add python_thread_multiprocess.py

README.md

@@ -29,6 +29,8 @@
 ### python_coroutine.py: Python进阶: 理解Python中的异步IO和协程(Coroutine), 并应用在爬虫中
 
 ### python_aiohttp.py: Python中最好用的异步爬虫库Aiohttp代码实例
+
+### python_thread_multiprocess.py: Python进阶: 聊聊IO密集型任务、计算密集型任务，以及多线程、多进程
 ===================================================================================================
 
 ### 您可以fork该项目,并在修改后提交Pull request

python_thread_multiprocess.py

@@ -0,0 +1,115 @@
+# _*_ coding: utf-8 _*_
+
+"""
+python_thread_multiprocee.py by xianhu
+"""
+
+import time
+import threading
+import multiprocessing
+
+# 定义全局变量Queue
+g_queue = multiprocessing.Queue()
+g_search_list = list(range(10000))
+
+
+# 定义一个IO密集型任务：利用time.sleep()
+def task_io(task_id):
+    print("IOTask[%s] start" % task_id)
+    while not g_queue.empty():
+        time.sleep(1)
+        try:
+            data = g_queue.get(block=True, timeout=1)
+            print("IOTask[%s] get data: %s" % (task_id, data))
+        except Exception as excep:
+            print("IOTask[%s] error: %s" % (task_id, str(excep)))
+    print("IOTask[%s] end" % task_id)
+    return
+
+
+# 定义一个计算密集型任务：利用一些复杂加减乘除、列表查找等
+def task_cpu(task_id):
+    print("CPUTask[%s] start" % task_id)
+    while not g_queue.empty():
+        count = 0
+        for i in range(10000):
+            count += pow(3*2, 3*2) if i in g_search_list else 0
+        try:
+            data = g_queue.get(block=True, timeout=1)
+            print("CPUTask[%s] get data: %s" % (task_id, data))
+        except Exception as excep:
+            print("CPUTask[%s] error: %s" % (task_id, str(excep)))
+    print("CPUTask[%s] end" % task_id)
+    return task_id
+
+
+def init_queue():
+    print("init g_queue start")
+    while not g_queue.empty():
+        g_queue.get()
+    for _index in range(10):
+        g_queue.put(_index)
+    print("init g_queue end")
+    return
+
+
+if __name__ == '__main__':
+    print("cpu count:", multiprocessing.cpu_count(), "\n")
+
+    print("========== 直接执行IO密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    task_io(0)
+    print("结束：", time.time() - time_0, "\n")
+
+    print("========== 多线程执行IO密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    thread_list = [threading.Thread(target=task_io, args=(i,)) for i in range(5)]
+    for t in thread_list:
+        t.start()
+    for t in thread_list:
+        if t.is_alive():
+            t.join()
+    print("结束：", time.time() - time_0, "\n")
+
+    print("========== 多进程执行IO密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    process_list = [multiprocessing.Process(target=task_io, args=(i,)) for i in range(multiprocessing.cpu_count())]
+    for p in process_list:
+        p.start()
+    for p in process_list:
+        if p.is_alive():
+            p.join()
+    print("结束：", time.time() - time_0, "\n")
+
+    print("========== 直接执行CPU密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    task_cpu(0)
+    print("结束：", time.time() - time_0, "\n")
+
+    print("========== 多线程执行CPU密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    thread_list = [threading.Thread(target=task_cpu, args=(i,)) for i in range(5)]
+    for t in thread_list:
+        t.start()
+    for t in thread_list:
+        if t.is_alive():
+            t.join()
+    print("结束：", time.time() - time_0, "\n")
+
+    print("========== 多进程执行cpu密集型任务 ==========")
+    init_queue()
+    time_0 = time.time()
+    process_list = [multiprocessing.Process(target=task_cpu, args=(i,)) for i in range(multiprocessing.cpu_count())]
+    for p in process_list:
+        p.start()
+    for p in process_list:
+        if p.is_alive():
+            p.join()
+    print("结束：", time.time() - time_0, "\n")
+
+    exit()