Python 爬虫 性能 相关（ asyncio 模块 --- 高性能爬虫 ）
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爬虫应用 asyncio 模块 ( 高性能爬虫 )：
python异步编程之asyncio（百万并发）：
深入理解 Python 异步编程(上)：
requests + asyncio ：
python 高并发模块 asynio：
aiohttp 官网文档 ：
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 ThreadPoolExecutorimport 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 ThreadPoolExecutorimport 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 ProcessPoolExecutorimport 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 ProcessPoolExecutorimport 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：
python---异步IO(asyncio)协程 ：
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.coroutinedef 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.coroutinedef 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：
用 aiohttp 写爬虫：
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 asynciofrom 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 timeimport asynciofrom 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 datetimeimport asynciofrom 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-8import 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500 to_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 aiohttpimport asyncio@asyncio.coroutinedef 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 asyncioimport aiohttpCONCURRENT_REQUESTS = 0async def aio_http_get(url, session): global CONCURRENT_REQUESTS async with session.get(url) as response: CONCURRENT_REQUESTS += 1 html = 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 asynciofrom 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 osimport sysimport aiohttpimport asynciosys.path.append(os.getcwd())sys.path.append("..")sys.path.append(os.path.abspath("../../"))CONCURRENT_REQUESTS = 20CONCURRENT_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) # this for 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 asyncioimport requests@asyncio.coroutinedef fetch_async(func, *args): loop = asyncio.get_event_loop() future = loop.run_in_executor(None, func, *args) response = yield from future print(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 requestsfrom 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, deferfrom 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 AsyncHTTPClientfrom tornado.httpclient import HTTPRequestfrom 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 reactorfrom twisted.web.client import getPageimport 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 selectimport socketimport timeclass AsyncTimeoutException(TimeoutError): """ 请求超时异常类 """ def __init__(self, msg): self.msg = msg super(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URL data: 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 = sock self.callback = callback self.host = host self.port = port self.method = method self.url = url self.data = data self.timeout = timeout self.__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 True def 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: return for context in r: sock = context.sock while True: try: data = sock.recv(8096) if not data: self.fds.remove(context) context.finish() break else: context.write(data) except BlockingIOError as e: break except TimeoutError as e: self.fds.remove(context) self.connections.remove(context) context.finish(e) break for 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：
- 引擎从调度器中取出一个链接(URL)用于接下来的抓取
- 引擎把URL封装成一个请求(Request)传给下载器
- 下载器把资源下载下来，并封装成应答包(Response)
- 爬虫解析Response
- 解析出实体（Item）,则交给实体管道进行进一步的处理
- 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]- 创建爬虫应用 如： scrapy gensipider -t basic oldboy oldboy.com scrapy gensipider -t xmlfeed autohome autohome.com.cn PS: 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.cfg project_name/ __init__.py items.py pipelines.py settings.py spiders/ __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 scrapy class 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,ossys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
三、开始项目
# -*- coding: utf-8 -*-import scrapyfrom scrapy.selector import Selectorfrom 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URL start_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' % page key = self.md5(page_url) if key in self.has_request_set: pass else: self.has_request_set[key] = page_url obj = Request(url=page_url, method='GET', callback=self.parse) yield obj @staticmethod def md5(val): import hashlib ha = hashlib.md5() ha.update(bytes(val, encoding='utf-8')) key = ha.hexdigest() return keyif __name__ == '__main__': from scrapy import cmdline cmdline.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 Selectorfrom scrapy.http import HtmlResponsehtml = """"""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)
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# -*- coding: utf-8 -*-import scrapyfrom scrapy.selector import Selectorfrom scrapy.http.request import Requestfrom scrapy.http.cookies import CookieJarfrom 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.value req = 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 req def check_login(self, response): req = Request( url='http://dig.chouti.com/', method='GET', callback=self.show, cookies=self.cookie_dict, dont_filter=True ) yield req def 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' % page import hashlib hash = hashlib.md5() hash.update(bytes(page_url, encoding='utf-8')) key = hash.hexdigest() if key in self.has_request_set: pass else: self.has_request_set[key] = page_url yield Request( url=page_url, method='GET', callback=self.show ) def do_favor(self, response): print(response.text)if __name__ == '__main__': from scrapy import cmdline cmdline.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 scrapyfrom scrapy.selector import Selectorfrom scrapy.http.request import Requestfrom scrapy.http.cookies import CookieJarfrom scrapy import FormRequestfrom ..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" % src obj = XiaoHuarItem(name=name, school=school, url=url) yield obj urls = 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: pass else: self.has_request_set[key] = url req = Request(url=url, method='GET', callback=self.parse) yield req @staticmethod def md5(val): import hashlib ha = 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 scrapyfrom scrapy.selector import Selectorfrom scrapy.http.request import Requestfrom scrapy.http.cookies import CookieJarfrom 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" % src obj = dict( name=name, school=school, url=url ) yield obj urls = 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: pass else: self.has_request_set[key] = url req = Request(url=url, method='GET', callback=self.parse) yield req @staticmethod def md5(val): import hashlib ha = hashlib.md5() ha.update(bytes(val, encoding='utf-8')) key = ha.hexdigest() return key pipelines
import jsonimport osimport 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 = v def 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() @classmethod def 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: """ pass def 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 result def 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 None def 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_response Request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 """ pass def 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_response Request 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 response def 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 ScrapyCommandfrom scrapy.utils.project import get_project_settings class Command(ScrapyCommand): requires_project = True def 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 @classmethod def 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 ext def 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() @classmethod def 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 True self.visited_url.add(request.url) return False def 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_DELAY 2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY 3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY 4. 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_CONCURRENCY target_delay = latency / self.target_concurrency new_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 HttpCacheMiddleware from scrapy.extensions.httpcache import DummyPolicy from 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 text if 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.py from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate) class MySSLFactory(ScrapyClientContextFactory): def getCertificateOptions(self): from OpenSSL import crypto v1 = 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.HttpDownloadHandler scrapy.core.downloader.webclient.ScrapyHTTPClientFactory scrapy.core.downloader.contextfactory.ScrapyClientContextFactory 相关配置 DOWNLOADER_HTTPCLIENTFACTORY DOWNLOADER_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: ''' pass def 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 result def 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 None def 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.htmlSPIDER_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_response Request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 ''' pass def 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_response Request 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 response def 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 typesfrom twisted.internet import deferfrom twisted.web.client import getPagefrom twisted.internet import reactorclass Request(object): def __init__(self, url, callback): self.url = url self.callback = callback self.priority = 0class HttpResponse(object): def __init__(self, content, request): self.content = content self.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 QueueQ = Queue()class CallLaterOnce(object): def __init__(self, func, *a, **kw): self._func = func self._a = a self._kw = kw self._call = None def 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 = None return self._func(*self._a, **self._kw)class Engine(object): def __init__(self): self.nextcall = None self.crawlling = [] self.max = 5 self._closewait = None def 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 + 1 Q.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: return while len(self.crawlling) < 5: try: req = Q.get(block=False) except Exception as e: req = None if not req: return d = 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.inlineCallbacks def crawl(self): spider = ChouTiSpider() start_requests = iter(spider.start_requests()) flag = True while flag: try: req = next(start_requests) Q.put(req) except StopIteration as e: flag = False self.nextcall = CallLaterOnce(self._next_request,spider) self.nextcall.schedule() self._closewait = defer.Deferred() yield self._closewait @defer.inlineCallbacks def 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：
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