How to return multiple results in Python threading?
Returning values from threads is not possible and, as such, in this example we pass in a globally accessible (to all threads) “results” array with the index of the array in which to store the result once fetched. The crawl () function will look like: logging.info(“Requested…” + url) logging.error(‘Error with URL check!’)
Are there any Python projects that combine requests with multithreading?
If you are concerned about the use of blocking IO, there are lots of projects out there that combine Requests with one of Python’s asynchronicity frameworks. Two excellent examples are grequests and requests-futures. Using this method gives me a noticable performance increase with 10 URLs: 0.877s vs 3.852s with your original method.
What do you need to know about threading in Python?
#need the index and the url in each queue item. The threaded “crawl” function will be different since it now relies on the queue. The threads are set up to close and return when the queue is empty of tasks. # Threaded function for queue processing. logging.info(“Requested…” + work[1]) logging.error(‘Error with URL check!’)
How are queues and threads used in Python?
Another of Pythons built-in libraries for threading, Queue, can be used to get around obstacle. A queue is essentially used to store a number of “tasks to be done”. Threads can take tasks from the queue when they are available, do the work, and then go back for more.
How to multi thread an operation within a loop in Python-stack overflow?
Next, the way to process 5 or 10 or 100 items at once is to create a pool of 5 or 10 or 100 workers, and put the items into a queue that the workers service. Fortunately, the stdlib multiprocessing and concurrent.futures libraries both wraps up most of the details for you.
Why do you not use multithreading in Python?
First, in Python, if your code is CPU-bound, multithreading won’t help, because only one thread can hold the Global Interpreter Lock, and therefore run Python code, at a time. So, you need to use processes, not threads.
How to transmit information between threads in Python?
Jake’s answer is good, but if you don’t want to use a threadpool (you don’t know how many threads you’ll need, but create them as needed) then a good way to transmit information between threads is the built-in Queue.Queue class, as it offers thread safety. I created the following decorator to make it act in a similar fashion to the threadpool: