From：https://www.cnblogs.com/bravexz/p/7741633.html

爬虫应用 asyncio 模块 ( 高性能爬虫 )：https://www.cnblogs.com/morgana/p/8495555.html

python异步编程之asyncio（百万并发）：https://www.cnblogs.com/shenh/p/9090586.html

深入理解 Python 异步编程(上)：https://blog.csdn.net/catwan/article/details/84975893

https://mp.weixin.qq.com/s?__biz=MjM5OTA1MDUyMA==&mid=2655439072&idx=3&sn=07ca0046b92998ea216958afa5baff8f

requests + asyncio ：https://github.com/wangy8961/python3-concurrency-pics-02

python 高并发模块 asynio：https://www.jianshu.com/p/9ea1198beb49

aiohttp 官网文档 ：https://docs.aiohttp.org/en/latest/

关键字：python 异步编程   、asyncio requests

 

写爬虫时性能的消耗主要在IO请求中，当单进程单线程模式下请求URL时必然会引起等待，从而使得请求整体变慢。

 

 

同步执行

 

示例代码：

import requestsdef fetch_async(url=None):response = requests.get(url)return responseurl_list = ['http://www.github.com', 'http://www.bing.com']for url in url_list:fetch_async(url)

 

 

多线程执行

 

示例代码：

from concurrent.futures import ThreadPoolExecutor
import requestsdef fetch_async(url):response = requests.get(url)return responseurl_list = ['http://www.github.com', 'http://www.bing.com']pool = ThreadPoolExecutor(5)
for url in url_list:pool.submit(fetch_async, url)
pool.shutdown(wait=True)

 

 

多线程 + 回调函数执行

 

示例代码：

# -*- coding: utf-8 -*-from concurrent.futures import ThreadPoolExecutor
import requestsdef fetch_async(url):response = requests.get(url)return responsedef callback(future):print(future.result())url_list = ['http://www.github.com', 'http://www.bing.com']pool = ThreadPoolExecutor(5)
for url in url_list:v = pool.submit(fetch_async, url)v.add_done_callback(callback)
pool.shutdown(wait=True)

 

 

多进程执行

 

示例代码：

# -*- coding: utf-8 -*-from concurrent.futures import ProcessPoolExecutor
import requestsdef fetch_async(url):response = requests.get(url)return responseurl_list = ['http://www.github.com', 'http://www.bing.com']pool = ProcessPoolExecutor(5)
for url in url_list:pool.submit(fetch_async, url)
pool.shutdown(wait=True)

 

 

多进程 + 回调函数执行

 

示例代码：

# -*- coding: utf-8 -*-from concurrent.futures import ProcessPoolExecutor
import requestsdef fetch_async(url):response = requests.get(url)return responsedef callback(future):print(future.result())url_list = ['http://www.github.com', 'http://www.bing.com']pool = ProcessPoolExecutor(5)
for url in url_list:v = pool.submit(fetch_async, url)v.add_done_callback(callback)
pool.shutdown(wait=True)

 

通过上述代码均可以完成对请求性能的提高，对于多线程和多进程的缺点是在IO阻塞时会造成了线程和进程的浪费，所以异步IO会是首选：

 

 

异步 IO

 

Python 中 异步协程 的 使用方法介绍：https://blog.csdn.net/freeking101/article/details/88119858

python---异步IO(asyncio)协程 ：https://www.cnblogs.com/ssyfj/p/9219360.html

 

 

python 由于 GIL（全局锁）的存在，不能发挥多核的优势，其性能一直饱受诟病。然而在 IO 密集型的网络编程里，异步处理比同步处理能提升成百上千倍的效率，弥补了 python 性能方面的短板，如最新的微服务框架 japronto，每秒的请求 可达百万级。

python 还有一个优势是库（第三方库）极为丰富，运用十分方便。asyncio 是 python3.4 版本引入到标准库，python2x 没有加这个库，毕竟 python3x 才是未来！python3.5 又加入了 async/await 特性。

 

在学习 asyncio 之前，先的理清楚 同步/异步的概念：

• · 同步 是指完成事务的逻辑，先执行第一个事务，如果阻塞了，会一直等待，直到这个事务完成，再执行第二个事务，顺序执行。。。
• · 异步 是和同步相对的，异步是指在处理调用这个事务的之后，不会等待这个事务的处理结果，直接处理第二个事务去了，通过状态、通知、回调 来通知 调用者处理结果。

 

调用步骤：

• 1. 当我们给一个函数添加了async 关键字，或者使用 asyncio.coroutine 装饰器装饰，就会把它变成一个异步函数。 
• 2. 每个线程 有一个 事件循环，主线程调用 asyncio.get_event_loop 时会创建事件循环，
• 3. 将任务封装为集合 asyncio.gather(*args)，之后一起传入事件循环中
• 4. 要把异步的任务丢给这个循环的 run_until_complete 方法，事件循环会安排协同程序的执行。和方法名字一样，该方法会等待异步的任务完全执行才会结束。

 

asyncio 示例 1

# -*- coding: utf-8 -*-import asyncio@asyncio.coroutine
def func1():print('before...func1......')yield from asyncio.sleep(5)print('end...func1......')tasks = [func1(), func1()]loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

 

asyncio 示例 2

# -*- coding: utf-8 -*-import asyncio@asyncio.coroutine
def fetch_async(host, url='/'):print(host, url)reader, writer = yield from asyncio.open_connection(host, 80)request_header_content = """GET %s HTTP/1.0\r\nHost: %s\r\n\r\n""" % (url, host,)request_header_content = bytes(request_header_content, encoding='utf-8')writer.write(request_header_content)yield from writer.drain()text = yield from reader.read()print(host, url, text)writer.close()tasks = [fetch_async('www.cnblogs.com', '/wupeiqi/'),fetch_async('dig.chouti.com', '/pic/show?nid=4073644713430508&lid=10273091')
]loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

 

 

asyncio + aiohttp

参考：https://www.cnblogs.com/zhanghongfeng/p/8662265.html

用 aiohttp 写爬虫：https://luca-notebook.readthedocs.io/zh_CN/latest/c01/用aiohttp写爬虫.html

 

aiohttp

　　如果需要并发 http 请求怎么办呢，通常是用 requests，但 requests 是同步的库，如果想异步的话需要引入 aiohttp。这里引入一个类，from aiohttp import ClientSession，首先要建立一个 session 对象，然后用 session 对象去打开网页。session 可以进行多项操作，比如 post, get, put, head 等。

示例：

import asyncio
from aiohttp import ClientSessiontasks = []
test_url = "https://www.baidu.com/{}"async def hello(url):async with ClientSession() as session:async with session.get(url) as response:response = await response.read()print(response)if __name__ == '__main__':loop = asyncio.get_event_loop()loop.run_until_complete(hello(test_url))

首先async def 关键字定义了这是个异步函数，await 关键字加在需要等待的操作前面，response.read()等待request响应，是个耗IO操作。然后使用ClientSession类发起http请求。

 

多链接 异步 访问

如果我们需要请求多个URL该怎么办呢，同步的做法访问多个URL只需要加个for循环就可以了。但异步的实现方式并没那么容易，在之前的基础上需要将hello()包装在asyncio的Future对象中，然后将Future对象列表作为任务传递给事件循环。

import time
import asyncio
from aiohttp import ClientSessiontasks = []
test_url = "https://www.baidu.com/{}"async def hello(url):async with ClientSession() as session:async with session.get(url) as response:response = await response.read()#            print(response)print('Hello World:%s' % time.time())def run():for i in range(5):task = asyncio.ensure_future(hello(test_url.format(i)))tasks.append(task)if __name__ == '__main__':loop = asyncio.get_event_loop()run()loop.run_until_complete(asyncio.wait(tasks))

 

收集 http 响应

上面介绍了访问不同链接的异步实现方式，但是我们只是发出了请求，如果要把响应一一收集到一个列表中，最后保存到本地或者打印出来要怎么实现呢，可通过asyncio.gather(*tasks)将响应全部收集起来，具体通过下面实例来演示。

import datetime
import asyncio
from aiohttp import ClientSessiontasks = []
test_url = "https://www.baidu.com/{}"async def hello(url):async with ClientSession() as session:async with session.get(url) as response:# print(response)print(f'Hello World : {datetime.datetime.now().replace(microsecond=0)}')return await response.read()def run():for i in range(5):task = asyncio.ensure_future(hello(test_url.format(i)))tasks.append(task)result = loop.run_until_complete(asyncio.gather(*tasks))print(result)if __name__ == '__main__':loop = asyncio.get_event_loop()run()

假如你的并发达到2000个，程序会报错：ValueError: too many file descriptors in select()。报错的原因字面上看是 Python 调取的 select 对打开的文件有最大数量的限制，这个其实是操作系统的限制，linux打开文件的最大数默认是1024，windows默认是509，超过了这个值，程序就开始报错。

这里我们有 三种方法解决 这个问题：

• 1.限制并发数量。（一次不要塞那么多任务，或者限制最大并发数量）
• 2.使用回调的方式。
• 3.修改操作系统打开文件数的最大限制，在系统里有个配置文件可以修改默认值，具体步骤不再说明了。

不修改系统默认配置的话，个人推荐限制并发数的方法，设置并发数为 500，处理速度更快。

# coding:utf-8
import time, asyncio, aiohttptest_url = 'https://www.baidu.com/'async def hello(url, semaphore):async with semaphore:async with aiohttp.ClientSession() as session:async with session.get(url) as response:print(f'status:{response.status}')return await response.read()async def run():semaphore = asyncio.Semaphore(500)  # 限制并发量为500to_get = [hello(test_url.format(), semaphore) for _ in range(1000)]  # 总共1000任务await asyncio.wait(to_get)if __name__ == '__main__':# now = lambda :time.time()loop = asyncio.get_event_loop()loop.run_until_complete(run())loop.close()

示例代码：

# -*- coding: utf-8 -*-import aiohttp
import asyncio@asyncio.coroutine
def fetch_async(url):print(url)# request函数是个IO阻塞型的函数# response = yield from aiohttp.request('GET', url)response = yield from aiohttp.ClientSession().get(url)print(response.status)print(url, response)# data = yield from response.read()return responsetasks = [# fetch_async('http://www.google.com/'),fetch_async('http://www.chouti.com/')
]event_loop = asyncio.get_event_loop()
results = event_loop.run_until_complete(asyncio.gather(*tasks))
event_loop.close()

 

Python3 协程控制 并发数 的 两种方法

1、TCPConnector 链接池

import asyncio
import aiohttpCONCURRENT_REQUESTS = 0async def aio_http_get(url, session):global CONCURRENT_REQUESTSasync with session.get(url) as response:CONCURRENT_REQUESTS += 1html = await response.text()print(f'[{CONCURRENT_REQUESTS}] : {response.status}')return htmldef main():urls = ['http://www.baidu.com' for _ in range(1000)]loop = asyncio.get_event_loop()connector = aiohttp.TCPConnector(limit=10)  # 限制同时链接数，连接默认是100，limit=0 无限制session = aiohttp.ClientSession(connector=connector, loop=loop)loop.run_until_complete(asyncio.gather(*(aio_http_get(url, session=session) for url in urls)))loop.close()passif __name__ == "__main__":main()

2、Semaphore 信号量

import asyncio
from aiohttp import ClientSession, TCPConnectorasync def async_spider(sem, url):"""异步任务"""async with sem:print('Getting data on url', url)async with ClientSession() as session:async with session.get(url) as response:html = await response.text()return htmldef parse_html(task):print(f'Status:{task.result()}')passasync def task_manager():"""异步任务管理器"""tasks = []sem = asyncio.Semaphore(10)  # 控制并发数url_list = ['http://www.baidu.com' for _ in range(100)]for url in url_list:task = asyncio.create_task(async_spider(sem, url))task.add_done_callback(parse_html)tasks.append(task)await asyncio.gather(*tasks)if __name__ == '__main__':print('Task start! It is working...')loop = asyncio.get_event_loop()loop.run_until_complete(task_manager())print('Finished!')

示例代码 2：

import os
import sys
import aiohttp
import asynciosys.path.append(os.getcwd())
sys.path.append("..")
sys.path.append(os.path.abspath("../../"))CONCURRENT_REQUESTS = 20
CONCURRENT_REQUESTS_actual = 0async def hello(sem, url):async with sem:      async with aiohttp.ClientSession() as session:           async with session.get('http://www.baidu.com', allow_redirects=False) as response:r = await response.read()print(f'[{url}] : http://www.baidu.com   {response.status}')def main():loop = asyncio.get_event_loop()tasks = []# 限制协程并发量sem = asyncio.Semaphore(CONCURRENT_REQUESTS)  # thisfor i in range(100000):task = asyncio.ensure_future(hello(sem, i))tasks.append(task)feature = asyncio.ensure_future(asyncio.gather(*tasks))loop.run_until_complete(feature)if __name__ == "__main__":main()

 

asyncio + requests

# -*- coding: utf-8 -*-import asyncio
import requests@asyncio.coroutine
def fetch_async(func, *args):loop = asyncio.get_event_loop()future = loop.run_in_executor(None, func, *args)response = yield from futureprint(response.url, response.content)tasks = [fetch_async(requests.get, 'http://www.cnblogs.com/wupeiqi/'),fetch_async(requests.get, 'http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091')
]loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

 

gevent + requests

# -*- coding: utf-8 -*-import geventimport requests
from gevent import monkeymonkey.patch_all()def fetch_async(method, url, req_kwargs):print(method, url, req_kwargs)response = requests.request(method=method, url=url, **req_kwargs)print(response.url, response.content)# ##### 发送请求 #####
gevent.joinall([gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),gevent.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}),
])# ##### 发送请求（协程池控制最大协程数量） #####
# from gevent.pool import Pool
# pool = Pool(None)
# gevent.joinall([
#     pool.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
#     pool.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
#     pool.spawn(fetch_async, method='get', url='https://www.github.com/', req_kwargs={}),
# ])

 

grequests

# -*- coding: utf-8 -*-import grequestsrequest_list = [grequests.get('http://httpbin.org/delay/1', timeout=0.001),grequests.get('http://fakedomain/'),grequests.get('http://httpbin.org/status/500')
]# ##### 执行并获取响应列表 #####
response_list = grequests.map(request_list)
print(response_list)# ##### 执行并获取响应列表（处理异常） #####
# def exception_handler(request, exception):
# print(request,exception)
#     print("Request failed")# response_list = grequests.map(request_list, exception_handler=exception_handler)
# print(response_list)

 

Twisted 示例

from twisted.web.client import getPage, defer
from twisted.internet import reactordef all_done(arg):reactor.stop()def callback(contents):print(contents)deferred_list = []url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
for url in url_list:deferred = getPage(bytes(url, encoding='utf8'))deferred.addCallback(callback)deferred_list.append(deferred)dlist = defer.DeferredList(deferred_list)
dlist.addBoth(all_done)reactor.run()

 

Tornado 示例

# -*- coding: utf-8 -*-from tornado.httpclient import AsyncHTTPClient
from tornado.httpclient import HTTPRequest
from tornado import ioloopdef handle_response(response):"""处理返回值内容（需要维护计数器，来停止IO循环），调用 ioloop.IOLoop.current().stop():param response::return:"""if response.error:print("Error:", response.error)else:print(response.body)def func():url_list = ['http://www.baidu.com','http://www.bing.com',]for url in url_list:print(url)http_client = AsyncHTTPClient()http_client.fetch(HTTPRequest(url), handle_response)ioloop.IOLoop.current().add_callback(func)
ioloop.IOLoop.current().start()

 

Twisted 更多

# -*- coding: utf-8 -*-from twisted.internet import reactor
from twisted.web.client import getPage
import urllib.parsedef one_done(arg):print(arg)reactor.stop()post_data = urllib.parse.urlencode({'check_data': 'adf'})
post_data = bytes(post_data, encoding='utf8')
headers = {b'Content-Type': b'application/x-www-form-urlencoded'}
response = getPage(bytes('http://dig.chouti.com/login', encoding='utf8'),method=bytes('POST', encoding='utf8'),postdata=post_data,cookies={},headers=headers)
response.addBoth(one_done)reactor.run()

 

以上均是 Python内置以及第三方模块提供异步IO请求模块，使用简便大大提高效率，

而对于异步IO请求的本质则是【非阻塞Socket】+【IO多路复用】：

 

 

非阻塞Socket + IO多路复用

 

 史上最牛逼的 异步 IO 模块 （ select、poll、epoll）

import select
import socket
import timeclass AsyncTimeoutException(TimeoutError):"""请求超时异常类"""def __init__(self, msg):self.msg = msgsuper(AsyncTimeoutException, self).__init__(msg)class HttpContext(object):"""封装请求和相应的基本数据"""def __init__(self, sock, host, port, method, url, data, callback, timeout=5):"""sock: 请求的客户端socket对象host: 请求的主机名port: 请求的端口port: 请求的端口method: 请求方式url: 请求的URLdata: 请求时请求体中的数据callback: 请求完成后的回调函数timeout: 请求的超时时间"""self.sock = sockself.callback = callbackself.host = hostself.port = portself.method = methodself.url = urlself.data = dataself.timeout = timeoutself.__start_time = time.time()self.__buffer = []def is_timeout(self):"""当前请求是否已经超时"""current_time = time.time()if (self.__start_time + self.timeout) < current_time:return Truedef fileno(self):"""请求sockect对象的文件描述符，用于select监听"""return self.sock.fileno()def write(self, data):"""在buffer中写入响应内容"""self.__buffer.append(data)def finish(self, exc=None):"""在buffer中写入响应内容完成，执行请求的回调函数"""if not exc:response = b''.join(self.__buffer)self.callback(self, response, exc)else:self.callback(self, None, exc)def send_request_data(self):content = """%s %s HTTP/1.0\r\nHost: %s\r\n\r\n%s""" % (self.method.upper(), self.url, self.host, self.data,)return content.encode(encoding='utf8')class AsyncRequest(object):def __init__(self):self.fds = []self.connections = []def add_request(self, host, port, method, url, data, callback, timeout):"""创建一个要请求"""client = socket.socket()client.setblocking(False)try:client.connect((host, port))except BlockingIOError as e:pass# print('已经向远程发送连接的请求')req = HttpContext(client, host, port, method, url, data, callback, timeout)self.connections.append(req)self.fds.append(req)def check_conn_timeout(self):"""检查所有的请求，是否有已经连接超时，如果有则终止"""timeout_list = []for context in self.connections:if context.is_timeout():timeout_list.append(context)for context in timeout_list:context.finish(AsyncTimeoutException('请求超时'))self.fds.remove(context)self.connections.remove(context)def running(self):"""事件循环，用于检测请求的socket是否已经就绪，从而执行相关操作"""while True:r, w, e = select.select(self.fds, self.connections, self.fds, 0.05)if not self.fds:returnfor context in r:sock = context.sockwhile True:try:data = sock.recv(8096)if not data:self.fds.remove(context)context.finish()breakelse:context.write(data)except BlockingIOError as e:breakexcept TimeoutError as e:self.fds.remove(context)self.connections.remove(context)context.finish(e)breakfor context in w:# 已经连接成功远程服务器，开始向远程发送请求数据if context in self.fds:data = context.send_request_data()context.sock.sendall(data)self.connections.remove(context)self.check_conn_timeout()if __name__ == '__main__':def callback_func(context, response, ex):""":param context: HttpContext对象，内部封装了请求相关信息:param response: 请求响应内容:param ex: 是否出现异常（如果有异常则值为异常对象；否则值为None）:return:"""print(context, response, ex)obj = AsyncRequest()url_list = [{'host': 'www.google.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,'callback': callback_func},{'host': 'www.baidu.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,'callback': callback_func},{'host': 'www.bing.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,'callback': callback_func},]for item in url_list:print(item)obj.add_request(**item)obj.running()

 

 

Scrapy

 

Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。 其可以应用在数据挖掘，信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的， 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛，可以用于数据挖掘、监测和自动化测试。

Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下

Scrapy主要包括了以下组件：

• 引擎(Scrapy)
  用来处理整个系统的数据流处理, 触发事务(框架核心)
• 调度器(Scheduler)
  用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL（抓取网页的网址或者说是链接）的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址
• 下载器(Downloader)
  用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的)
• 爬虫(Spiders)
  爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面
• 项目管道(Pipeline)
  负责处理爬虫从网页中抽取的实体，主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后，将被发送到项目管道，并经过几个特定的次序处理数据。
• 下载器中间件(Downloader Middlewares)
  位于Scrapy引擎和下载器之间的框架，主要是处理Scrapy引擎与下载器之间的请求及响应。
• 爬虫中间件(Spider Middlewares)
  介于Scrapy引擎和爬虫之间的框架，主要工作是处理蜘蛛的响应输入和请求输出。
• 调度中间件(Scheduler Middewares)
  介于Scrapy引擎和调度之间的中间件，从Scrapy引擎发送到调度的请求和响应。

Scrapy运行流程大概如下：

1. 引擎从调度器中取出一个链接(URL)用于接下来的抓取
2. 引擎把URL封装成一个请求(Request)传给下载器
3. 下载器把资源下载下来，并封装成应答包(Response)
4. 爬虫解析Response
5. 解析出实体（Item）,则交给实体管道进行进一步的处理
6. 解析出的是链接（URL）,则把URL交给调度器等待抓取

 

一、scrapy 的安装

 

Linux
      pip3 install scrapy 
 
Windows

• a.  pip3 install wheel
• b.  下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
• c.  进入下载目录，执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
• d.  pip3 install scrapy
• e.  下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/

 

二、scrapy 的基本使用

 

一、基本命令

1. scrapy startproject 项目名称- 在当前目录中创建中创建一个项目文件（类似于Django）2. scrapy genspider [-t template] <name> <domain>- 创建爬虫应用如：scrapy gensipider -t basic oldboy oldboy.comscrapy gensipider -t xmlfeed autohome autohome.com.cnPS:查看所有命令：scrapy gensipider -l查看模板命令：scrapy gensipider -d 模板名称3. scrapy list- 展示爬虫应用列表4. scrapy crawl 爬虫应用名称- 运行单独爬虫应用

 

二、项目结构及其爬虫应用简介

project_name/scrapy.cfgproject_name/__init__.pyitems.pypipelines.pysettings.pyspiders/__init__.py爬虫1.py爬虫2.py爬虫3.py

文件说明：

• scrapy.cfg  项目的主配置信息。（真正爬虫相关的配置信息在settings.py文件中）
• items.py    设置数据存储模板，用于结构化数据，如：Django的Model
• pipelines    数据处理行为，如：一般结构化的数据持久化
• settings.py 配置文件，如：递归的层数、并发数，延迟下载等
• spiders      爬虫目录，如：创建文件，编写爬虫规则

注意：一般创建爬虫文件时，以网站域名命名

import scrapyclass XiaoHuarSpider(scrapy.spiders.Spider):name = "xiaohuar"                            # 爬虫名称 *****allowed_domains = ["xueshengmai.com"]  # 允许的域名start_urls = ["http://www.xueshengmai.com/hua/",   # 其实URL]def parse(self, response):# 访问起始URL并获取结果后的回调函数pass

关于 windows 的编码问题import sys,os
sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')

 

三、开始项目

# -*- coding: utf-8 -*-import scrapy
from scrapy.selector import Selector
from scrapy.http.request import Requestclass DigSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "dig"# 允许的域名allowed_domains = ["chouti.com"]# 起始URLstart_urls = ['http://dig.chouti.com/',]has_request_set = {}def parse(self, response):print(response.url)hxs = Selector(response=response)page_list = hxs.xpath(r'//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()for page in page_list:page_url = 'http://dig.chouti.com%s' % pagekey = self.md5(page_url)if key in self.has_request_set:passelse:self.has_request_set[key] = page_urlobj = Request(url=page_url, method='GET', callback=self.parse)yield obj@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return keyif __name__ == '__main__':from scrapy import cmdlinecmdline.execute('scrapy crawl dig'.split())pass    

执行此爬虫文件，则在终端进入项目目录执行如下命令：scrapy crawl dig --nolog

对于上述代码重要之处在于：

• Request 是一个封装用户请求的类，在回调函数中yield该对象表示继续访问
• Selector 用于结构化 HTML 代码并提供选择器功能。 ( HtmlXpathSelector 已被弃用 ）

 

四、scrapy 的选择器

# -*- coding: utf-8 -*-from scrapy.selector import Selector
from scrapy.http import HtmlResponse
html = """
<!DOCTYPE html>
<html><head lang="en"><meta charset="UTF-8"><title></title></head><body><ul><li class="item-"><a id='i1' href="link.html">first item</a></li><li class="item-0"><a id='i2' href="llink.html">first item</a></li><li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li></ul><div><a href="llink2.html">second item</a></div></body>
</html>
"""
response = HtmlResponse(url='http://example.com', body=html, encoding='utf-8')hxs = Selector(response=response).xpath('//a')
print(hxs)
hxs = Selector(response=response).xpath('//a[2]')
print(hxs)
hxs = Selector(response=response).xpath('//a[@id]')
print(hxs)
hxs = Selector(response=response).xpath('//a[@id="i1"]')
print(hxs)
hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]')
print(hxs)
hxs = Selector(response=response).xpath('//a[contains(@href, "link")]')
print(hxs)
hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]')
print(hxs)
hxs = Selector(response=response).xpath(r'//a[re:test(@id, "i\d+")]')
print(hxs)
hxs = Selector(response=response).xpath(r'//a[re:test(@id, "i\d+")]/text()').extract()
print(hxs)
hxs = Selector(response=response).xpath(r'//a[re:test(@id, "i\d+")]/@href').extract()
print(hxs)
hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract()
print(hxs)
hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()
print(hxs)ul_list = Selector(response=response).xpath('//body/ul/li')
for item in ul_list:v = item.xpath('./a/span')# 或# v = item.xpath('a/span')# 或# v = item.xpath('*/a/span')print(v)

自动登录抽屉并点赞

# -*- coding: utf-8 -*-import scrapy
from scrapy.selector import Selector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequestclass ChouTiSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "chouti"# 允许的域名allowed_domains = ["chouti.com"]cookie_dict = {}has_request_set = {}def start_requests(self):url = 'http://dig.chouti.com/'# return [Request(url=url, callback=self.login)]yield Request(url=url, callback=self.login)def login(self, response):cookie_jar = CookieJar()cookie_jar.extract_cookies(response, response.request)for k, v in cookie_jar._cookies.items():for i, j in v.items():for m, n in j.items():self.cookie_dict[m] = n.valuereq = Request(url='http://dig.chouti.com/login',method='POST',headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},body='phone=8615131255089&password=pppppppp&oneMonth=1',cookies=self.cookie_dict,callback=self.check_login)yield reqdef check_login(self, response):req = Request(url='http://dig.chouti.com/',method='GET',callback=self.show,cookies=self.cookie_dict,dont_filter=True)yield reqdef show(self, response):# print(response)hxs = Selector(response=response)news_list = hxs.xpath('//div[@id="content-list"]/div[@class="item"]')for new in news_list:# temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()yield Request(url='http://dig.chouti.com/link/vote?linksId=%s' % (link_id,),method='POST',cookies=self.cookie_dict,callback=self.do_favor)page_list = hxs.xpath(r'//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()for page in page_list:page_url = 'http://dig.chouti.com%s' % pageimport hashlibhash = hashlib.md5()hash.update(bytes(page_url, encoding='utf-8'))key = hash.hexdigest()if key in self.has_request_set:passelse:self.has_request_set[key] = page_urlyield Request(url=page_url,method='GET',callback=self.show)def do_favor(self, response):print(response.text)if __name__ == '__main__':from scrapy import cmdlinecmdline.execute('scrapy crawl chouti'.split())pass

注意：settings.py 中设置 DEPTH_LIMIT = 1来指定  “递归”  的层数。

 

五、格式化处理

上述实例只是简单的处理，所以在 parse 方法中直接处理。如果对于想要获取更多的数据处理，则可以利用 Scrapy 的 items 将数据格式化，然后统一交由 pipelines 来处理。

spiders/xiahuar.py

import scrapy
from scrapy.selector import Selector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest
from ..items import XiaoHuarItemclass XiaoHuarSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "xiaohuar"# 允许的域名allowed_domains = ["xueshengmai.com"]start_urls = ["http://www.xueshengmai.com/hua/",]# custom_settings = {#     'ITEM_PIPELINES':{#         'spider1.pipelines.JsonPipeline': 100#     }# }has_request_set = {}def parse(self, response):# 分析页面# 找到页面中符合规则的内容（校花图片），保存# 找到所有的a标签，再访问其他a标签，一层一层的搞下去hxs = Selector(response=response)items = hxs.xpath('//div[@class="item_list infinite_scroll"]/div')for item in items:src = item.select('.//div[@class="img"]/a/img/@src').extract_first()name = item.select('.//div[@class="img"]/span/text()').extract_first()school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()url = "http://www.xiaohuar.com%s" % srcobj = XiaoHuarItem(name=name, school=school, url=url)yield objurls = hxs.xpath(r'//a[re:test(@href, "http://www.xueshengmai.com/list-1-\d+.html")]/@href')for url in urls:key = self.md5(url)if key in self.has_request_set:passelse:self.has_request_set[key] = urlreq = Request(url=url, method='GET', callback=self.parse)yield req@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return key

items

import scrapyclass XiaoHuarItem(scrapy.Item):name = scrapy.Field()school = scrapy.Field()url = scrapy.Field()

 

改进（ 不需要 item ，直接返回一个 Python 类型的 dict ）：

可以不需要 item ，直接返回一个 Python 类型的 dict 即可，因为 Scrapy 的 item 本身就是一个 Python 类型 的 dict

import scrapy
from scrapy.selector import Selector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequestclass XiaoHuarSpider(scrapy.Spider):# 爬虫应用的名称，通过此名称启动爬虫命令name = "xiaohuar"# 允许的域名allowed_domains = ["xueshengmai.com"]start_urls = ["http://www.xueshengmai.com/hua/",]# custom_settings = {#     'ITEM_PIPELINES':{#         'spider1.pipelines.JsonPipeline': 100#     }# }has_request_set = {}def parse(self, response):# 分析页面# 找到页面中符合规则的内容（校花图片），保存# 找到所有的a标签，再访问其他a标签，一层一层的搞下去hxs = Selector(response=response)items = hxs.xpath('//div[@class="item_list infinite_scroll"]/div')for item in items:src = item.select('.//div[@class="img"]/a/img/@src').extract_first()name = item.select('.//div[@class="img"]/span/text()').extract_first()school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()url = "http://www.xiaohuar.com%s" % srcobj = dict(name=name, school=school, url=url)            yield objurls = hxs.xpath(r'//a[re:test(@href, "http://www.xueshengmai.com/list-1-\d+.html")]/@href')for url in urls:key = self.md5(url)if key in self.has_request_set:passelse:self.has_request_set[key] = urlreq = Request(url=url, method='GET', callback=self.parse)yield req@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return key

pipelines

import json
import os
import requestsclass JsonPipeline(object):def __init__(self):self.file = open('xiaohua.txt', 'w')def process_item(self, item, spider):v = json.dumps(dict(item), ensure_ascii=False)self.file.write(v)self.file.write('\n')self.file.flush()return itemclass FilePipeline(object):def __init__(self):if not os.path.exists('imgs'):os.makedirs('imgs')def process_item(self, item, spider):response = requests.get(item['url'], stream=True)file_name = '%s_%s.jpg' % (item['name'], item['school'])with open(os.path.join('imgs', file_name), mode='wb') as f:f.write(response.content)return item

settings

ITEM_PIPELINES = {'spider1.pipelines.JsonPipeline': 100,'spider1.pipelines.FilePipeline': 300,
}
# 每行后面的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。

对于pipeline可以做更多，如下：

自定义 pipeline

from scrapy.exceptions import DropItemclass CustomPipeline(object):def __init__(self,v):self.value = vdef process_item(self, item, spider):# 操作并进行持久化# return表示会被后续的pipeline继续处理return item# 表示将item丢弃，不会被后续pipeline处理# raise DropItem()@classmethoddef from_crawler(cls, crawler):"""初始化时候，用于创建pipeline对象:param crawler: :return: """val = crawler.settings.getint('MMMM')return cls(val)def open_spider(self,spider):"""爬虫开始执行时，调用:param spider: :return: """print('000000')def close_spider(self,spider):"""爬虫关闭时，被调用:param spider: :return: """print('111111')

 

六、中间件

爬虫中间件

class SpiderMiddleware(object):def process_spider_input(self,response, spider):"""下载完成，执行，然后交给parse处理:param response: :param spider: :return: """passdef process_spider_output(self,response, result, spider):"""spider处理完成，返回时调用:param response::param result::param spider::return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)"""return resultdef process_spider_exception(self,response, exception, spider):"""异常调用:param response::param exception::param spider::return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline"""return Nonedef process_start_requests(self,start_requests, spider):"""爬虫启动时调用:param start_requests::param spider::return: 包含 Request 对象的可迭代对象"""return start_requests

下载器中间件

class DownMiddleware1(object):def process_request(self, request, spider):"""请求需要被下载时，经过所有下载器中间件的process_request调用:param request: :param spider: :return:  None,继续后续中间件去下载；Response对象，停止process_request的执行，开始执行process_responseRequest对象，停止中间件的执行，将Request重新调度器raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception"""passdef process_response(self, request, response, spider):"""spider处理完成，返回时调用:param response::param result::param spider::return: Response 对象：转交给其他中间件process_responseRequest 对象：停止中间件，request会被重新调度下载raise IgnoreRequest 异常：调用Request.errback"""print('response1')return responsedef process_exception(self, request, exception, spider):"""当下载处理器(download handler)或 process_request() (下载中间件)抛出异常:param response::param exception::param spider::return: None：继续交给后续中间件处理异常；Response对象：停止后续process_exception方法Request对象：停止中间件，request将会被重新调用下载"""return None

 

七、自定义命令

• 在 spiders 同级创建任意目录，如：commands
• 在其中创建 crawlall.py 文件 （此处文件名就是自定义的命令）

crawlall.py

from scrapy.commands import ScrapyCommand
from scrapy.utils.project import get_project_settingsclass Command(ScrapyCommand):requires_project = Truedef syntax(self):return '[options]'def short_desc(self):return 'Runs all of the spiders'def run(self, args, opts):spider_list = self.crawler_process.spiders.list()for name in spider_list:self.crawler_process.crawl(name, **opts.__dict__)self.crawler_process.start()

• 在 settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
• 在项目目录执行命令：scrapy crawlall 

 

八、自定义扩展（ 使用 信号 ）

自定义扩展时，使用 信号 在指定位置注册制定操作

自定义扩展

from scrapy import signalsclass MyExtension(object):def __init__(self, value):self.value = value@classmethoddef from_crawler(cls, crawler):val = crawler.settings.getint('MMMM')ext = cls(val)crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)return extdef spider_opened(self, spider):print('open')def spider_closed(self, spider):print('close')

 

九、避免重复访问

scrapy 默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：

DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'DUPEFILTER_DEBUG = FalseJOBDIR = "保存范文记录的日志路径，如：/root/"  # 最终路径为 /root/requests.seen　　

自定义 URL 去重操作

class RepeatUrl:def __init__(self):self.visited_url = set()@classmethoddef from_settings(cls, settings):"""初始化时，调用:param settings: :return: """return cls()def request_seen(self, request):"""检测当前请求是否已经被访问过:param request: :return: True表示已经访问过；False表示未访问过"""if request.url in self.visited_url:return Trueself.visited_url.add(request.url)return Falsedef open(self):"""开始爬去请求时，调用:return: """print('open replication')def close(self, reason):"""结束爬虫爬取时，调用:param reason: :return: """print('close replication')def log(self, request, spider):"""记录日志:param request: :param spider: :return: """print('repeat', request.url)

 

十、其他

# -*- coding: utf-8 -*-# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html# 1. 爬虫名称
BOT_NAME = 'step8_king'# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
#    使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
#     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#     'Accept-Language': 'en',
# }# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
#    'step8_king.pipelines.JsonPipeline': 700,
#    'step8_king.pipelines.FilePipeline': 500,
# }# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
#     # 'step8_king.extensions.MyExtension': 500,
# }# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html"""
17. 自动限速算法from scrapy.contrib.throttle import AutoThrottle自动限速设置1. 获取最小延迟 DOWNLOAD_DELAY2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCYtarget_delay = latency / self.target_concurrencynew_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间new_delay = max(target_delay, new_delay)new_delay = min(max(self.mindelay, new_delay), self.maxdelay)slot.delay = new_delay
"""# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings"""
18. 启用缓存目的用于将已经发送的请求或相应缓存下来，以便以后使用from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddlewarefrom scrapy.extensions.httpcache import DummyPolicyfrom scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'"""
19. 代理，需要在环境变量中设置from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware方式一：使用默认os.environ{http_proxy:http://root:woshiniba@192.168.11.11:9999/https_proxy:http://192.168.11.11:9999/}方式二：使用自定义下载中间件def to_bytes(text, encoding=None, errors='strict'):if isinstance(text, bytes):return textif not isinstance(text, six.string_types):raise TypeError('to_bytes must receive a unicode, str or bytes ''object, got %s' % type(text).__name__)if encoding is None:encoding = 'utf-8'return text.encode(encoding, errors)class ProxyMiddleware(object):def process_request(self, request, spider):PROXIES = [{'ip_port': '111.11.228.75:80', 'user_pass': ''},{'ip_port': '120.198.243.22:80', 'user_pass': ''},{'ip_port': '111.8.60.9:8123', 'user_pass': ''},{'ip_port': '101.71.27.120:80', 'user_pass': ''},{'ip_port': '122.96.59.104:80', 'user_pass': ''},{'ip_port': '122.224.249.122:8088', 'user_pass': ''},]proxy = random.choice(PROXIES)if proxy['user_pass'] is not None:request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)print "**************ProxyMiddleware have pass************" + proxy['ip_port']else:print "**************ProxyMiddleware no pass************" + proxy['ip_port']request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])DOWNLOADER_MIDDLEWARES = {'step8_king.middlewares.ProxyMiddleware': 500,}""""""
20. Https访问Https访问时有两种情况：1. 要爬取网站使用的可信任证书(默认支持)DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"2. 要爬取网站使用的自定义证书DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"# https.pyfrom scrapy.core.downloader.contextfactory import ScrapyClientContextFactoryfrom twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)class MySSLFactory(ScrapyClientContextFactory):def getCertificateOptions(self):from OpenSSL import cryptov1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())return CertificateOptions(privateKey=v1,  # pKey对象certificate=v2,  # X509对象verify=False,method=getattr(self, 'method', getattr(self, '_ssl_method', None)))其他：相关类scrapy.core.downloader.handlers.http.HttpDownloadHandlerscrapy.core.downloader.webclient.ScrapyHTTPClientFactoryscrapy.core.downloader.contextfactory.ScrapyClientContextFactory相关配置DOWNLOADER_HTTPCLIENTFACTORYDOWNLOADER_CLIENTCONTEXTFACTORY""""""
21. 爬虫中间件class SpiderMiddleware(object):def process_spider_input(self,response, spider):'''下载完成，执行，然后交给parse处理:param response: :param spider: :return: '''passdef process_spider_output(self,response, result, spider):'''spider处理完成，返回时调用:param response::param result::param spider::return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)'''return resultdef process_spider_exception(self,response, exception, spider):'''异常调用:param response::param exception::param spider::return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline'''return Nonedef process_start_requests(self,start_requests, spider):'''爬虫启动时调用:param start_requests::param spider::return: 包含 Request 对象的可迭代对象'''return start_requests内置爬虫中间件：'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {# 'step8_king.middlewares.SpiderMiddleware': 543,
}"""
22. 下载中间件class DownMiddleware1(object):def process_request(self, request, spider):'''请求需要被下载时，经过所有下载器中间件的process_request调用:param request::param spider::return:None,继续后续中间件去下载；Response对象，停止process_request的执行，开始执行process_responseRequest对象，停止中间件的执行，将Request重新调度器raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception'''passdef process_response(self, request, response, spider):'''spider处理完成，返回时调用:param response::param result::param spider::return:Response 对象：转交给其他中间件process_responseRequest 对象：停止中间件，request会被重新调度下载raise IgnoreRequest 异常：调用Request.errback'''print('response1')return responsedef process_exception(self, request, exception, spider):'''当下载处理器(download handler)或 process_request() (下载中间件)抛出异常:param response::param exception::param spider::return:None：继续交给后续中间件处理异常；Response对象：停止后续process_exception方法Request对象：停止中间件，request将会被重新调用下载'''return None默认下载中间件{'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,}"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
#    'step8_king.middlewares.DownMiddleware1': 100,
#    'step8_king.middlewares.DownMiddleware2': 500,
# }sittings

 

十一、TinyScrapy

参考版

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import types
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactorclass Request(object):def __init__(self, url, callback):self.url = urlself.callback = callbackself.priority = 0class HttpResponse(object):def __init__(self, content, request):self.content = contentself.request = requestclass ChouTiSpider(object):def start_requests(self):url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']for url in url_list:yield Request(url=url, callback=self.parse)def parse(self, response):print(response.request.url)# yield Request(url="http://www.baidu.com", callback=self.parse)from queue import Queue
Q = Queue()class CallLaterOnce(object):def __init__(self, func, *a, **kw):self._func = funcself._a = aself._kw = kwself._call = Nonedef schedule(self, delay=0):if self._call is None:self._call = reactor.callLater(delay, self)def cancel(self):if self._call:self._call.cancel()def __call__(self):self._call = Nonereturn self._func(*self._a, **self._kw)class Engine(object):def __init__(self):self.nextcall = Noneself.crawlling = []self.max = 5self._closewait = Nonedef get_response(self,content, request):response = HttpResponse(content, request)gen = request.callback(response)if isinstance(gen, types.GeneratorType):for req in gen:req.priority = request.priority + 1Q.put(req)def rm_crawlling(self,response,d):self.crawlling.remove(d)def _next_request(self,spider):if Q.qsize() == 0 and len(self.crawlling) == 0:self._closewait.callback(None)if len(self.crawlling) >= 5:returnwhile len(self.crawlling) < 5:try:req = Q.get(block=False)except Exception as e:req = Noneif not req:returnd = getPage(req.url.encode('utf-8'))self.crawlling.append(d)d.addCallback(self.get_response, req)d.addCallback(self.rm_crawlling,d)d.addCallback(lambda _: self.nextcall.schedule())@defer.inlineCallbacksdef crawl(self):spider = ChouTiSpider()start_requests = iter(spider.start_requests())flag = Truewhile flag:try:req = next(start_requests)Q.put(req)except StopIteration as e:flag = Falseself.nextcall = CallLaterOnce(self._next_request,spider)self.nextcall.schedule()self._closewait = defer.Deferred()yield self._closewait@defer.inlineCallbacksdef pp(self):yield self.crawl()_active = set()
obj = Engine()
d = obj.crawl()
_active.add(d)li = defer.DeferredList(_active)
li.addBoth(lambda _,*a,**kw: reactor.stop())reactor.run()

备注： 更多文档参见：https://scrapy-chs.readthedocs.io/zh_CN/latest/index.html