| 12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667 | """Recursive webcrawler example.For asynchronous DNS lookups install the `dnspython` package:    $ pip install dnspythonRequires the `pybloom` module for the bloom filter which is usedto ensure a lower chance of recrawling an URL previously seen.Since the bloom filter is not shared, but only passed as an argumentto each subtask, it would be much better to have this as a centralizedservice.  Redis sets could also be a practical solution.A BloomFilter with a capacity of 100_000 members and an error rateof 0.001 is 2.8MB pickled, but if compressed with zlib it only takesup 2.9kB(!).We don't have to do compression manually, just set the tasks compressionto "zlib", and the serializer to "pickle"."""import reimport timeimport urlparsefrom celery import task, groupfrom eventlet import Timeoutfrom eventlet.green import urllib2from pybloom import BloomFilter# http://daringfireball.net/2009/11/liberal_regex_for_matching_urlsurl_regex = re.compile(    r'\b(([\w-]+://?|www[.])[^\s()<>]+(?:\([\w\d]+\)|([^[:punct:]\s]|/)))')def domain(url):    """Returns the domain part of an URL."""    return urlparse.urlsplit(url)[1].split(':')[0]@task(ignore_result=True, serializer='pickle', compression='zlib')def crawl(url, seen=None):    print('crawling: {0}'.format(url))    if not seen:        seen = BloomFilter(capacity=50000, error_rate=0.0001)    with Timeout(5, False):        try:            data = urllib2.urlopen(url).read()        except (urllib2.HTTPError, IOError):            return    location = domain(url)    wanted_urls = []    for url_match in url_regex.finditer(data):        url = url_match.group(0)        # To not destroy the internet, we only fetch URLs on the same domain.        if url not in seen and location in domain(url):            wanted_urls.append(url)            seen.add(url)    subtasks = group(crawl.s(url, seen) for url in wanted_urls)    subtasks.apply_async()
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