在input()、sleep(2)、request.get()等时，都会导致线程阻塞，协程可以解决IO等操作时的阻塞现象，提高CPU利用效率。
1.单线程的多任务异步协程
main.py
"""=== coding: UTF8 ==="""
import asyncio
import time
async def func1():
print("hello python1")
await asyncio.sleep(2)
print("hello python1")
async def func2():
print("hello python2")
await asyncio.sleep(3)
print("hello python2")
async def func3():
print("hello python3")
await asyncio.sleep(4)
print("hello python3")
async def main():
# 准备异步协程对象列表
tasks = [
asyncio.create_task(func1()),
asyncio.create_task(func2()),
asyncio.create_task(func3())
]
await asyncio.wait(tasks)
"""
========================================
主函数功能测试
========================================
"""
if __name__ == '__main__':
t1 = time.time()
# 一次性运行多个任务
asyncio.run(main())
t2 = time.time()
print(t2 - t1) # 打印耗时的时间
运行效果：
"C:Program FilesPython38python.exe" E:/PythonSourceCode/test/main.py hello python1 hello python2 hello python3 hello python1 hello python2 hello python3 4.022439956665039 Process finished with exit code 0
2.单线程的多任务异步协程在爬虫领域的模拟应用
只是模拟，可以作为模板，在实际爬虫时，需要重点解决
await asyncio.sleep(3) # 模拟网络请求（网络耗时）
main.py
"""=== coding: UTF8 ==="""
import asyncio
import time
# 在爬虫领域的应用
async def download(url):
print("准备开始下载")
await asyncio.sleep(3) # 模拟网络请求（网络耗时）
print("下载完成")
async def main():
urls = ["https://www.hao123.com/", "https://www.baidu.com/", "https://www.bilibili.com/"]
# 准备异步协程对象列表
tasks = []
for url in urls:
d = asyncio.create_task(download(url))
tasks.append(d)
await asyncio.wait(tasks)
"""
========================================
主函数功能测试
========================================
"""
if __name__ == '__main__':
t1 = time.time()
# 一次性运行多个任务
asyncio.run(main())
t2 = time.time()
print(t2 - t1) # 打印耗时的时间
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