Python 线程与进程
线程是操作系统能够进行运算调度的最小单位。它被包含在进程之中，是进程中的实际运作单位。一条线程指的是进程中一个单一顺序的控制流，一个进程中可以并发多个线程，每条线程并行执行不同的任务。
使用 threading 模块
方法一：
import threading
import time
def foo(n):
print('foo %s'%n)
time.sleep(1)
print('end foo')
def bar(n):
print('bar %s'%n)
time.sleep(2)
print('end bar')
t1 = threading.Thread(target=foo, args=(1,))
t2 = threading.Thread(target=bar, args=(2,))
t1.start()
t2.start()
print('........in the main..........')
运行结果：
foo 1 bar 2 ........in the main.......... end foo end bar
方法二：
import time, threading
class MyThread(threading.Thread):
def __init__(self, num):
threading.Thread.__init__(self)
self.num = num
def run(self): #定义线程要运行的函数
print("running on number:%s" % self.num)
time.sleep(3)
if __name__ == '__main__':
t1 = MyThread(1)
t2 = MyThread(2)
t1.start()
t2.start()
运行结果:
running on number:1 running on number:2
join 方法使得主线程等待子线程完成才继续
import threading
import time
begin = time.time()
def foo(n):
print('foo %s'%n)
time.sleep(1)
print('end foo')
def bar(n):
print('bar %s'%n)
time.sleep(2)
print('end bar')
t1 = threading.Thread(target=foo, args=(1,))
t2 = threading.Thread(target=bar, args=(2,))
t1.start()
t2.start()
t1.join()
t2.join()
print('........in the main..........')
运行结果:
foo 1 bar 2 end foo end bar ........in the main..........
在计算密集型任务中串行与多线程进行对比
import threading, time begin = time.time() def add(n): sum = 0 for i in range(n): sum += i print(sum) add(100000000) add(200000000) end = time.time() print(end-begin)
运行结果：
4999999950000000 19999999900000000 17.66856598854065import threading, time begin = time.time() def add(n): sum = 0 for i in range(n): sum += i print(sum) t1 = threading.Thread(target=add, args=(100000000,)) t1.start() t2 = threading.Thread(target=add, args=(200000000,)) t2.start() t1.join() t2.join() end = time.time() print(end-begin)
运行结果：
4999999950000000 19999999900000000 21.088160276412964 # 结果为串行运行比多线程运行更快
Cpython 中有 GIL (Global Interpreter Lock，全局解释器锁)，所以在同一时刻，只能有一个线程进入调度。如果任务是IO密集型的，可以使用多线程；如果任务是计算密集型的，最优方法是改成 C。
setDaemon()
调用该方法只要是主线程完成，不管子线程是否完成都要和主线程一起退出。
threading.currentThread()
返回当前的线程变量。
threading.active_count()
返回正在运行的线程数量。
import threading, time
from time import ctime,sleep
def music(func):
print(threading.current_thread())
for i in range(2):
print("Begin listening to %s. %s" %(func, ctime()))
sleep(2)
print("end listening %s" %ctime())
def movie(func):
print(threading.current_thread())
for i in range(2):
print("Begin watching at the %s %s" %{func, ctime()})
sleep(4)
print("end watching %s" %ctime())
threads = []
t1 = threading.Thread(target=music, args=('klvchen',))
threads.append(t1)
t2 = threading.Thread(target=movie, args=('lili',))
threads.append(t2)
if __name__ == '__main__':
for t in threads:
t.setDaemon(True)
t.start()
print(threading.current_thread())
print(threading.active_count())
print("all over %s" %ctime())
运行结果：
<Thread(Thread-1, started daemon 5856)> Begin listening to klvchen. Wed Jul 11 23:43:51 2018 <Thread(Thread-2, started daemon 9124)> <_MainThread(MainThread, started 9444)> 3 all over Wed Jul 11 23:43:51 2018
