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asyncio和 aiohttp

asyncio即Asynchronous I/O是python一个用来处理并发(concurrent)事件的包，是很多python异步架构的基础，多用于处理高并发网络请求方面的问题。

为了简化并更好地标识异步IO，从Python 3.5开始引入了新的语法async和await，可以让coroutine的代码更简洁易读。

asyncio 被用作多个提供高性能 Python 异步框架的基础，包括网络和网站服务，数据库连接库，分布式任务队列等等。

asyncio 往往是构建 IO 密集型和高层级 结构化 网络代码的最佳选择。

import asyncioasync def task(i):print(f"task {i} start")await asyncio.sleep(1)print(f"task {i} end")# 创建事件循环对象
loop = asyncio.get_event_loop()
# 直接将协程对象加入时间循环中
tasks = [task(1), task(2)]
# asyncio.wait:将协程任务进行收集，功能类似后面的asyncio.gather
# run_until_complete阻塞调用，直到协程全部运行结束才返回
loop.run_until_complete(asyncio.wait(tasks))
loop.close()

task: 任务,对协程对象的进一步封装,包含任务的各个状态;asyncio.Task是Future的一个子类，用于实现协作式多任务的库，且Task对象不能用户手动实例化，通过下面2个函数loop.create_task() 或 asyncio.ensure_future()创建。

import asyncio, timeasync def work(i, n):  # 使用async关键字定义异步函数print('任务{}等待: {}秒'.format(i, n))await asyncio.sleep(n)  # 休眠一段时间print('任务{}在{}秒后返回结束运行'.format(i, n))return i + nstart_time = time.time()  # 开始时间tasks = [asyncio.ensure_future(work(1, 1)),asyncio.ensure_future(work(2, 2)),asyncio.ensure_future(work(3, 3))]loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.wait(tasks))
loop.close()print('运行时间: ', time.time() - start_time)
for task in tasks:print('任务执行结果: ', task.result())

3.8版本+ 特性

async.run() 运行协程
async.create_task()创建task
async.gather()获取返回值

import asyncio, timeasync def work(i, n):  # 使用async关键字定义异步函数print('任务{}等待: {}秒'.format(i, n))await asyncio.sleep(n)  # 休眠一段时间print('任务{}在{}秒后返回结束运行'.format(i, n))return i + ntasks = []
async def main():global taskstasks = [asyncio.create_task(work(1, 1)),asyncio.create_task(work(2, 2)),asyncio.create_task(work(3, 3))]await asyncio.wait(tasks) # 阻塞start_time = time.time()  # 开始时间
asyncio.run(main())
print('运行时间: ', time.time() - start_time)
for task in tasks:print('任务执行结果: ', task.result())

asyncio.create_task() 函数在 Python 3.7 中被加入。

asyncio.gather方法

# 用gather()收集返回值import asyncio, timeasync def work(i, n):  # 使用async关键字定义异步函数print('任务{}等待: {}秒'.format(i, n))await asyncio.sleep(n)  # 休眠一段时间print('任务{}在{}秒后返回结束运行'.format(i, n))return i + nasync def main():tasks = [asyncio.create_task(work(1, 1)),asyncio.create_task(work(2, 2)),asyncio.create_task(work(3, 3))]# 将task作为参数传入gather，等异步任务都结束后返回结果列表response = await asyncio.gather(tasks[0], tasks[1], tasks[2])print("异步任务结果：", response)start_time = time.time()  # 开始时间asyncio.run(main())print('运行时间: ', time.time() - start_time)

aiohttp

爬虫最重要的模块requests，但它是阻塞式的发起请求，每次请求发起后需阻塞等待其返回响应，不能做其他的事情。本文要介绍的aiohttp可以理解成是和requests对应Python异步网络请求库，它是基于 asyncio 的异步模块，可用于实现异步爬虫，有点就是更快于 requests 的同步爬虫。安装方式，pip install aiohttp。

aiohttp是一个为Python提供异步HTTP 客户端/服务端编程，基于asyncio的异步库。asyncio可以实现单线程并发IO操作，其实现了TCP、UDP、SSL等协议，aiohttp就是基于asyncio实现的http框架, 使用方式如下。

import aiohttp
import asyncioasync def main():async with aiohttp.ClientSession() as session:async with session.get("http://httpbin.org/headers") as response:print(await response.text())asyncio.run(main())

案例

import asyncio
import os
import aiohttp
import time
from utils.aiorequests import aiorequest
from lxml import etreeheaders = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36"
}url = "https://www.pkdoutu.com/photo/list/"base_url = "https://www.xr02.vip/"async def get_home_url():async with aiohttp.ClientSession() as session:async with session.get(url, headers=headers, ssl=False) as resp:res = await resp.content.read()selector = etree.HTML(res)urls = selector.xpath('//ul/li[@class="i_list list_n2"]/a/@href')return map(lambda i: base_url+i, urls)async def get_page_url(urls):async with aiohttp.ClientSession() as session:async with session.get(urls, headers=headers, ssl=False) as resp:res = await resp.content.read()selector = etree.HTML(res)page_urls = selector.xpath('//div[@class="page"]/a/@href')return map(lambda i: base_url+i, set(page_urls))async def get_img_url(urls):async with aiohttp.ClientSession() as session:async with session.get(urls, headers=headers, ssl=False) as resp:res = await resp.content.read()selector = etree.HTML(res)name = selector.xpath("//h1/text()")[0].replace("[XiuRen秀人网]",'')img_urls = selector.xpath('//p/img/@src')return name, map(lambda i: base_url+i, img_urls)async def download_img(urls, base_name):name = os.path.basename(urls)name = base_name + '_' + nametry:async with aiohttp.ClientSession() as session:async with session.get(urls, headers=headers, ssl=False) as resp:res = await resp.content.read()with open(f"./imgs/{name}","wb") as f:f.write(res)print(f"url: {urls} 下载成功，存储文件为{name}")except:print(f"url: {urls} 下载失败")return "success"async def main():tasks_1 = [asyncio.create_task(get_page_url(i)) for i in await get_home_url()]result_1 = await asyncio.gather(*tasks_1)result_list = []for i in result_1: result_list.extend(list(i))tasks_2 = [asyncio.create_task(get_img_url(i)) for i in result_list]result_2 = await asyncio.gather(*tasks_2)tasks_3 = []for name, img_url in result_2:tasks_3.extend(asyncio.create_task(download_img(url, name)) for url in img_url)await asyncio.gather(*tasks_3)if __name__ == '__main__':if not os.path.isdir("./imgs"):os.mkdir("./imgs")start = time.time()asyncio.run(main())print(time.time()-start)

通过这个案例，可以看到一个问题，那就是 aiohttp的使用，每次都需要写一堆重复代码，并且整个代码结构看起来复杂，作为一个高级开发，必须要会做的就是减少代码重复编写，要将其模块化，封装起来

优化方案

aiorequest.py

class AioRequest:async def request(self, method: str, url: str, data: Union[Dict, bytes, None] = None, **kwargs: Any) -> Any:async with aiohttp.ClientSession() as session:async with session.request(method, url, ssl=False, data=data, **kwargs) as response:if response.status != 200:raise Exception(f"{method.upper()} request failed with status {response.status}")# return await handler(await response.content.read()# return 这里必须带上await，但不支持 await ClientResponse 对象直接返回 必须要处理响应数据# 根据内容类型处理响应体content_type = response.headers.get('Content-Type')if content_type and ('image' in content_type or 'video' in content_type):return await response.read()  # 返回图片或视频的二进制数据elif 'application/json' in content_type:return await response.json()  # 假设响应是JSON格式else:return await response.text()  # 读取文本内容async def get(self, url: str, **kwargs: Any):return await self.request("GET", url, **kwargs)async def post(self, url: str, data: Union[Dict, bytes], **kwargs: Any):return await self.request("POST", url, data=data, **kwargs)# 处理大文件async def save_binary_content(self, url: str, file_path: str, headers: Dict[str, str] = None, **kwargs: Any):async with aiohttp.ClientSession(headers=headers) as session:async with session.get(url, ssl=False, **kwargs) as response:if response.status != 200:raise Exception(f"GET request failed with status {response.status}")with open(file_path, 'wb') as f:while True:chunk = await response.content.read(1024)  # 每次读取1024字节if not chunk:breakf.write(chunk)aiorequest = AioRequest()  # 减少对象的重复创建消耗内存

使用aiorequest 后，代码就简洁明了多了,

import asyncio
import os
import time
from utils.aiorequests import aiorequest
from lxml import etreeheaders = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/110.0.0.0 Safari/537.36"
}base_url = "https://www.xr02.vip/"img_urls_dict = dict()async def get_home_url():res  = await aiorequest.get(base_url)selector = etree.HTML(res)urls = selector.xpath('//ul/li[@class="i_list list_n2"]/a/@href')return map(lambda i: base_url+i, urls)async def get_page_url(urls):res = await aiorequest.get(urls)selector = etree.HTML(res)await get_img_url(res)page_urls = selector.xpath('//div[@class="page"]/a/@href')page_urls = list(map(lambda i: base_url + i, set(page_urls)))page_urls.remove(urls)return page_urlsasync def get_img_url(res):selector = etree.HTML(res)name = selector.xpath("//h1/text()")[0].replace("[XiuRen秀人网]",'')img_list = selector.xpath('//p/img/@src')img_list = map(lambda i: base_url+i, img_list)if name not in img_urls_dict:img_urls_dict.setdefault(name, list(img_list))else:img_urls_dict[name].extend(list(img_list))async def get_imgs_url(urls):res = await aiorequest.get(urls)await get_img_url(res)async def download_img(urls, base_name):name = os.path.basename(urls)name = base_name + '_' + nametry:res = await aiorequest.get(urls)with open(f"./imgs_2/{name}","wb") as f:f.write(res)print(f"url: {urls} 下载成功，存储文件为{name}")except:print(f"url: {urls} 下载失败")return "success"async def main():tasks_1 = [asyncio.create_task(get_page_url(i)) for i in await get_home_url()]result_1 = await asyncio.gather(*tasks_1)result_list = []for i in result_1: result_list.extend(i)tasks_2 = [asyncio.create_task(get_imgs_url(i)) for i in result_list]await asyncio.wait(tasks_2)tasks_3 = []for name, img_url in img_urls_dict.items():tasks_3.extend(asyncio.create_task(download_img(url, name)) for url in img_url)await asyncio.wait(tasks_3)if __name__ == '__main__':if not os.path.isdir("./imgs_2"):os.mkdir("./imgs_2")start = time.time()asyncio.run(main())print(time.time()-start)