python-multiprocessing

问题 I am new dev in python. My code is code below: import warnings import requests import multiprocessing from colorama import init init(autoreset=True) from requests.packages.urllib3.exceptions import InsecureRequestWarning warnings.simplefilter("ignore", UserWarning) warnings.simplefilter('ignore', InsecureRequestWarning) from bs4 import BeautifulSoup as BS headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari

问题 My original issue is that I am trying to do the following: def submit_decoder_process(decoder, input_line): decoder.process_line(input_line) return decoder self.pool = Pool(processes=num_of_processes) self.pool.apply_async(submit_decoder_process, [decoder, input_line]).get() decoder is a bit involved to describe here, but the important thing is that decoder is an object that is initialized with PyParsing expression that calls setParseAction(). This fails pickle that multiprocessing uses and

问题 So I have a system with a producer and a consumer are connected by a queue of unlimited size, but if the consumer repeatedly calls get until the Empty exception is thrown it does not clear the queue. I believe that this is because the thread in the queue on the consumer side which serialises the objects into the socket gets blocked once the socket buffer is full, and so it then waits until the buffer has space, however, it is possible for the consumer to call get "too fast" and so it thinks

问题 I am struggling to understand the difference between run() and start() . According to the documentation, run() method invokes the callable object passed to the object's constructor, while start() method starts the process and can be called only once. I tried an example below: def get_process_id(process_name): print process_name, os.getpid() p1 = multiprocessing.Process(target=get_process_id, args=('process_1',)) p2 = multiprocessing.Process(target=get_process_id, args=('process_2',)) p1.run()

问题 I am trying to create an architecture that will have a main parent process & it can create new child processes. The main parent process will always be on loop to check if there is any child process available. I have used ThreadedConnectionPool of psycopg2.pool module in order to have a common database connection for all child processes created. That means the program will be connecting once to the database and execute all the SQL queries for each of the child processes. So there is no need to

问题 I'm trying to update a shared object (a dict ) using the following code. But it does not work. It gives me the input dict as an output. Edit : Exxentially, What I'm trying to achieve here is to append items in the data (a list) to the dict's list. Data items give indices in the dict. Expected output : {'2': [2], '1': [1, 4, 6], '3': [3, 5]} Note: Approach 2 raise error TypeError: 'int' object is not iterable Approach 1 from multiprocessing import * def mapTo(d,tree): for idx, item in

问题 I'm trying to update a shared object (a dict ) using the following code. But it does not work. It gives me the input dict as an output. Edit : Exxentially, What I'm trying to achieve here is to append items in the data (a list) to the dict's list. Data items give indices in the dict. Expected output : {'2': [2], '1': [1, 4, 6], '3': [3, 5]} Note: Approach 2 raise error TypeError: 'int' object is not iterable Approach 1 from multiprocessing import * def mapTo(d,tree): for idx, item in

问题 I'm trying to update a shared object (a dict ) using the following code. But it does not work. It gives me the input dict as an output. Edit : Exxentially, What I'm trying to achieve here is to append items in the data (a list) to the dict's list. Data items give indices in the dict. Expected output : {'2': [2], '1': [1, 4, 6], '3': [3, 5]} Note: Approach 2 raise error TypeError: 'int' object is not iterable Approach 1 from multiprocessing import * def mapTo(d,tree): for idx, item in

问题 I want to search for pre-defined list of keywords in a given article and increment the score by 1 if keyword is found in article. I want to use multiprocessing since pre-defined list of keyword is very large - 10k keywords and number of article is 100k. I came across this question but it does not address my question. I tried this implementation but getting None as result. keywords = ["threading", "package", "parallelize"] def search_worker(keyword): score = 0 article = """ The multiprocessing

问题 I want to search for pre-defined list of keywords in a given article and increment the score by 1 if keyword is found in article. I want to use multiprocessing since pre-defined list of keyword is very large - 10k keywords and number of article is 100k. I came across this question but it does not address my question. I tried this implementation but getting None as result. keywords = ["threading", "package", "parallelize"] def search_worker(keyword): score = 0 article = """ The multiprocessing