python爬虫Scrapy及其性能相关
爬虫性能相关 |
在编写爬虫时,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。
1 import requests 2 3 def fetch_async(url): 4 response = requests.get(url) 5 return response 6 7 8 url_list = ['http://www.github.com', 'http://www.bing.com'] 9 10 for url in url_list: 11 fetch_async(url) 12 13 1.同步执行
1 from concurrent.futures import ThreadPoolExecutor 2 import requests 3 4 5 def fetch_async(url): 6 response = requests.get(url) 7 return response 8 9 10 url_list = ['http://www.github.com', 'http://www.bing.com'] 11 pool = ThreadPoolExecutor(5) 12 for url in url_list: 13 pool.submit(fetch_async, url) 14 pool.shutdown(wait=True)
1 from concurrent.futures import ThreadPoolExecutor 2 import requests 3 4 def fetch_async(url): 5 response = requests.get(url) 6 return response 7 8 9 def callback(future): 10 print(future.result()) 11 12 13 url_list = ['http://www.github.com', 'http://www.bing.com'] 14 pool = ThreadPoolExecutor(5) 15 for url in url_list: 16 v = pool.submit(fetch_async, url) 17 v.add_done_callback(callback) 18 pool.shutdown(wait=True)
1 from concurrent.futures import ProcessPoolExecutor 2 import requests 3 4 def fetch_async(url): 5 response = requests.get(url) 6 return response 7 8 9 url_list = ['http://www.github.com', 'http://www.bing.com'] 10 pool = ProcessPoolExecutor(5) 11 for url in url_list: 12 pool.submit(fetch_async, url) 13 pool.shutdown(wait=True)
from concurrent.futures import ProcessPoolExecutor import requests def fetch_async(url): response = requests.get(url) return response def 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,对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费,所以异步IO回事首选:
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()
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()
import aiohttp import asyncio @asyncio.coroutine def fetch_async(url): print(url) response = yield from aiohttp.request('GET', url) # data = yield from response.read() # print(url, data) print(url, response) response.close() tasks = [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()
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 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()
import gevent import requests from gevent import monkey monkey.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={}), # ])
import grequests request_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)
1 from twisted.web.client import getPage, defer 2 from twisted.internet import reactor 3 4 5 def all_done(arg): 6 reactor.stop() 7 8 9 def callback(contents): 10 print(contents) 11 12 13 deferred_list = [] 14 15 url_list = ['http://www.bing.com', 'http://www.baidu.com', ] 16 for url in url_list: 17 deferred = getPage(bytes(url, encoding='utf8')) 18 deferred.addCallback(callback) 19 deferred_list.append(deferred) 20 21 dlist = defer.DeferredList(deferred_list) 22 dlist.addBoth(all_done) 23 24 reactor.run()
1 from tornado.httpclient import AsyncHTTPClient 2 from tornado.httpclient import HTTPRequest 3 from tornado import ioloop 4 5 6 def handle_response(response): 7 """ 8 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() 9 :param response: 10 :return: 11 """ 12 if response.error: 13 print("Error:", response.error) 14 else: 15 print(response.body) 16 17 18 def func(): 19 url_list = [ 20 'http://www.baidu.com', 21 'http://www.bing.com', 22 ] 23 for url in url_list: 24 print(url) 25 http_client = AsyncHTTPClient() 26 http_client.fetch(HTTPRequest(url), handle_response) 27 28 29 ioloop.IOLoop.current().add_callback(func) 30 ioloop.IOLoop.current().start()
1 from twisted.internet import reactor 2 from twisted.web.client import getPage 3 import urllib.parse 4 5 6 def one_done(arg): 7 print(arg) 8 reactor.stop() 9 10 post_data = urllib.parse.urlencode({'check_data': 'adf'}) 11 post_data = bytes(post_data, encoding='utf8') 12 headers = {b'Content-Type': b'application/x-www-form-urlencoded'} 13 response = getPage(bytes('http://dig.chouti.com/login', encoding='utf8'), 14 method=bytes('POST', encoding='utf8'), 15 postdata=post_data, 16 cookies={}, 17 headers=headers) 18 response.addBoth(one_done) 19 20 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】:
1 import select 2 import socket 3 import time 4 5 6 class AsyncTimeoutException(TimeoutError): 7 """ 8 请求超时异常类 9 """ 10 11 def __init__(self, msg): 12 self.msg = msg 13 super(AsyncTimeoutException, self).__init__(msg) 14 15 16 class HttpContext(object): 17 """封装请求和相应的基本数据""" 18 19 def __init__(self, sock, host, port, method, url, data, callback, timeout=5): 20 """ 21 sock: 请求的客户端socket对象 22 host: 请求的主机名 23 port: 请求的端口 24 port: 请求的端口 25 method: 请求方式 26 url: 请求的URL 27 data: 请求时请求体中的数据 28 callback: 请求完成后的回调函数 29 timeout: 请求的超时时间 30 """ 31 self.sock = sock 32 self.callback = callback 33 self.host = host 34 self.port = port 35 self.method = method 36 self.url = url 37 self.data = data 38 39 self.timeout = timeout 40 41 self.__start_time = time.time() 42 self.__buffer = [] 43 44 def is_timeout(self): 45 """当前请求是否已经超时""" 46 current_time = time.time() 47 if (self.__start_time + self.timeout) < current_time: 48 return True 49 50 def fileno(self): 51 """请求sockect对象的文件描述符,用于select监听""" 52 return self.sock.fileno() 53 54 def write(self, data): 55 """在buffer中写入响应内容""" 56 self.__buffer.append(data) 57 58 def finish(self, exc=None): 59 """在buffer中写入响应内容完成,执行请求的回调函数""" 60 if not exc: 61 response = b''.join(self.__buffer) 62 self.callback(self, response, exc) 63 else: 64 self.callback(self, None, exc) 65 66 def send_request_data(self): 67 content = """%s %s HTTP/1.0\r\nHost: %s\r\n\r\n%s""" % ( 68 self.method.upper(), self.url, self.host, self.data,) 69 70 return content.encode(encoding='utf8') 71 72 73 class AsyncRequest(object): 74 def __init__(self): 75 self.fds = [] 76 self.connections = [] 77 78 def add_request(self, host, port, method, url, data, callback, timeout): 79 """创建一个要请求""" 80 client = socket.socket() 81 client.setblocking(False) 82 try: 83 client.connect((host, port)) 84 except BlockingIOError as e: 85 pass 86 # print('已经向远程发送连接的请求') 87 req = HttpContext(client, host, port, method, url, data, callback, timeout) 88 self.connections.append(req) 89 self.fds.append(req) 90 91 def check_conn_timeout(self): 92 """检查所有的请求,是否有已经连接超时,如果有则终止""" 93 timeout_list = [] 94 for context in self.connections: 95 if context.is_timeout(): 96 timeout_list.append(context) 97 for context in timeout_list: 98 context.finish(AsyncTimeoutException('请求超时')) 99 self.fds.remove(context) 100 self.connections.remove(context) 101 102 def running(self): 103 """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""" 104 while True: 105 r, w, e = select.select(self.fds, self.connections, self.fds, 0.05) 106 107 if not self.fds: 108 return 109 110 for context in r: 111 sock = context.sock 112 while True: 113 try: 114 data = sock.recv(8096) 115 if not data: 116 self.fds.remove(context) 117 context.finish() 118 break 119 else: 120 context.write(data) 121 except BlockingIOError as e: 122 break 123 except TimeoutError as e: 124 self.fds.remove(context) 125 self.connections.remove(context) 126 context.finish(e) 127 break 128 129 for context in w: 130 # 已经连接成功远程服务器,开始向远程发送请求数据 131 if context in self.fds: 132 data = context.send_request_data() 133 context.sock.sendall(data) 134 self.connections.remove(context) 135 136 self.check_conn_timeout() 137 138 139 if __name__ == '__main__': 140 def callback_func(context, response, ex): 141 """ 142 :param context: HttpContext对象,内部封装了请求相关信息 143 :param response: 请求响应内容 144 :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) 145 :return: 146 """ 147 print(context, response, ex) 148 149 obj = AsyncRequest() 150 url_list = [ 151 {'host': 'www.google.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5, 152 'callback': callback_func}, 153 {'host': 'www.baidu.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5, 154 'callback': callback_func}, 155 {'host': 'www.bing.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5, 156 'callback': callback_func}, 157 ] 158 for item in url_list: 159 print(item) 160 obj.add_request(**item) 161 162 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
1、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.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
2、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 = ["xiaohuar.com"] # 允许的域名 start_urls = [ "http://www.xiaohuar.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
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
1 import scrapy 2 from scrapy.selector import HtmlXPathSelector 3 from scrapy.http.request import Request 4 5 6 class DigSpider(scrapy.Spider): 7 # 爬虫应用的名称,通过此名称启动爬虫命令 8 name = "dig" 9 10 # 允许的域名 11 allowed_domains = ["chouti.com"] 12 13 # 起始URL 14 start_urls = [ 15 'http://dig.chouti.com/', 16 ] 17 18 has_request_set = {} 19 20 def parse(self, response): 21 print(response.url) 22 23 hxs = HtmlXPathSelector(response) 24 page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract() 25 for page in page_list: 26 page_url = 'http://dig.chouti.com%s' % page 27 key = self.md5(page_url) 28 if key in self.has_request_set: 29 pass 30 else: 31 self.has_request_set[key] = page_url 32 obj = Request(url=page_url, method='GET', callback=self.parse) 33 yield obj 34 35 @staticmethod 36 def md5(val): 37 import hashlib 38 ha = hashlib.md5() 39 ha.update(bytes(val, encoding='utf-8')) 40 key = ha.hexdigest() 41 return key
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
- HtmlXpathSelector用于结构化HTML代码并提供选择器功能
四、scrapy的选择器
#!/usr/bin/env python # -*- coding:utf-8 -*- from scrapy.selector import Selector, HtmlXPathSelector 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 = HtmlXPathSelector(response) # print(hxs) # 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('//a[re:test(@id, "i\d+")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # print(hxs) # hxs = Selector(response=response).xpath('//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)
# -*- coding: utf-8 -*- import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request from scrapy.http.cookies import CookieJar from scrapy import FormRequest class 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 = HtmlXPathSelector(response) news_list = hxs.select('//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.select('//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)
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。
import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request from scrapy.http.cookies import CookieJar from scrapy import FormRequest class 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 = ["xiaohuar.com"] start_urls = [ "http://www.xiaohuar.com/list-1-1.html", ] # 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 = HtmlXPathSelector(response) items = hxs.select('//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 from ..items import XiaoHuarItem obj = XiaoHuarItem(name=name, school=school, url=url) yield obj urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.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
import scrapy class XiaoHuarItem(scrapy.Item): name = scrapy.Field() school = scrapy.Field() url = scrapy.Field()
import json import os import requests class 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 item class 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
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:
from scrapy.exceptions import DropItem class 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
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
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 下载器中间件
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)
from scrapy.commands import ScrapyCommand from 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
自定义扩展时,利用信号在指定位置注册制定操作
from scrapy import signals class 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 = False JOBDIR = "保存范文记录的日志路径,如:/root/" # 最终路径为 /root/requests.seen
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.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_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, # }
十一、TinyScrapy
#!/usr/bin/env python # -*- coding:utf-8 -*- import types from twisted.internet import defer from twisted.web.client import getPage from twisted.internet import reactor class Request(object): def __init__(self, url, callback): self.url = url self.callback = callback self.priority = 0 class HttpResponse(object): def __init__(self, content, request): self.content = content self.request = request class 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 = 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:http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html