一、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、简介
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
三、基本使用
1.使用流程
1.创建项目 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.创建爬虫应用
scrapy genspider 爬虫名字 主页
- 创建爬虫应用
例如： scrapy gensipider -t basic oldboy oldboy.com
scrapy gensipider -t xmlfeed autohome autohome.com.cn
查看所有命令：scrapy gensipider -l
查看模板命令：scrapy gensipider -d 模板名称
3，用pycharm打开项目目录
会创建很多文件
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 爬虫模板目录，如：创建文件，编写爬虫规则
3.查看爬虫应用列表
scrapy list
4.配置
settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。
4.运行爬虫应用
scrapy crawl 爬虫应用名称 --nolog#不加日志
2.程序实例
#打开spiders/应用 #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
3.小试牛刀
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
class 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 = HtmlXPathSelector(response)
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
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 key
#重写start请求函数制定处理函数
def start_requests(self):
for url in self.start_urls:
yield Request(url,callback=self.next)
def next(self):
pass
总结：
- 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
三、 选择器（类似于标签选择器）
# -*- 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‘)找到所有a标签
# print(hxs)
# hxs = Selector(response=response).xpath(‘//a[2]‘)找到a标签
# print(hxs)
# hxs = Selector(response=response).xpath(‘//a[@id]‘)找到a标签有id的
# print(hxs)
# hxs = Selector(response=response).xpath(‘//a[@id="i1"]‘) 找到a标签切id=il的
# print(hxs)
# hxs = Selector(response=response).xpath(‘//a[@href="link.html"][@id="i1"]‘)找到a标签 href=link.html 且 id =il
# 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)
示例：自动登陆抽屉并点赞
自动登陆抽屉并点赞
-*- coding: utf-8 -*-
import scrapy
import sys,io
from scrapy.http import Request
from scrapy.selector import Selector, HtmlXPathSelector
from ..items import ChoutiItem
# 用于定位标签
sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding=‘gb18030‘)
from scrapy.http.cookies import CookieJar
class ChoutiSpider(scrapy.Spider):
name = "chouti"
allowed_domains = ["chouti.com"]
# allowed_domains = ["chouti.com",baidu.com] 域名限制
start_urls = [‘http://dig.chouti.com/‘]
cookie_dict=None
def parse(self, response):
cookie_obj=CookieJar()
cookie_obj.extract_cookies(response,response.request)
# response.request返回是访问对象
self.cookie_dict=cookie_obj._cookies
# 带上用户名密码+cookie
yield Request(
url="http://dig.chouti.com/login",
method=‘POST‘,
body="phone=8618731008140&password=cuiyuetian1988&oneMonth=1",
headers={‘Content-Type‘:‘application/x-www-form-urlencoded; charset=UTF-8‘},
cookies=cookie_obj._cookies,
callback=self.check_login
)
def check_login(self,response):
‘‘‘查看登录结果‘‘‘
print(response.text)
yield Request(url=‘http://dig.chouti.com/‘,callback=self.like)
def like(self,response):
‘‘‘点赞‘‘‘
id_list = Selector(response=response).xpath(‘//div[@share-linkid]/@share-linkid‘).extract()
for nid in id_list:
print(nid)
url = "http://dig.chouti.com/link/vote?linksId=%s" % nid
yield Request(
url=url,
method="POST",
cookies=self.cookie_dict,
callback=self.show
)
page_urls=Selector(response=response).xpath(‘//div[@id="dig_lcpage"]//a/@href‘).extract()
for page in page_urls:
url = "http://dig.chouti.com%s" % page
yield Request(url=url, callback=self.like)
def show(self,response):
print(response.text)
我写哟
四、 格式化处理（items.py）
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。
# -*- coding: utf-8 -*-
import scrapy,io,sys
from scrapy.http import Request
from scrapy.selector import Selector, HtmlXPathSelector
# sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding=‘gb18030‘)
from ..items import Xiaohua
class XiaohuSpider(scrapy.Spider):
name=‘xiaohua‘
allowed_domains = ["xiaohuar.com"]
start_urls = [‘http://xiaohuar.com/hua/‘]
vis=set()
def parse(self, response):
res=Selector(response=response).xpath(‘//div[@id="list_img"]//div[@class="item_t"]‘)
for obj in res:
src=obj.xpath(‘.//div[@class="img"]//img/@src‘).extract_first().strip()
name=obj.xpath(‘.//div[@class="img"]/span/text()‘).extract_first().strip()
src=‘http://xiaohuar.com%s‘%(src)
item_obj=Xiaohua(src=src,name=name)
yield item_obj
res2=Selector(response=response).xpath(‘//div[@id="page"]//a/@href‘)
for url in res2:
if not url:
continue
md_url = self.md5(url.extract())
if md_url in self.vis:
pass
else:
self.vis.add(md_url)
url = url.extract()
print(url)
yield Request(url=url,callback=self.parse)
def md5(self,url):
import hashlib
obj=hashlib.md5()
obj.update(bytes(url, encoding=‘utf-8‘))
return obj.hexdigest()
spiders/xiahuar.py
import scrapy
class Xiaohua(scrapy.Item):
src=scrapy.Field()
name=scrapy.Field()
items
import json
import os
import requests
class Myxiaohua(object):
def __init__(self):
if not os.path.exists(‘imgs‘):
os.makedirs(‘imgs‘)
def process_item(self, item, spider):
name="%s.jpg"%item[‘name‘]
print(item[‘src‘])
res = requests.get(item[‘src‘], stream=True)
res.encoding=‘utf-8‘
with open(os.path.join(‘imgs‘,name),‘wb‘) as f :
f.write(res.content)
return item
pipelines
ITEM_PIPELINES = {
‘myscrapy1.pipelines.Myscrapy1Pipeline‘: 300,
‘myscrapy1.pipelines.Myxiaohua‘: 300,
}
#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。
setting
五、自定制命令
- 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）
- 待续。。。。
六、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
extensions
EXTENSIONS = {
# ‘scrapy.extensions.telnet.TelnetConsole‘: None,
‘myscrapy1.extensions.MyExtend‘: 300,
}
setting
七、自定义避免重复访问
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)
自定义URL去重操作
说明
# from scrapy.dupefilters import RFPDupeFilter
class RepeatFilter(object):
def __init__(self):
self.visited_set=set()
@classmethod
def from_settings(cls, settings):
return cls()
def request_seen(self, request):
if request.url in self.visited_set:
return True
self.visited_set.add(request.url)
return False
def open(self): # can return deferred
print(‘start...‘)
pass
def close(self, reason): # can return a deferred
print(‘close...‘)
pass
def log(self, request, spider): # log that a request has been filtered
pass
myduplication.py
DUPEFILTER_CLASS=‘myscrapy1.myduplication.RepeatFilter‘
setting
八、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请求头客户端 user-agent请求头会带着你的BOT_NAME
# USER_AGENT = ‘step8_king (+http://www.yourdomain.com)‘
# 可以进行伪装成浏览器USER_AGENT = ‘Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36‘
# Obey robots.txt rules
# 4. 禁止爬虫配置是否遵循反爬虫规则
# ROBOTSTXT_OBEY = False
# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数（根据反爬虫能力制定并发）
# 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 帮我们
# 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:[email protected]: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,
# }
settings
时间： 2024-08-08 17:45:43