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I'm writing a program that downloads data from a website (eve-central.com). It returns xml when I send a GET request with some parameters. The problem is that I need to make about 7080 of such requests because i can't specify the typeid parameter more than once.

def get_data_eve_central(typeids, system, hours, minq=1, thread_count=1): import xmltodict, urllib3 pool = urllib3.HTTPConnectionPool('api.eve-central.com') for typeid in typeids: r = pool.request('GET', '/api/quicklook', fields={'typeid': typeid, 'usesystem': system, 'sethours': hours, 'setminQ': minq}) answer = xmltodict.parse(r.data) 

It was really slow when I just connected to the website and made all the requests so I decided to make it use multiple threads at a time (I read that if the process involves a lot of waiting (I/O, HTTP requests), it can be speeded up a lot with multithreading). I rewrote it using multiple threads, but it somehow isn't any faster (a bit slower in fact). Here's the code rewritten using multithreading:

def get_data_eve_central(all_typeids, system, hours, minq=1, thread_count=1): if thread_count > len(all_typeids): raise NameError('TooManyThreads') def requester(typeids): pool = urllib3.HTTPConnectionPool('api.eve-central.com') for typeid in typeids: r = pool.request('GET', '/api/quicklook', fields={'typeid': typeid, 'usesystem': system, 'sethours': hours, 'setminQ': minq}) answer = xmltodict.parse(r.data)['evec_api']['quicklook'] answers.append(answer) def chunkify(items, quantity): chunk_len = len(items) // quantity rest_count = len(items) % quantity chunks = [] for i in range(quantity): chunk = items[:chunk_len] items = items[chunk_len:] if rest_count and items: chunk.append(items.pop(0)) rest_count -= 1 chunks.append(chunk) return chunks t = time.clock() threads = [] answers = [] for typeids in chunkify(all_typeids, thread_count): threads.append(threading.Thread(target=requester, args=[typeids])) threads[-1].start() threads[-1].join() print(time.clock()-t) return answers 

What I do is I divide all typeids into as many chunks as the quantity of threads i want to use and create a thread for each chunk to process it. The question is: what can slow it down? (I apologise for my bad english)

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Python has Global Interpreter Lock. It can be your problem. Actually Python cannot do it in a genuine parallel way. You may think about switching to other languages or staying with Python but use process-based parallelism to solve your task. Here is a nice presentation Inside the Python GIL

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5 Comments

I think so too, but i can't see, where my threads use the similar resource. They use answers list, yes, but i tried removing it and it was just as slow so I think it's not the problem.
Take a look at the nice presentation dabeaz.com/python/GIL.pdf "Inside the Python GIL". After that I believe you will find out exactly why GIL makes you problems.
I read the presentation (it's a great one by the way, thanks), but i still can't figure out what is the problem in my particular case. The operation that takes most of the time is waiting for the server to respond, but it's an I/O operation and it (as I understood from the presentation) should release the GIL while waiting, which it (judging by the time the program runs) doesn't do.
I use 'for' to give threads their tasks, I think it's a good idea to try using queues like it was recommended here
I rewrote my program using queues and it's really a lot faster. Thanks!

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