我正在努力理解Python中的线程。我看过文档和示例,但坦率地说,许多示例过于复杂,我很难理解它们。
如何清楚地显示为多线程划分的任务?
我正在努力理解Python中的线程。我看过文档和示例,但坦率地说,许多示例过于复杂,我很难理解它们。
如何清楚地显示为多线程划分的任务?
当前回答
我发现这非常有用:创建与内核一样多的线程,并让它们执行(大量)任务(在本例中,调用shell程序):
import Queue
import threading
import multiprocessing
import subprocess
q = Queue.Queue()
for i in range(30): # Put 30 tasks in the queue
q.put(i)
def worker():
while True:
item = q.get()
# Execute a task: call a shell program and wait until it completes
subprocess.call("echo " + str(item), shell=True)
q.task_done()
cpus = multiprocessing.cpu_count() # Detect number of cores
print("Creating %d threads" % cpus)
for i in range(cpus):
t = threading.Thread(target=worker)
t.daemon = True
t.start()
q.join() # Block until all tasks are done
其他回答
以前的解决方案都没有在我的GNU/Linux服务器上使用多个内核(我没有管理员权限)。他们只是在一个核心上跑步。
我使用较低级别的os.fork接口来派生多个进程。这是对我有用的代码:
from os import fork
values = ['different', 'values', 'for', 'threads']
for i in range(len(values)):
p = fork()
if p == 0:
my_function(values[i])
break
下面的代码可以运行10个线程同时打印0到99之间的数字:
from threading import Thread
def test():
for i in range(0, 100):
print(i)
thread_list = []
for _ in range(0, 10):
thread = Thread(target=test)
thread_list.append(thread)
for thread in thread_list:
thread.start()
for thread in thread_list:
thread.join()
下面的代码是上述代码循环版本的简写,运行10个线程,同时打印0到99之间的数字:
from threading import Thread
def test():
[print(i) for i in range(0, 100)]
thread_list = [Thread(target=test) for _ in range(0, 10)]
[thread.start() for thread in thread_list]
[thread.join() for thread in thread_list]
结果如下:
...
99
83
97
84
98
99
85
86
87
88
...
我发现这非常有用:创建与内核一样多的线程,并让它们执行(大量)任务(在本例中,调用shell程序):
import Queue
import threading
import multiprocessing
import subprocess
q = Queue.Queue()
for i in range(30): # Put 30 tasks in the queue
q.put(i)
def worker():
while True:
item = q.get()
# Execute a task: call a shell program and wait until it completes
subprocess.call("echo " + str(item), shell=True)
q.task_done()
cpus = multiprocessing.cpu_count() # Detect number of cores
print("Creating %d threads" % cpus)
for i in range(cpus):
t = threading.Thread(target=worker)
t.daemon = True
t.start()
q.join() # Block until all tasks are done
import threading
import requests
def send():
r = requests.get('https://www.stackoverlow.com')
thread = []
t = threading.Thread(target=send())
thread.append(t)
t.start()
使用线程/多处理的最简单方法是使用更多高级库,如autothread。
import autothread
from time import sleep as heavyworkload
@autothread.multithreaded() # <-- This is all you need to add
def example(x: int, y: int):
heavyworkload(1)
return x*y
现在,您可以为函数提供int列表。Autothread将为您处理所有事务,并只提供并行计算的结果。
result = example([1, 2, 3, 4, 5], 10)