I need to do some three-step web scraping in Python. I have a couple base pages that I scrape initially, and I need to get a few select links off those pages and retrieve the pages they point to, and repeat that one more time. The trick is I would like to do this all asynchronously, so that every request is fired off as soon as possible, and the whole application isn't blocked on a single request. How would I do this?
Up until this point, I've been doing one-step scraping with eventlet, like this:
urls = ['http://example.com', '...']
def scrape_page(url):
"""Gets the data from the web page."""
body = eventlet.green.urllib2.urlopen(url).read()
# Do something with body
return data
pool = eventlet.GreenPool()
for data in pool.imap(screen_scrape, urls):
# Handle the data...
However, if I extend this technique and include a nested GreenPool.imap loop, it blocks until all the requests in that group are done, meaning the application can't start more requests as needed.
I know I could do this with Twisted or another asynchronous server, but I don't need such a huge library and I would rather use something lightweight. I'm open to suggestions, though.
Here is an idea... but forgive me since I don't know eventlet. I can only provide a rough concept.
Consider your "step 1" pool the producers. Create a queue and have your step 1 workers place any new urls they find into the queue.
Create another pool of workers. Have these workers pull from the queue for urls and process them. If during their process they discover another url, put that into the queue. They will keep feeding themselves with subsequent work.
Technically this approach would make it easily recursive beyond 1,2,3+ steps. As long as they find new urls and put them in the queue, the work keeps happening.
Better yet, start out with the original urls in the queue, and just create a single pool that puts new urls to that same queue. Only one pool needed.
Post note
Funny enough, after I posted this answer and went to look for what the eventlet 'queue' equivalent was, I immediately found an example showing exactly what I just described:
http://eventlet.net/doc/examples.html#producer-consumer-web-crawler
In that example there is a producer and fetch method. The producer starts pulling urls from the queue and spawning threads to fetch. fetch then puts any new urls back into the queue and they keep feeding each other.
Related
I am currently working on a test system that uses selenium grid for WhatsApp automation.
WhatsApp requires a QR code scan to log in, but once the code has been scanned, the session persists as long as the cookies remain saved in the browser's user data directory.
I would like to run a series of tests concurrently while making sure that every session is only used by one thread at any given time.
I would also like to be able to add additional tests to the queue while tests are being run.
So far I have considered using the ThreadPoolExecutor context manager in order to limit the maximum available workers to the maximum number of sessions. Something like this:
import queue
from concurrent.futures import ThreadPoolExecutor
def make_queue(questions):
q = queue.Queue()
for question in questions:
q.put(question)
return q
def test_conversation(q):
item = q.get()
# Whatsapp test happens here
q.task_done()
def run_tests(questions):
q = make_queue(questions)
with ThreadPoolExecutor(max_workers=number_of_sessions) as executor:
while not q.empty()
test_results = executor.submit(test_conversation, q)
for f in concurrent.futures.as_completed(test_results):
# save results somewhere
It does not include some way to make sure that every thread gets its own session though and as far as I know I can only send one parameter to the function that the executor calls.
I could make some complicated checkout system that works like borrowing books from a library so that every session can only be checked out once at any given time, but I'm not confident in making something that is thread safe and works in all cases. Even the ones I can't think of until they happen.
I am also not sure how I would keep the thing going while adding items to the queue without it locking up my entire application. Would I have to run run_tests() in its own thread?
Is there an established way to do this? Any help would be much appreciated.
I'm currently running a python script against multiple web server. The general task is to find out broken (external) links within a cms. Script runs pretty well so far but in reason I test around 50 internal projects and each with several hundreds sub pages. This ends in several thousands external links i have to check.
For that reason I added multi-threading - improves performance as it was my wish. But here comes the problem. If there is a page to check which contains a list of links to the same server (bundle of known issues or tasks to do) it will slow down the destination system. I neither would like to slow my own server nor server that are not mine.
Currently I running up to 20 threads and than waiting 0.5s until a "thread position" is ready to use. To check if a URL is broken I deal with urlopen(request) coming from urllib2 and log every time it throws an HTTPError. Back to the list of multiple URLs to the same server... my script will "flood" the web server with - cause of multi-threading - up to 20 simultaneous requests.
Just that you have an idea in which dimensions this script runs/URLs have to check: Using only 20 threads "slows" down the current script for only 4 projects to 45min running time. And this is only checking .. Next step will be to check broken URLs for . Using the current script shows us some peaks with 1000ms response time within server monitoring.
Does everyone has an idea how to improve this script in general? Or is there a much better way to check this big amount of URLs? Maybe a counter that pause the thread if there are 10 requests to a single destination?
Thanks for all suggestions
When I was running a crawler, I had all of my URLs prioritized by domain name. Basically, my queue of URLs to crawl was really a queue of domain names, and each domain name had a list of URLs.
When it came time to get the next URL to crawl, a thread would pull a domain name from the queue and crawl the next URL on that domain's list. When done processing that URL, the thread would put the domain on a delay list and remove from the delay list any domains whose delay had expired.
The delay list was a priority queue ordered by expiration time. That way I could give different delay times to each domain. That allowed me to support the crawl-delay extension to robots.txt. Some domains were ok with me hitting their server once per second. Others wanted a one minute delay between requests.
With this setup, I never hit the same domain with multiple threads concurrently, and I never hit them more often than they requested. My default delay was something like 5 seconds. That seems like a lot, but my crawler was looking at millions of domains, so it was never wanting for stuff to crawl. You could probably reduce your default delay.
If you don't want to queue your URLs by domain name, what you can do is maintain a list (perhaps a hash table or the python equivalent) that holds the domain names that are currently being crawled. When you dequeue a URL, you check the domain against the hash table, and put the URL back into the queue if the domain is currently in use. Something like:
goodUrl = false
while (!goodUrl)
url = urlqueue.Dequeue();
lock domainsInUse
if domainsInUse.Contains(url.domainName)
urlqueue.Add(url) // put it back at the end of the queue
else
domainsInUse.Add(url.domainName)
goodUrl = true
That will work, although it's going to be a big CPU pig if the queue contains a lot of URLs from the same domain. For example if you have 20 threads and only 5 different domains represented in the queue, then on average 15 of your threads will be continually spinning, looking for a URL to crawl.
If you only want status make a HEAD request instead of urlopen. This will considerably reduce the load on the server. And of course limit the number of simultaneous requests.
import httplib
from urlparse import urlparse
def is_up(url):
_, host, path, _, _, _ = urlparse(url)
conn = httplib.HTTPConnection(host)
conn.request('HEAD', path)
return conn.getresponse().status < 400
I'm wanting to achieve multithreading in python where the threaded function does some actions and adds a URL to a list of URLs (links) and a listener watches the links list from the calling script for new elements to iterate over. Confused? Me too, I'm not even sure how to go about explaining this, so let me try to demonstrate with pseudo-code:
from multiprocessing import Pool
def worker(links):
#do lots of things with urllib2 including finding elements with BeautifulSoup
#extracting text from those elements and using it to compile the unique URL
#finally, append a url that was gathered in the `lots of things` section to a list
links.append( `http://myUniqueURL.com` ) #this will be unique for each time `worker` is called
links = []
for i in MyBigListOfJunk:
Pool().apply(worker, links)
for link in links:
#do a bunch of stuff with this link including using it to retrieve the html source with urllib2
Now, rather than waiting for all the worker threads to finish and iterate over links all at once, is there a way for me to iterate over the URLs as they are getting appended to the links list? Basically, the worker iteration to generate the links list HAS to be separate from the iteration of links itself; however, rather than running each sequentially I was hoping I could run them somewhat concurrently and save some time... currently I must call worker upwards of 30-40 times within a loop and the entire script takes roughly 20 minutes to finish executing...
Any thoughts would be very welcome, thank you.
You should use Queue class for this. It is a thread-safe array. It's 'get' function removes item from Queue, and, what's important, blocks when there is no items and waits until other processes add them.
If you use multiprocessing than you should use Queue from this module, not the Queue module.
Next time you ask questions on processes, provide exact Python version you want it for. This is for 2.6
I am new to python, and even newer to twisted. I am trying to use twisted to download a few hundred thousand files but am having trouble trying to add an errback. I'd like to print the bad url if the download fails. I've misspelled one of my urls on purpose in order to throw an error. However, the code I have just hangs and python doesn't finish (it finishes fine if I remove the errback call).
Also, how to I process each file individually? From my understanding, "finish" is called when everything completes. I'd like to gzip each file when it's downloaded so that it's removed from memory.
Here's what I have:
urls = [
'http://www.python.org',
'http://stackfsdfsdfdsoverflow.com', # misspelled on purpose to generate an error
'http://www.twistedmatrix.com',
'http://www.google.com',
'http://launchpad.net',
'http://github.com',
'http://bitbucket.org',
]
def finish(results):
for result in results:
print 'GOT PAGE', len(result), 'bytes'
reactor.stop()
def print_badurls(err):
print err # how do I just print the bad url????????
waiting = [client.getPage(url) for url in urls]
defer.gatherResults(waiting).addCallback(finish).addErrback(print_badurls)
reactor.run()
Welcome to Python and Twisted!
There are a few problems with the code you pasted. I'll go through them one at a time.
First, if you do want to download thousands of urls, and will have thousands of items in the urls list, then this line:
waiting = [client.getPage(url) for url in urls]
is going to cause problems. Do you want to try to download every page in the list simultaneously? By default, in general, things you do in Twisted happen concurrently, so this loop starts downloading every URL in the urls list at once. Most likely, this isn't going to work. Your DNS server is going to drop some of the domain lookup requests, your DNS client is going to drop some of the domain lookup responses. The TCP connection attempts to whatever addresses you do get back will compete for whatever network resources are still available, and some of them will time out. The rest of the connections will all trickle along, sharing available bandwidth between dozens or perhaps hundreds of different downloads.
Instead, you probably want to limit the degree of concurrency to perhaps 10 or 20 downloads at a time. I wrote about one approach to this on my blog a while back.
Second, gatherResults returns a Deferred that fires as soon as any one Deferred passed to it fires with a failure. So as soon as any one client.getPage(url) fails - perhaps because of one of the problems I mentioned above, or perhaps because the domain has expired, or the web server happens to be down, or just because of an unfortunate transient network condition, the Deferred returned by gatherResults will fail. finish will be skipped and print_badurls will be called with the error describing the single failed getPage call.
To handle failures from individual HTTP requests, add the callbacks and errbacks to the Deferreds returned from the getPage calls. After adding those callbacks and errbacks, you can use defer.gatherResults to wait for all of the downloads and processing of the download results to be complete.
Third, you might want to consider using a higher-level tool for this - scrapy is a web crawling framework (based on Twisted) that provides lots of cool useful helpers for this kind of application.
I'm trying to write a 'market data engine' of sorts.
So far I have a queue of threads, each thread will urllib to google finance and re the stock details out the page. Each thread will poll the page ever few seconds.
From here, how can I persist the data in a way another class can just poll it, without the problem of 2 processes accessing the same resource at the same time? For example, if I get my threads to write to a dict that's constantly being updated, will I have trouble reading that same hash from another function?
You are correct that using a standard dict is not thread-safe (see here) and may cause you problems.
A very nice way to handle this is to use the Queue class in the queue module in the standard library. It is thread-safe. Have the worker threads send updates to the main thread via the queue and have the main thread alone update the dictionary.
You could also have the threads update a database, but that may or may not be overkill for what you're doing.
You might also want to take a look at something like eventlet. In fact, they have a web crawler example on their front page.