![]() Parse_us = ĭata = p.map(get_links, )ĭata = Now, using multiprocessing, let's put it all together: def main(): At the very least, you might want to log the error either in a plain text file or even using something like Python's logging standard library. In general, it's a bad idea to just silently move along on errors. The final exception could arguably be excluded and we could further handle the explicit errors. Print('Likely got None for links, so we are throwing this') Print('We probably did not find any useful links, returning empty list') Print('Got a TypeError, probably got a None that we tried to iterate over') Thus, we have a few exceptions to handle for: def get_links(url): If we are able to connect and read the source code, we might not find any links at all. If they do have a website, maybe they don't allow bot connections. If it does have a server, maybe there's nothing on it being returned. In this function, we're grabbing the source code, then parsing it with Beautiful Soup. Soup = bs.BeautifulSoup(resp.text, 'lxml') Now, we need to find those links! def get_links(url): A browser knows this is really a link to, but our program wont without us telling it: def handle_local_links(url,link): Many times, websites will have local links, basically where the link doesn't actually start with http or https, and instead it starts with a slash, like /login/. If one doesn't no matter, since we're going to start with parsing a handful of these. com domain names have at least something. To figure out where to begin, we're going to write a function that generates a random combination of three characters, and then we'll slap an " and a ".com" and we've got probably a decent starting place, since most 3 letter. Once with a starting point, a spider simply will continue crawling around, and then networking out to other websites via links. Now, with a spider, we need to figure out at least where to begin. Starting = ''.join(random.SystemRandom().choice(string.ascii_lowercase) for _ in range(3)) We'll be using random and string to generate random strings, and requests to actually make the request and grab the source code. If you're not familiar with Beautiful Soup, you can check out the Beautiful Soup miniseries. Next, we're going to make use of the Beautiful Soup library for parsing the HTML. We will obviously be using multiprocessing, and we're going to use the Pool so we can access the returned values from a process. To begin, let's make some imports: from multiprocessing import Pool If you're just now joining us, you may want to start with the multiprocessing tutorial, as this is meant to simply be an example of what we learned. The idea here will be to quickly access and process many websites at the same time. Here, we're going to be covering the beginnings to building a spider, using the multiprocessing library. In this part, we're going to talk more about the built-in library: multiprocessing. ![]() Welcome to part 12 of the intermediate Python programming tutorial series. ![]()
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