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Multithreaded concurrent fetching

If a single thread is too slow, you will need multithreading. Here is a simple thread pool template. This program simply prints 1-10, but you can see that it is concurrent.

Although the multithreading of Python is very creepy, it can improve the efficiency to a certain extent for the frequent network type of crawlers.

From threading import Threadfrom Queue import Queuefrom time import sleep# Q is the task queue # NUM is the total number of concurrent threads # JOBS is the number of tasks Q = Queue () NUM = 2JOBS = 1 task specific processing function, responsible for handling a single task def do_somthing_using (arguments): print arguments# this is the worker process Responsible for continuously fetching data from the queue and processing def working (): while True: arguments = q.get () do_somthing_using (arguments) sleep (1) q.task_done () # fork NUM thread waiting queue for i in range (NUM): t = Thread (target=working) t.setDaemon (True) t.start () # queue for i in range (JOBS) : q.put (I) # waiting for all JOBS to complete q.join () these are all the contents of the article "how to achieve multithreaded concurrent fetching by python" Thank you for reading! I believe we all have a certain understanding, hope to share the content to help you, if you want to learn more knowledge, welcome to follow the industry information channel!

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