url, filename = queue.pop(0)
c = freelist.pop()
c.fp = open(filename, "wb")
c.setopt(pycurl.URL, url)
c.setopt(pycurl.WRITEDATA, c.fp)
m.add_handle(c)
# store some info
c.filename = filename
c.url = url
# Run the internal curl state machine for the multi stack
while 1:
ret, num_handles = m.perform()
if ret != pycurl.E_CALL_MULTI_PERFORM:
break
# Check for curl objects which have terminated, and add them to the freelist
while 1:
num_q, ok_list, err_list = m.info_read()
for c in ok_list:
c.fp.close()
c.fp = None
m.remove_handle(c)
print "Success:", c.filename, c.url, c.getinfo(pycurl.EFFECTIVE_URL)
freelist.append(c)
for c, errno, errmsg in err_list:
c.fp.close()
c.fp = None
m.remove_handle(c)
print "Failed: ", c.filename, c.url, errno, errmsg
freelist.append(c)
num_processed = num_processed + len(ok_list) + len(err_list)
if num_q == 0:
break
# Currently no more I/O is pending, could do something in the meantime
# (display a progress bar, etc.).
# We just call select() to sleep until some more data is available.
m.select(1.0)
# Cleanup
for c in m.handles:
if c.fp is not None:
c.fp.close()
c.fp = None
c.close()
m.close()
Method 7
Another simple spider
Uses BeautifulSoup and urllib2. Nothing too sophisticated, just reads all a href’s builds a list and goes though it.
Method 8
All methods was sourced from stackoverflow.com or stackexchange.com, is licensed under cc by-sa 2.5, cc by-sa 3.0 and cc by-sa 4.0