进程process:应用程序以一个整体的形式暴露给操作系统管理,里边包含对各种资源的调用,内存的分配,对各种资源管理的集合
线程thread:操作系统最小的调度单位,是一串指令的集合
进程 要操作cpu,必须先创建一个线程
进程与线程区别:线程共享,进程独立 线程共享内存空间,进程内存是独立的 同一个进程之间的线程可以直接通信,两个进程必须通过中间代理才能通信,创建新线程很简单,创建新进程需要对其父进程进行一次克隆 一个线程可以控制和操作统一进程里的其他线程,进程只能操作子进程
GIL:Global Interpreter Lock
直接调用import threading
import time
def run(n):
print("task:", n)
time.sleep(2)
t1 = threading.Thread(target=run, args=("t1",))
t2 = threading.Thread(target=run, args=("t2",))
t3 = threading.Thread(target=run, args=("t3",))
t1.start()
t2.start()
t3.start()
"""
task: t1
task: t2
task: t3
"""
继承式调用
import threading
import time
class MyThread(threading.Thread):
def __init__(self, n, sleep_time):
super(MyThread, self).__init__()
self.n = n
self.sleep_time = sleep_time
def run(self): # 需要运行的代码
print("task:", self.n)
time.sleep(self.sleep_time)
print("task done", self.n, threading.current_thread(), threading.active_count())
t1 = MyThread("t1", 2)
t2 = MyThread("t2", 3)
t3 = MyThread("t3", 4)
t1.start()
t2.start()
t3.start()
# 等待线程执行完毕继续主线程,阻塞
t1.join() # wait()
t2.join()
t3.join()
print("...main...", threading.current_thread(), threading.active_count()) # 主线程
"""
task: t1
task: t2
task: t3
task done t1 4
task done t2 3
task done t3 2
...main... 1
"""
多线程调用
# 主线程与子线程是并行的
import threading
import time
def run(n):
print("task:", n)
time.sleep(2)
print("task done", n)
start_time = time.time()
threads = [] # 保存线程列表
for i in range(5):
t = threading.Thread(target=run, args=("t%s"%i,))
t.start()
threads.append(t)
# 将所有线程阻塞
for t in threads:
t.join()
end_time = time.time()
print("time:", end_time - start_time)
"""
task: t0
task: t1
task: t2
task: t3
task: t4
task done t4
task done t2
task done t3
task done t1
task done t0
time: 2.0103650093078613
"""
守护线程
import threading
import time
def run(n):
print("task:", n)
time.sleep(2)
print("task done", n)
start_time = time.time()
threads = [] # 保存线程列表
for i in range(5):
t = threading.Thread(target=run, args=("t%s"%i,))
t.setDaemon(True) # 设置为守护线程,主线程停止随之停止
t.start()
threads.append(t)
time.sleep(2) # 等待部分线程执行完毕
end_time = time.time()
print("time:", end_time - start_time)
"""
task: t0
task: t1
task: t2
task: t3
task: t4
task done t2
task done t4
task done t3
task done t1
task done t0
time: 2.0087130069732666
"""
互斥锁
import threading
import time
num = 0
lock = threading.Lock() # 实例化互斥锁
def run(n):
global num
lock.acquire() # 申请锁
time.sleep(2)
num += 1
lock.release() # 释放锁
print(num)
start_time = time.time()
threads = [] # 保存线程列表
for i in range(5):
t = threading.Thread(target=run, args=("t%s"%i,))
t.start()
threads.append(t)
for thread in threads:
thread.join() # 等待部分线程执行完毕
end_time = time.time()
print("time:", end_time - start_time)
print("num:", num)
"""
1
2
3
4
5
time: 10.027688980102539
num: 5
"""
递归锁
import threading
import time
num = 0
lock = threading.RLock() # 实例化递归锁,此处用普通互斥锁会卡死
def run1():
print("run1_start")
lock.acquire() # 第二级锁
print("run1")
lock.release()
def run2():
lock.acquire() # 第二级锁
print("run2")
lock.release()
def run():
lock.acquire() # 第一级锁
print("run1_begin")
run1()
print("run2_begin")
run2()
print("run_end")
lock.release() # 释放锁
start_time = time.time()
t = threading.Thread(target=run)
t.start()
# t.join() # 等待全部线程执行完毕
while threading.active_count() > 1:
print(threading.current_thread())
end_time = time.time()
print("time:", end_time - start_time)
"""
run1_begin
run1_start
run1
run2_begin
run2
run_end
time: 0.0
"""
信号锁
import threading
import time
semaphore = threading.BoundedSemaphore(5) # 设置信号量,最多允许5个线程同时运行
def run(n):
semaphore.acquire() # 信号锁
time.sleep(1)
print("run", n)
semaphore.release()
start_time = time.time()
for i in range(10):
t = threading.Thread(target=run, args=(i,))
t.start()
# 等待全部线程执行完毕
while threading.active_count() != 1:
pass
end_time = time.time()
print("time:", end_time - start_time)
"""
run 1
run 2
run 4
run 0
run 3
run 5
run 7
run 8
run 9
run 6
time: 2.061771869659424
"""